@article {Filali20222174,
	title = {Dynamic SDN-Based Radio Access Network Slicing With Deep Reinforcement Learning for URLLC and eMBB Services},
	journal = {IEEE Transactions on Network Science and Engineering},
	volume = {9},
	number = {4},
	year = {2022},
	note = {cited By 3},
	pages = {2174-2187},
	abstract = {Radio access network (RAN) slicing is a key technology that enables 5G network to support heterogeneous requirements of generic services, namely ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB). In this paper, we propose a two time-scales RAN slicing mechanism to optimize the performance of URLLC and eMBB services. In a large time-scale, an SDN controller allocates radio resources to gNodeBs according to the requirements of the eMBB and URLLC services. In a short time-scale, each gNodeB allocates its available resources to its end-users and requests, if needed, additional resources from adjacent gNodeBs. We formulate this problem as a non-linear binary program and prove its NP-hardness. Next, for each time-scale, we model the problem as a Markov decision process (MDP), where the large-time scale is modeled as a single agent MDP whereas the shorter time-scale is modeled as a multi-agent MDP. We leverage the exponential-weight algorithm for exploration and exploitation (EXP3) to solve the single-agent MDP of the large time-scale MDP and the multi-agent deep Q-learning (DQL) algorithm to solve the multi-agent MDP of the short time-scale resource allocation. Extensive simulations show that our approach is efficient under different network parameters configuration and it outperforms recent benchmark solutions. {\textcopyright} 2013 IEEE.},
	keywords = {5G mobile communication systems, Deep learning, EMBB, Heuristic algorithms, Heuristics algorithm, Learning algorithms, Low-latency communication, Markov processes, Multi agent systems, Network slicing, Optimisations, Optimization, Quality of service, Quality-of-service, Radio access networks, Reinforcement learning, Resource allocation, Resource Management, Software agents, Software defined networking, Software-defined networkings, Time measurement, Ultra reliable low latency communication, URLLC},
	doi = {10.1109/TNSE.2022.3157274},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126273319\&doi=10.1109\%2fTNSE.2022.3157274\&partnerID=40\&md5=44d6a41c3d7b8b6d8c4d6918856f36c5},
	author = {Filali, A. and Mlika, Z. and Cherkaoui, S. and Kobbane, A.}
}
@article {Ahajjam2022,
	title = {Experimental investigation of variational mode decomposition and deep learning for short-term multi-horizon residential electric load forecasting},
	journal = {Applied Energy},
	volume = {326},
	year = {2022},
	note = {cited By 0},
	abstract = {With the booming growth of advanced digital technologies, it has become possible for users as well as distributors of energy to obtain detailed and timely information about the electricity consumption of households. These technologies can also be used to forecast the household{\textquoteright}s electricity consumption (a.k.a. the load). In this paper, Variational Mode Decomposition and deep learning techniques are investigated as a way to improve the accuracy of the load forecasting problem. Although this problem has been studied in the literature, selecting an appropriate decomposition level and a deep learning technique providing better forecasting performance have garnered comparatively less attention. This study bridges this gap by studying the effect of six decomposition levels and five distinct deep learning networks. The raw load profiles are first decomposed into intrinsic mode functions using the Variational Mode Decomposition in order to mitigate their non-stationary aspect. Then, day, hour, and past electricity consumption data are fed as a three-dimensional input sequence to a four-level Wavelet Decomposition Network model. Finally, the forecast sequences related to the different intrinsic mode functions are combined to form the aggregate forecast sequence. The proposed method was assessed using load profiles of five Moroccan households from the Moroccan buildings{\textquoteright} electricity consumption dataset (MORED) and was benchmarked against state-of-the-art time-series models and a baseline persistence model. {\textcopyright} 2022 Elsevier Ltd},
	keywords = {data set, decomposition, Decomposition level, Deep learning, Electric load forecasting, Electric power plant loads, Electric power utilization, electricity, electricity supply, Electricity-consumption, Experimental investigations, forecasting method, Housing, Intrinsic mode functions, learning, Learning algorithms, Learning systems, Learning techniques, Load profiles, Multi-horizon forecasting, Residential load forecasting, Short-term residential load forecasting, Variational mode decomposition, Wavelet decomposition},
	doi = {10.1016/j.apenergy.2022.119963},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138343844\&doi=10.1016\%2fj.apenergy.2022.119963\&partnerID=40\&md5=322ce14ee40d2de7bbdfa72a4aabc718},
	author = {Ahajjam, M.A. and Bonilla Licea, D. and Ghogho, M. and Kobbane, A.}
}
@article {Gryech2022,
	title = {An Exploration of Features Impacting Respiratory Diseases in Urban Areas},
	journal = {International Journal of Environmental Research and Public Health},
	volume = {19},
	number = {5},
	year = {2022},
	note = {cited By 3},
	abstract = {Air pollution exposure has become ubiquitous and is increasingly detrimental to human health. Small Particulate matter (PM) is one of the most harmful forms of air pollution. It can easily infiltrate the lungs and trigger several respiratory diseases, especially in vulnerable populations such as children and elderly people. In this work, we start by leveraging a retrospective study of 416 children suffering from respiratory diseases. The study revealed that asthma prevalence was the most common among several respiratory diseases, and that most patients suffering from those diseases live in areas of high traffic, noise, and greenness. This paved the way to the construction of the MOREAIR dataset by combining feature abstraction and micro-level scale data collection. Unlike existing data sets, MOREAIR is rich in context-specific components, as it includes 52 temporal or geographical features, in addition to air-quality measurements. The use of Random Forest uncovered the most important features for the understanding of air-quality distribution in Moroccan urban areas. By linking the medical data and the MOREAIR dataset, we observed that the patients included in the medical study come mostly from neighborhoods that are characterized by either high average or high variations of pollution levels. {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.},
	keywords = {aged, air pollutant, Air Pollutants, Air pollution, Air quality, air quality control, Article, asthma, breathing disorder, child, controlled study, disease risk assessment, environmental exposure, environmental risk, exploratory research, geographic information system, GIS, health risk, human, Humans, major clinical study, Measurement, medical information, Moroccan, neighborhood, noise injury, Particulate Matter, prevalence, public health, random forest, Respiration Disorders, respiratory disease, respiratory tract disease, Retrospective Studies, retrospective study, Risk assessment, risk factor, traffic pollution, urban area},
	doi = {10.3390/ijerph19053095},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125596721\&doi=10.3390\%2fijerph19053095\&partnerID=40\&md5=011cdce4b84286477d86b54655147f71},
	author = {Gryech, I. and Ghogho, M. and Mahraoui, C. and Kobbane, A.}
}
@conference {Rachidi202213,
	title = {Network intrusion detection using Machine Learning approach},
	booktitle = {ACM International Conference Proceeding Series},
	year = {2022},
	note = {cited By 0},
	pages = {13-17},
	abstract = {Today, intrusion detection has become an active research area. Due to the rapidly increasing number of intrusion variants, intrusion detection system analyses and notifies the activities of users as normal (or) anomaly. In our paper, we built a model of intrusion detection system applied to the NSL-KDD data set using different supervised classifiers such as KNN and Na{\"\i}ve Bayes. We also proposed two algorithms for multi-classification based on the Random Forest (RF) which is an ensemble classifier and KNN. Then we used the K-folds method to evaluate and validate our model. To evaluate the performances, we realized experiments on NSL-KDD data set. The result shows that the second proposed algorithm is efficient with high accuracy and time optimization. {\textcopyright} 2022 ACM.},
	keywords = {Barium compounds, Classification (of information), Computer crime, data set, Decision trees, Intrusion detection, Intrusion Detection Systems, Intrusion-Detection, Machine learning, Machine learning approaches, Multi-classification, Network intrusion detection, NSL-KDD, Random forests, Research areas, Sodium compounds, Supervised classifiers},
	doi = {10.1145/3551690.3551693},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139141127\&doi=10.1145\%2f3551690.3551693\&partnerID=40\&md5=e47a5f8038487b706673543f7fdf2de4},
	author = {Rachidi, Z. and Chougdali, K. and Kobbane, A. and Ben-Othman, J.}
}
@conference {Elhachimi2022,
	title = {Secure Internet of Thing using Blockchain Technology},
	booktitle = {2022 7th International Conference on Smart and Sustainable Technologies, SpliTech 2022},
	year = {2022},
	note = {cited By 0},
	abstract = {With their vast range of uses, Internet of things (IoT) and its applications are becoming more popular. However, the security and privacy of the IoT-based applications remains a worry. The majority of the privacy and security issues of the interconnected, diverse resource-constrained IoT devices are unable to be solved efficiently by traditional security protocols. Blockchain technology has emerged as a distributed ledger technology or data structure that can manage many intelligent IoT transactions and ensure greater security to data management. In this paper, we propose a light-weight authentication system based Blockchain approach that provides network and communication security. Due to Blockchain decentralized nature and transparency, the proposed approach ensures high-level data security, improves system operation efficiency and system performances. {\textcopyright} 2022 University of Split, FESB.},
	keywords = {Authentication systems, Block-chain, Blockchain, Data privacy, Distributed ledger, Information management, Internet of thing security, Internet of things, ITS applications, Light weight, Network security, Privacy and security, Privacy issue, Security and privacy, Security issues, Security protocols},
	doi = {10.23919/SpliTech55088.2022.9854376},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138143921\&doi=10.23919\%2fSpliTech55088.2022.9854376\&partnerID=40\&md5=166e29d5aefdeeb4fac8936bf1150d04},
	author = {Elhachimi, J. and Kobbane, A.}
}
@article {Abouaomar2022,
	title = {Service Function Chaining in MEC: A Mean-Field Game and Reinforcement Learning Approach},
	journal = {IEEE Systems Journal},
	year = {2022},
	note = {cited By 0},
	pages = {1-12},
	abstract = {Multiaccess edge computing (MEC) and network virtualization technologies are important enablers for fifth generation networks to deliver diverse services. Services are often provided as fully connected virtual network functions (VNFs), through service function chaining (SFC). However, the problem of allocating SFC resources at the edge still faces many challenges related to the way VNFs are placed, chained, and scheduled. In this article, to solve these problems, we propose a game theory-based approach with the objective to reduce service latency in the context of SFC at the edge. The problem of allocating SFC resources can be divided into two subproblems: 1) the VNF placement and routing subproblem, and 2) the VNF scheduling subproblem. For the former subproblem, we formulate it as a mean-field game in which VNFs are contending over edge resources aiming at reducing the resource consumption of MEC nodes and reducing latency for users. We also propose a reinforcement learning-based technique, where the Ishikawa{\textendash}Mann learning algorithm is used. For the later subproblem, we formulate it as a matching game between VFNs and edge resources to find the execution order of the VNFs while reducing the latency. To efficiently solve it, we propose a modified version of the many-to-one deferred acceptance algorithm (DAA), called the enhanced multistep DAA. To illustrate the performance of the proposed approaches, we perform extensive simulations. The results show that the approaches achieve up to 40\% less resource consumption, and up to 38\% less latency than the benchmarked state-of-the-art methods. IEEE},
	keywords = {Computation theory, Computer games, Edge computing, Game, Game theory, Learning algorithms, Network function virtualization, Problem solving, Processor scheduling, Reinforcement learning, Resource allocation, Resource allocation/provisioning, Resource Management, Resources allocation, Routings, Scheduling, Service function chaining, Service functions, Transfer functions, Virtual reality, Virtualizations},
	doi = {10.1109/JSYST.2022.3171232},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131721006\&doi=10.1109\%2fJSYST.2022.3171232\&partnerID=40\&md5=e7ecad4d011f9a66bf06f1e9f3f4d176},
	author = {Abouaomar, A. and Cherkaoui, S. and Mlika, Z. and Kobbane, A.}
}
@conference {Ben-Aboud2021,
	title = {Acquisition and time-series analysis of electromagnetic pollution data},
	booktitle = {2021 17th International Conference on Intelligent Environments, IE 2021 - Proceedings},
	year = {2021},
	note = {cited By 0},
	abstract = {With the increasing use of wireless communication technologies, it is important to monitor electromagnetic exposure, ideally with high temporal and spatial resolutions. This paper presents our low-cost electro-smog measurement process, covering hardware selection, RF power measurement, and RF power correction. Then, a time series analysis is performed on the electromagnetic exposure data collected in the city of Sala Al Jadida - Morocco for seven days. The results show that the electro-smog exposure has a strong predictable pattern and a preliminary time series model is derived. {\textcopyright} 2021 IEEE.},
	keywords = {Air pollution, Electro magnetic pollution, Electromagnetic exposure, Hardware selection, Harmonic analysis, Intelligent agents, Low costs, Measurement process, Temporal and spatial, Time series analysis, Time series modeling, Wireless communication technology},
	doi = {10.1109/IE51775.2021.9486565},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114504253\&doi=10.1109\%2fIE51775.2021.9486565\&partnerID=40\&md5=8958a981795705a145d39c5225a3dd66},
	author = {Ben-Aboud, Y. and Ghogho, M. and Pollin, S. and Kobbane, A.}
}
@article {Mabrouk2021,
	title = {A cooperative game based mechanism for autonomous organization and ubiquitous connectivity in VANETs},
	journal = {Simulation Modelling Practice and Theory},
	volume = {107},
	year = {2021},
	note = {cited By 7},
	abstract = {Vehicular communications in Vehicular Ad-hoc NETworks (VANETs) play an interesting role in improving traffic flow on the roads. In such wireless networks, the vehicles cooperate with each other or with the roadside infrastructure to disseminate the data. In this paper, we introduce a mechanism based on coalitional game theory to study the cooperative transmission in VANETs. Each vehicle tries to access the Internet via gateways that can be either fixed or mobile. However, these gateways help the vehicles to access the Internet by cooperatively relaying the vehicles{\textquoteright} messages. Thus, two notions to indicate the availability of transmission between vehicles and gateways are introduced. These notions are chosen to deal with the highly dynamic topology in VANETs, namely the notion of an encounter and the notion of a link{\textquoteright}s predicted lifetime. The problem is modelled as a non-transferable utility game. Then, an algorithm is proposed to dynamically form coalitions among the vehicles. Moreover, a probability of being active is set in terms of speed of the received vehicle. To evaluate the proposed solution, two scenarios are used: fixed gateways scenario and mobile gateways scenario. The numerical results show that the scenario of mobile gateways is more effective in terms of stimulating vehicles to regroup into coalitions. Hence, this helps the vehicles to access the Internet. {\textcopyright} 2020},
	keywords = {Coalitional game theory, Cooperative game, Cooperative transmission, Dynamic topologies, Game theory, Gateways (Computer networks), Non-transferable utilities, Numerical results, Probability, Vehicle transmissions, Vehicular ad hoc networks, Vehicular Adhoc Networks (VANETs), Vehicular communications},
	doi = {10.1016/j.simpat.2020.102213},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093923113\&doi=10.1016\%2fj.simpat.2020.102213\&partnerID=40\&md5=3ede889d7bb9d063f8c8265857ff2ede},
	author = {Mabrouk, A. and Naja, A. and Oualhaj, O.A. and Kobbane, A. and Boulmalf, M.}
}
@conference {Abouaomar2021273,
	title = {A deep reinforcement learning approach for service migration in MEC-enabled vehicular networks},
	booktitle = {Proceedings - Conference on Local Computer Networks, LCN},
	volume = {2021-October},
	year = {2021},
	note = {cited By 4},
	pages = {273-280},
	abstract = {Multi-access edge computing (MEC) is a key enabler to reduce the latency of vehicular network. Due to the vehicles mobility, their requested services (e.g., infotainment services) should frequently be migrated across different MEC servers to guarantee their stringent quality of service requirements. In this paper, we study the problem of service migration in a MEC-enabled vehicular network in order to minimize the total service latency and migration cost. This problem is formulated as a nonlinear integer program and is linearized to help obtaining the optimal solution using off-the-shelf solvers. Then, to obtain an efficient solution, it is modeled as a multi-agent Markov decision process and solved by leveraging deep Q learning (DQL) algorithm. The proposed DQL scheme performs a proactive services migration while ensuring their continuity under high mobility constraints. Finally, simulations results show that the proposed DQL scheme achieves close-to-optimal performance. {\textcopyright} 2021 IEEE.},
	keywords = {Deep learning, Edge computing, Infotainment, Integer programming, Learning schemes, Markov processes, Multi agent systems, Multi-access edge computing, Multiaccess, Q-learning, Quality of service, Reinforcement learning, Reinforcement learning approach, Service migration, Vehicle mobility, Vehicular networks},
	doi = {10.1109/LCN52139.2021.9524882},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118466383\&doi=10.1109\%2fLCN52139.2021.9524882\&partnerID=40\&md5=8e35dfee04f347da3f757f57f5d575c8},
	author = {Abouaomar, A. and Mlika, Z. and Filali, A. and Cherkaoui, S. and Kobbane, A.}
}
@article {Ben-Aboud2021107149,
	title = {Electro-Smog Monitoring Using Low-Cost Software-Defined Radio Dongles},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	note = {cited By 1},
	pages = {107149-107158},
	abstract = {With the increasing use of wireless communication technologies, it is important to monitor electromagnetic exposure (ideally with high temporal and spatial resolutions). In this paper, we explore the use of low-cost software-defined radio dongle for electro-smog measurements and more specifically for electro-magnetic fields power measurements and the estimation of the incident power density. We describe how the raw data is collected and then compute the average electromagnetic field power. We then compensate for the non-linearity of the amplifier and the antenna gain to get the corrected electromagnetic field power measurements. We use these measurements to estimate the incident power density which is the metric that we use to evaluate the electro-smog. The results show that the considered low-cost SDR dongle is stable and provides good quality power measurements. The estimation of the incident power density is shown to be accurate enough for monitoring the electro-smog. {\textcopyright} 2013 IEEE.},
	keywords = {Air pollution, Analog circuits, Antenna gains, Antennas, Costs, Electromagnetic exposure, Electromagnetic fields, Incident power, Low costs, Radio, Radio receivers, Software radio, Software-defined radios, Temporal and spatial, Wireless communication technology},
	doi = {10.1109/ACCESS.2021.3100773},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112673496\&doi=10.1109\%2fACCESS.2021.3100773\&partnerID=40\&md5=b7b53e18cf471222f475a67fe957cbee},
	author = {Ben-Aboud, Y. and Ghogho, M. and Pollin, S. and Kobbane, A.}
}
@conference {Abouaomar2021,
	title = {Mean-Field Game and Reinforcement Learning MEC Resource Provisioning for SFC},
	booktitle = {2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings},
	year = {2021},
	note = {cited By 0},
	abstract = {In this paper, we address the resource provisioning problem for service function chaining (SFC) in terms of the placement and chaining of virtual network functions (VNFs) within a multi-access edge computing (MEC) infrastructure to reduce service delay. We consider the VNFs as the main entities of the system and propose a mean-field game (MFG) framework to model their behavior for their placement and chaining. Then, to achieve the optimal resource provisioning policy without considering the system control parameters, we reduce the proposed MFG to a Markov decision process (MDP). In this way, we leverage reinforcement learning with an actor-critic approach for MEC nodes to learn complex placement and chaining policies. Simulation results show that our proposed approach outperforms benchmark state-of-the-art approaches. {\textcopyright} 2021 IEEE.},
	keywords = {Computer games, Computing infrastructures, Computing resource, e-learning, Edge computing, Markov processes, Mean-field games, Multi-access edge computing, Multiaccess, Network function virtualization, Reinforcement learning, Reinforcement learnings, Resource provisioning, Service function chaining, Service functions, Transfer functions, Virtual addresses, Virtual reality},
	doi = {10.1109/GLOBECOM46510.2021.9685236},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124062107\&doi=10.1109\%2fGLOBECOM46510.2021.9685236\&partnerID=40\&md5=8319d7756843c2ccadb8f9de4bec7eff},
	author = {Abouaomar, A. and Cherkaoui, S. and Mlika, Z. and Kobbane, A.}
}
@conference {Ahajjam2021,
	title = {On Multi-Label Classification for Non-Intrusive Load Identification using Low Sampling Frequency Datasets},
	booktitle = {Conference Record - IEEE Instrumentation and Measurement Technology Conference},
	volume = {2021-May},
	year = {2021},
	note = {cited By 0},
	abstract = {Non-intrusive load monitoring (NILM) aims to infer information about the electric consumption of individual loads using the premises{\textquoteright} aggregate consumption. In this work, we target supervised multi-label classification for non-intrusive load identification. We describe how we have created a new dataset from Moroccan households using a low sampling frequency. Then, we analyze the performance of three machine learning models for NILM, and investigate the impact of signal input length on performance. {\textcopyright} 2021 IEEE.},
	keywords = {Aggregate consumption, Classification (of information), Electric consumption, Load identification, Machine learning models, Measurement, Multi label classification, Non-intrusive, Nonintrusive load monitoring, Sampling frequencies},
	doi = {10.1109/I2MTC50364.2021.9460059},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113709883\&doi=10.1109\%2fI2MTC50364.2021.9460059\&partnerID=40\&md5=2f6ca1a0b8790dce2a085d0e0ff10cf4},
	author = {Ahajjam, M.A. and Essayeh, C. and Ghogho, M. and Kobbane, A.}
}
@conference {Gryech2021,
	title = {On spatial prediction of urban air pollution},
	booktitle = {2021 17th International Conference on Intelligent Environments, IE 2021 - Proceedings},
	year = {2021},
	note = {cited By 0},
	abstract = {Air pollution continues to draw global attention, and still causes adverse environmental issues and health effects. Questions about how air pollution evolves spatially are also still unsolved. Many air quality monitoring stations are deployed in several countries to give insight about air quality. However, it is quite frequent for these stations to go out of order during their long life time. These incidents may lead to a significant loss of pollution data. To mitigate this issue, we propose to leverage spatial correlation between pollution monitoring stations to predict the lost data. To reduce the complexity of the prediction model, for each monitoring station, we identify the best set of other stations to use in the prediction model. Correlation-based station selection is shown to outperform distance-based station selection and provides an R2 above 0.8 when applied to the Airparif datasets. {\textcopyright} 2021 IEEE.},
	keywords = {Air quality, Air quality monitoring stations, Environmental issues, Forecasting, Intelligent agents, Monitoring stations, Pollution monitoring, Prediction model, Predictive analytics, Spatial correlations, Spatial prediction, Urban air pollution},
	doi = {10.1109/IE51775.2021.9486618},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114499832\&doi=10.1109\%2fIE51775.2021.9486618\&partnerID=40\&md5=10a04db251b0bca163abb4d34f0c721a},
	author = {Gryech, I. and Ben-Aboud, Y. and Ghogho, M. and Kobbane, A.}
}
@conference {Naja2020,
	title = {Alert Message Dissemination using Graph-based Markov Decision Process Model in VANETs},
	booktitle = {IEEE International Conference on Communications},
	volume = {2020-June},
	year = {2020},
	note = {cited By 0},
	abstract = {Vehicular Ad-hoc Networks (VANETs) have many promising applications such as improving vehicle driver{\textquoteright}s safety, and so, decreasing car deaths. In VANETs, the main communication way is broadcast. Such Broadcast needs to be done efficiently especially in congested areas to avoid the broadcast storm problem. A crashed vehicle disseminates a message about its incident to all nodes in the network. The vehicle nodes of the network have to disseminate in their turn the alert message carefully to maximize both reachability and saved rebroadcast (by reducing congestion) while minimizing the delay. This concern is demonstrated and modeled by decision hypothesis. In this paper, at first, we are keen on the Markov decision process (MDP), which is utilized to model and tackle such successive decision issues. We aim to optimize a utility for each vehicle relying upon an irregular domain and choices made by it. As the MDP formalism achieves its cutoff points when it is important to consider the cooperation between the several vehicles. We will begin utilizing the Graph-based MDP where the state and activity spaces are factorizable by factors. We then demonstrate that the transition functions and rewards are deteriorated into nearby functions, and the reliance relations between the vehicles are spoken to by a graph. To Figure the optimal strategy, we use Mean Field Approximation (MFA) for tackling GMDP issue. {\textcopyright} 2020 IEEE.},
	keywords = {Accidents, Broadcast storm problem, Graphic methods, Markov decision process models, Markov Decision Processes, Markov processes, Mean field approximation, Message dissemination, Mobile telecommunication systems, Optimal strategies, Traffic congestion, Transition functions, Vehicles, Vehicular ad hoc networks, Vehicular Adhoc Networks (VANETs)},
	doi = {10.1109/ICC40277.2020.9148997},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089436123\&doi=10.1109\%2fICC40277.2020.9148997\&partnerID=40\&md5=12d16adc7ab7a4b60d7ff52c15709c2c},
	author = {Naja, A. and Oualhaj, O.A. and Boulmalf, M. and Essaaidi, M. and Kobbane, A.}
}
@conference {Boudagdigue2020,
	title = {Cluster-based certificate revocation in industrial IOT networks using Signaling game},
	booktitle = {2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings},
	year = {2020},
	note = {cited By 1},
	abstract = {Industrial IoT network (IIoT) is the result of integrating Internet of Things into the industrial processes to make manufacturers more efficient and reactive. This integration brings with it new security and privacy challenges because of the sensitive information exchanged between devices and the infrastructure. In order to prevent malicious nodes from abusing the IIoT system, this paper investigates a new distributed certificate revocation protocol. Hence, we propose cluster-based certificate revocation mechanism for IIoT network by using game theory. Indeed, our proposed signaling game allows to make a decision on a targeted node after evaluating its behaving. In this approach, we assume an IIoT network organized as a set of clusters called communities. Each community consists of a set of member nodes and a community leader who uses a multi-stage game to renew the certificate of well behaving member nodes and revoke the certificate of malicious member nodes. Based on the Perfect Bayesian Equilibrium, we describe a reactive algorithm implementing the certificates update mechanism. By simulations, we evaluate the convergence speed, the dynamic and the accuracy of the leader{\textquoteright}s posterior belief on nodes with different behaviors. {\textcopyright} 2020 IEEE.},
	keywords = {Certificate revocation, Game theory, Industrial internet of things (IIoT), Industrial processs, Multi stage games, Perfect bayesian equilibriums, Privacy by design, Reactive algorithms, Security and privacy, Sensitive informations, Update mechanisms},
	doi = {10.1109/GLOBECOM42002.2020.9322497},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100398930\&doi=10.1109\%2fGLOBECOM42002.2020.9322497\&partnerID=40\&md5=8d905a0b2029ae303a74268527163a44},
	author = {Boudagdigue, C. and Benslimane, A. and Kobbane, A.}
}
@article {Lhazmir2020,
	title = {A decision-making analysis in UAV-enabled wireless power transfer for IoT networks},
	journal = {Simulation Modelling Practice and Theory},
	volume = {103},
	year = {2020},
	note = {cited By 8},
	abstract = {We consider an IoT network with energy-harvesting capabilities. To extend the network lifetime, we propose a novel unmanned aerial vehicle (UAV)- enabled wireless power transfer (WPT) system, where UAVs move among IoT devices and act as data aggregators and wireless power providers. This paper addresses the decision-making problem since the limited buffer and energy resources constrain all nodes. Each IoT node must decide on whether to request a data transmission, to ask for a wireless energy transfer or to abstain and not take any action. When a UAV receives a request from an IoT device, either for data reception or wireless energy transmission, it has to accept or decline. In this paper, we aim to find a proper packet delivery and energy transfer policy according to the system state that maximizes the data transmission efficiency of the system. We first formulate the problem as a Markov Decision Process (MDP) to tackle the successive decision issues, to optimize a utility for each node upon a casual environment. As the MDP formalism achieves its limits when the interactions between different nodes are considered, we formulate the problem as a Graph-based MDP (GMDP). The transition functions and rewards are then decomposed into local functions, and a graph illustrates the dependency{\textquoteright} relations among the nodes. To obtain the optimal policy despite the system{\textquoteright}s variations, Mean-Field Approximation (MFA) and Approximate linear-programming (ALP) algorithms were proposed to solve the GMDP problem. {\textcopyright} 2020 Elsevier B.V.},
	keywords = {Antennas, Approximate linear programming, Approximation algorithms, Behavioral research, Data communication systems, Data transfer, Data transmission efficiency, Decision making, Decision making analysis, Decision-making problem, Energy harvesting, Energy resources, Energy transfer, Graph theory, Graphic methods, Inductive power transmission, Internet of things, Linear programming, Markov Decision Processes, Markov processes, Mean field approximation, Unmanned aerial vehicles (UAV), Wireless energy transfers, Wireless power transfer (WPT)},
	doi = {10.1016/j.simpat.2020.102102},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084066274\&doi=10.1016\%2fj.simpat.2020.102102\&partnerID=40\&md5=6a1c9e107244a170a782e61d0f9755cc},
	author = {Lhazmir, S. and Oualhaj, O.A. and Kobbane, A. and Mokdad, L.}
}
@conference {Ahajjam20201701,
	title = {Electric Power Quality Disturbances Classification based on Temporal-Spectral Images and Deep Convolutional Neural Networks},
	booktitle = {2020 International Wireless Communications and Mobile Computing, IWCMC 2020},
	year = {2020},
	note = {cited By 7},
	pages = {1701-1706},
	abstract = {We propose a deep learning based technique for power quality disturbances (PQD) detection and identification that aims at mimicking the reasoning of human field experts. This technique consists of processing small-size images containing superimposed time and frequency representations of the electric signal. The classification of PQD is performed with a convolutional neural network (CNN) trained with synthetic signals containing various single and multiple PQDs. Simulation results show that our technique is able to detect and identify with a high accuracy, in addition to pure sinusoidal, eight single PQDs and 20 of their combinations (up to four PQDs in the same signal) even in the presence of noise. Features such as lower computational load and simplicity while maintaining high performance sets the proposed technique apart from previous ones. {\textcopyright} 2020 IEEE.},
	keywords = {Computational loads, Convolution, Convolutional neural networks, Deep learning, Deep neural networks, Detection and identifications, Electric power quality disturbances, Electric signal, Image classification, Mobile computing, Power quality, Power quality disturbances, Spectral images, Spectroscopy, Synthetic signals, Time and frequencies},
	doi = {10.1109/IWCMC48107.2020.9148438},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089652241\&doi=10.1109\%2fIWCMC48107.2020.9148438\&partnerID=40\&md5=a479607523102d68ad4d7d0188079ac8},
	author = {Ahajjam, M.A. and Licea, D.B. and Ghogho, M. and Kobbane, A.}
}
@conference {Hafaiedh2020,
	title = {Fuzzified Double Game for Qos-Aware LTE-U and Wifi Coexistence in 5Ghz Band},
	booktitle = {2020 Global Information Infrastructure and Networking Symposium, GIIS 2020},
	year = {2020},
	note = {cited By 0},
	abstract = {In the current decade, cellular networks are facing the challenge of meeting aggressive data demand with limited licensed spectrum and LTE over the unlicensed band (LTE-U) has come as an effective way to defeat this problem. Using LTE-U along with superior techniques such as carrier aggregation (CA), it became possible to boost the performance of existing cellular networks. However, LTE-Ucan potentially deteriorate the performance of coexisting WiFi systems operating over the unlicensed bands if not well managed. Mainly because of the LTE-U{\textquoteright}s selfish nature of using the resources without sharing. In this paper, an effective coexistence mechanism between LTE-U and WiFi systems is being investigated. The point is to facilitate the cellular networks to use LTE-U with CA to satisfy the quality-of-service (QoS) of the users while protecting WiFi users, considering multiple operators in a dense deployment scenario. To resolve this problem, a double cooperative game will be used. That game will be implemented, in addition to the fuzzy logic, which will help us in resource allocation for users QoS. {\textcopyright} 2020 IEEE.},
	keywords = {Carrier aggregations, Cellular network, Cellular radio systems, Cooperative game, Deployment scenarios, Fuzzy logic, Mobile telecommunication systems, Multiple operator, QoS-aware, Quality of service, Superior technique, Wi-Fi, WiFi systems, Wireless local area networks (WLAN)},
	doi = {10.1109/GIIS50753.2020.9248487},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097601439\&doi=10.1109\%2fGIIS50753.2020.9248487\&partnerID=40\&md5=ca56971766f975bae3c7b9a084c6b679},
	author = {Hafaiedh, H. and El Korbi, I. and Langar, R. and Saidane, L.A. and Kobbane, A.}
}
@article {Ahajjam2020,
	title = {IMPEC: An integrated system for monitoring and processing electricity consumption in buildings},
	journal = {Sensors (Switzerland)},
	volume = {20},
	number = {4},
	year = {2020},
	note = {cited By 4},
	abstract = {Non-intrusive Load Monitoring (NILM) systems aim at identifying and monitoring the power consumption of individual appliances using the aggregate electricity consumption. Many issues hinder their development. For example, due to the complexity of data acquisition and labeling, datasets are scarce; labeled datasets are essential for developing disaggregation and load prediction algorithms. In this paper, we introduce a new NILM system, called Integrated Monitoring and Processing Electricity Consumption (IMPEC). The main characteristics of the proposed system are flexibility, compactness, modularity, and advanced on-board processing capabilities. Both hardware and software parts of the system are described, along with several validation tests performed at residential and industrial settings. {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
	keywords = {Article, Data acquisition, Disaggregation, Electric load management, Electric power utilization, electricity, Electricity-consumption, Energy monitoring, Hardware and software, Industrial settings, Integrated monitoring, Labeled data, Monitoring, Nonintrusive load monitoring, On-board processing, software, Software testing},
	doi = {10.3390/s20041048},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079573681\&doi=10.3390\%2fs20041048\&partnerID=40\&md5=a145afa634dd9bf882c3c570823158c9},
	author = {Ahajjam, M.A. and Licea, D.B. and Ghogho, M. and Kobbane, A.}
}
@article {Assila2020,
	title = {Improving caching resource management: A pricing economic approach using Cournot, Bertrand, and Stackelberg game models},
	journal = {International Journal of Communication Systems},
	year = {2020},
	note = {cited By 3},
	abstract = {Over-The-Top broadcasts a huge number of medias that mobile network operators have to manage efficiently before to deliver it to their subscribers. We propose an economic pricing approach to address caching resource management issues in the 5G wireless networks and to overcome limitations in terms of throughput, latency, and reliability. Moreover, we consider this approach based on an oligopolistic multi-market deducted from Cournot, Stackelberg, and Bertrand models. For simulation purpose, we consider the routing protocol (Ad-hoc On-Demand Distance Vector [AODV]) commonly used for the wireless network. We use the NS-2 package, and we analyze results in terms of End-to-End delay representing latency, throughput, packet delivery ratio, and normalized network load. {\textcopyright} 2020 John Wiley \& Sons, Ltd.},
	keywords = {5G mobile communication systems, Ad hoc on demand distance vector, caching, Costs, Cournot, Economics, Mobile network operators, Mobile telecommunication systems, Natural resources management, Packet delivery ratio, Resource allocation, Resource Management, Stackelberg, Stackelberg Games, wireless networks},
	doi = {10.1002/dac.4358},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079387484\&doi=10.1002\%2fdac.4358\&partnerID=40\&md5=70ae8f696b34a21860572f8c3437dd46},
	author = {Assila, B. and Kobbane, A. and Ben-Othman, J.}
}
@article {Gryech2020379,
	title = {Machine learning for air quality prediction using meteorological and traffic related features},
	journal = {Journal of Ambient Intelligence and Smart Environments},
	volume = {12},
	number = {5},
	year = {2020},
	note = {cited By 4},
	pages = {379-391},
	abstract = {The presence of pollutants in the air has a direct impact on our health and causes detrimental changes to our environment. Air quality monitoring is therefore of paramount importance. The high cost of the acquisition and maintenance of accurate air quality stations implies that only a small number of these stations can be deployed in a country. To improve the spatial resolution of the air monitoring process, an interesting idea is to develop data-driven models to predict air quality based on readily available data. In this paper, we investigate the correlations between air pollutants concentrations and meteorological and road traffic data. Using machine learning, regression models are developed to predict pollutants concentration. Both linear and non-linear models are investigated in this paper. It is shown that non-linear models, namely Random Forest (RF) and Support Vector Regression (SVR), better describe the impact of traffic flows and meteorology on the concentrations of pollutants in the atmosphere. It is also shown that more accurate prediction models can be obtained when including some pollutants{\textquoteright} concentration as predictors. This may be used to infer the concentrations of some pollutants using those of other pollutants, thereby reducing the number of air pollution sensors. {\textcopyright} 2020 - IOS Press and the authors. All rights reserved.},
	keywords = {Accurate prediction, Air quality, Air quality monitoring, Air quality prediction, Data-driven model, Decision trees, Forecasting, Machine learning, Non-linear model, Nonlinear systems, Pollution sensors, Predictive analytics, Spatial resolution, Support vector regression, Support vector regression (SVR)},
	doi = {10.3233/AIS-200572},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093821240\&doi=10.3233\%2fAIS-200572\&partnerID=40\&md5=f8b7d726f054f01a2be432560d359fc5},
	author = {Gryech, I. and Ghogho, M. and Elhammouti, H. and Sbihi, N. and Kobbane, A.}
}
@article {Lhazmir2020973,
	title = {Matching Game with No-Regret Learning for IoT Energy-Efficient Associations with UAV},
	journal = {IEEE Transactions on Green Communications and Networking},
	volume = {4},
	number = {4},
	year = {2020},
	note = {cited By 4},
	pages = {973-981},
	abstract = {Unmanned aerial vehicles (UAVs) are a promising technology to provide an energy-efficient and cost-effective solution for data collection from ground Internet of Things (IoT) network. In this paper, we analyze the UAV-IoT device associations that provide reliable connections with low communication power and load balance the traffic using analytical techniques from game theory. In particular, to maximize the IoT devices{\textquoteright} benefits, a novel framework is proposed to assign them the most suitable UAVs. We formulate the problem as a distributed algorithm that combines notions from matching theory and no-regret learning. First, we develop a many-to-one matching game where UAVs and IoT devices are the players. In this subgame, the players rank one another based on individual utility functions that capture their needs. Each IoT device aims to minimize its transmitting energy while meeting its signal-to-interference-plus-noise-ratio (SINR) requirements, and each UAV seeks to maximize the number of served IoT devices while respecting its energy constraints. Second, a non-cooperative game based on no-regret learning is used to determine each IoT device{\textquoteright}s regret. Then, UAVs open a window for transfers to the IoT devices. Simulation results show that the proposed approach provides a low average total transmit power, ensures fast data transmission and optimal utilization of the UAVs{\textquoteright} bandwidth. {\textcopyright} 2017 IEEE.},
	keywords = {Antennas, Cost effectiveness, Cost-effective solutions, energy efficiency, Fast data transmission, Game theory, Internet of things, Internet of Things (IOT), Noncooperative game, Optimal utilization, Reliable connections, Signal interference, Signal to interference plus noise ratio, Signal to noise ratio, Total transmit power, Unmanned aerial vehicles (UAV)},
	doi = {10.1109/TGCN.2020.3008992},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096697293\&doi=10.1109\%2fTGCN.2020.3008992\&partnerID=40\&md5=7f2e844f54122845029dfd8503c5eaf6},
	author = {Lhazmir, S. and Oualhaj, O.A. and Kobbane, A. and Ben-Othman, J.}
}
@article {Gryech2020,
	title = {Moreair: A low-cost urban air pollution monitoring system},
	journal = {Sensors (Switzerland)},
	volume = {20},
	number = {4},
	year = {2020},
	note = {cited By 25},
	abstract = {MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children{\textquoteright}s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution. {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
	keywords = {Agile deployments, Agile manufacturing systems, Air quality, Costs, Decision trees, Geographic information systems, Information systems, Information use, Learning systems, Machine learning, Mobile sensing, Monitoring, Particles (particulate matter), Particulate Matter, Pollution detection, Pollution monitoring, Random forests, Real-time information, Sensor deployment, Urban air pollution, Urban pollutions},
	doi = {10.3390/s20040998},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079609813\&doi=10.3390\%2fs20040998\&partnerID=40\&md5=dc90b4357fcdc64d82d12f57a45f971f},
	author = {Gryech, I. and Ben-Aboud, Y. and Guermah, B. and Sbihi, N. and Ghogho, M. and Kobbane, A.}
}
@article {Ahajjam2020,
	title = {Mored: A moroccan buildings{\textquoteright} electricity consumption dataset},
	journal = {Energies},
	volume = {13},
	number = {24},
	year = {2020},
	note = {cited By 6},
	abstract = {This paper consists of two parts: An overview of existing open datasets of electricity consumption and a description of the Moroccan Buildings{\textquoteright} Electricity Consumption Dataset, a first of its kind, coined as MORED. The new dataset comprises electricity consumption data of various Moroccan premises. Unlike existing datasets, MORED provides three main data components: Whole premises (WP) electricity consumption, individual load (IL) ground-truth consumption, and fully labeled IL signatures, from affluent and disadvantaged neighborhoods. The WP consumption data were acquired at low rates (1/5 or 1/10 samples/s) from 12 households; the IL ground-truth data were acquired at similar rates from five households for extended durations; and IL signature data were acquired at high and low rates (50 k and 4 samples/s) from 37 different residential and industrial loads. In addition, the dataset encompasses non-intrusive load monitoring (NILM) metadata. {\textcopyright} 2020 by the authors.},
	keywords = {Data components, Electric load management, Electric power utilization, Electricity-consumption, Ground truth, Ground truth data, Industrial loads, Low rates, Nonintrusive load monitoring, Signature data},
	doi = {10.3390/en13246737},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106664615\&doi=10.3390\%2fen13246737\&partnerID=40\&md5=2d7b881b6d24a1d21b672b26fa9ee62f},
	author = {Ahajjam, M.A. and Licea, D.B. and Essayeh, C. and Ghogho, M. and Kobbane, A.}
}
@article {Filali2020197017,
	title = {Multi-access edge computing: A survey},
	journal = {IEEE Access},
	volume = {8},
	year = {2020},
	note = {cited By 49},
	pages = {197017-197046},
	abstract = {Multi-access Edge Computing (MEC) is a key solution that enables operators to open their networks to new services and IT ecosystems to leverage edge-cloud benefits in their networks and systems. Located in close proximity from the end users and connected devices, MEC provides extremely low latency and high bandwidth while always enabling applications to leverage cloud capabilities as necessary. In this article, we illustrate the integration of MEC into a current mobile networks{\textquoteright} architecture as well as the transition mechanisms to migrate into a standard 5G network architecture.We also discuss SDN, NFV, SFC and network slicing as MEC enablers. Then, we provide a state-of-the-art study on the different approaches that optimize the MEC resources and its QoS parameters. In this regard, we classify these approaches based on the optimized resources and QoS parameters (i.e., processing, storage, memory, bandwidth, energy and latency). Finally, we propose an architectural framework for a MEC-NFV environment based on the standard SDN architecture. {\textcopyright} 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.},
	keywords = {5G mobile communication systems, Architectural frameworks, Bandwidth, Close proximity, Edge computing, Network function virtualization, Network slicing, Networks and systems, Optimized resources, QoS parameters, State of the art, Transition mechanism},
	doi = {10.1109/ACCESS.2020.3034136},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099901543\&doi=10.1109\%2fACCESS.2020.3034136\&partnerID=40\&md5=bc99db081ebbbf5eb6d188c020bb33a2},
	author = {Filali, A. and Abouaomar, A. and Cherkaoui, S. and Kobbane, A. and Guizani, M.}
}
@conference {Amine2020,
	title = {New Network Slicing Scheme for UE Association Solution in 5G Ultra Dense HetNets},
	booktitle = {IEEE International Conference on Communications},
	volume = {2020-June},
	year = {2020},
	note = {cited By 5},
	abstract = {Network slicing (NS) will have an essential role to enhance the isolation and the flexibility of the future generation of cellular networks (5G) with heterogeneous capabilities, notably in ultra-dense (UD) urban zones. Thus, it may be the principal component necessary to respond to 5G UD heterogeneous networks (UD-HetNets) technical requirements. The aim of this paper is to propose a new NS architecture to resolve user equipment (UE)-association problem in 5G UD-HetNets. Accordingly, we formulated the problem as a one-to-many matching game based on matching theory, while exploiting the isolation character of slicing to eliminate interferences between pico-cells and those among macro-cell and pico-cells. Next, we proposed the UE-slice association algorithm (U-S.AA) to find the stable matching among user equipments (UEs) and different network slices. Numerical simulation results validate our theoretical model, and prove the efficient of the proposed user-slice association solution to enhance the global network performance, respecting the UEs quality of service (QoS), as well as improving the energy efficiency (EE) of UEs. {\textcopyright} 2020 IEEE.},
	keywords = {5G mobile communication systems, Association algorithms, Cellular network, energy efficiency, Future generations, Heterogeneous networks, Matching theory, Network performance, Principal Components, Stable matching, Technical requirement, Theoretical modeling},
	doi = {10.1109/ICC40277.2020.9148844},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089429385\&doi=10.1109\%2fICC40277.2020.9148844\&partnerID=40\&md5=1c1af15932312ae46b6294cfb76fd07d},
	author = {Amine, M. and Kobbane, A. and Ben-Othman, J.}
}
@article {Filali202015947,
	title = {Preemptive SDN Load Balancing with Machine Learning for Delay Sensitive Applications},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	number = {12},
	year = {2020},
	note = {cited By 12},
	pages = {15947-15963},
	abstract = {SDN is a key-enabler to achieve scalability in 5G and Multi-access Edge Computing networks. To balance the load between distributed SDN controllers, the migration of the data plane components has been proposed. Different from most previous works which use reactive mechanisms, we propose to preemptively balance the load in the SDN control plane to support network flows that require low latency communications. First, we forecast the load of SDN controllers to prevent load imbalances and schedule data plane migrations in advance. Second, we optimize the migration operations to achieve better load balancing under delay constraints. Specifically, in the first step, we construct two prediction models based on Auto Regressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) approaches to forecast SDN controllers load. Then, we conduct a comparative study between these two models and calculate their accuracies and forecast errors. The results show that, in long-term predictions, the accuracy of LSTM model outperforms that of ARIMA by 55\% in terms of prediction errors. In the second step, to select which data plane components to migrate and where the migration should happen under delay constraints, we formulate the problem as a non-linear binary program, prove its NP-completeness and propose a reinforcement learning algorithm to solve it. The simulations show that the proposed algorithm performs close to optimal and outperforms recent benchmark algorithms from the literature. {\textcopyright} 1967-2012 IEEE.},
	keywords = {5G mobile communication systems, Auto-regressive integrated moving average, Autoregressive moving average model, Balancing, Comparative studies, Controllers, Delay constraints, Delay-sensitive applications, Forecasting, Learning algorithms, Long short-term memory, Long-term prediction, Low-latency communication, Prediction errors, Predictive analytics, Reactive mechanism, Reinforcement learning},
	doi = {10.1109/TVT.2020.3038918},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097173809\&doi=10.1109\%2fTVT.2020.3038918\&partnerID=40\&md5=4dc77968a74ba95fb61deec16c598fbb},
	author = {Filali, A. and Mlika, Z. and Cherkaoui, S. and Kobbane, A.}
}
@conference {Ben-Aboud20201324,
	title = {A research-oriented low-cost air pollution monitoring IoT platform},
	booktitle = {2020 International Wireless Communications and Mobile Computing, IWCMC 2020},
	year = {2020},
	note = {cited By 1},
	pages = {1324-1329},
	abstract = {This paper presents an IoT platform designed for air pollution monitoring. It aiming to facilitate the testing of different data collection strategies, to simplify the air quality monitoring process, to provide the citizens with real-time information about air pollution, to allow citizens to participate in the air quality monitoring process, and to help the authorities identify zones of high air pollution and take the most appropriate measures to improve air quality. The sensor nodes have been developed using low-cost off-the-shelf hardware. Both nomadic and mobile sensor nodes have been developed. A novel sensor management middleware has been designed and developed to have the flexibility to remotely control the operational settings of the sensor nodes and to reduce the volume of transmitted data. Finally, two applications have been developed and implemented for data visualization. The first is a mobile friendly air pollution meter. The second offers a spatial visualization of air pollution levels using a Geographic Information System (GIS). The developed platform has been tested in multiple measurement campaigns. The results of one of these campaigns (conducted in Hay Nahda II, Rabat, Morocco) is presented in this paper to showcase the platform. {\textcopyright} 2020 IEEE.},
	keywords = {Air pollution monitoring, Air quality, Air quality monitoring, Costs, Data collection strategies, Data visualization, Information use, Internet of things, Middleware, Mobile computing, Mobile sensor node, Multiple measurements, Off-the-shelf hardwares, Pollution detection, Real-time information, Sensor nodes, Spatial visualization, Visualization},
	doi = {10.1109/IWCMC48107.2020.9148176},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089690465\&doi=10.1109\%2fIWCMC48107.2020.9148176\&partnerID=40\&md5=6b9c355d625a664f7d5ac062470cf5f0},
	author = {Ben-Aboud, Y. and Ghogho, M. and Kobbane, A.}
}
@article {Boudagdigue20203667,
	title = {Trust Management in Industrial Internet of Things},
	journal = {IEEE Transactions on Information Forensics and Security},
	volume = {15},
	year = {2020},
	note = {cited By 17},
	pages = {3667-3682},
	abstract = {Automobile manufacturers around the world are increasingly deploying Industrial Internet of Things (IIoT) devices in their factories to accompany the Industrial Revolution 4.0. Security and privacy are the main limitations to the integration of Internet of Things (IoT) into industrial processes. Therefore, it is necessary to protect industrial data contained in IIoT devices and keep them confidential. As a step towards this direction, in this paper, we propose a dynamic trust management model suitable for industrial environments. We propose also to change the traditional centralized architecture of IIoT networks in automotive plants into a hybrid architecture based on a set of new industrial relationship rules. The performance evaluation in this work is done in two parts. In the first part, we compare our proposed architecture with the traditional architecture of the plant{\textquoteright}s IIoT network. The results of this comparison show that our architecture is more suitable to simplify trust management of IIoT devices. In the second part, we demonstrated the ability, the adaptiveness and the resiliency of our proposed trust model against behavioral changes of IIoT nodes in malicious environments. {\textcopyright} 2005-2012 IEEE.},
	keywords = {Automobile manufacture, Automobile manufacturers, Automotive industry, Centralized architecture, Dynamic trust managements, Industrial environments, Industrial internet of things (IIoT), Industrial relationship, Internet of Things (IOT), Network architecture, Proposed architectures, Traditional architecture, Trusted computing},
	doi = {10.1109/TIFS.2020.2997179},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089186851\&doi=10.1109\%2fTIFS.2020.2997179\&partnerID=40\&md5=105acbd7042007978b04935eb0240170},
	author = {Boudagdigue, C. and Benslimane, A. and Kobbane, A. and Liu, J.}
}
@article {Amine2020,
	title = {Two-sided matching framework for optimal user association in 5G multi-RAT UDNs},
	journal = {International Journal of Communication Systems},
	volume = {33},
	number = {8},
	year = {2020},
	note = {cited By 2},
	abstract = {Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra-dense networks (5G multi-RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi-RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many-to-one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs. {\textcopyright} 2020 John Wiley \& Sons, Ltd.},
	keywords = {5G mobile communication systems, 5G multi-RAT UDNs, Association algorithms, decoupled uplink/downlink access (DUDA), energy efficiency, Game theory, Industrial research, Matching game, Matching theory, Network performance, Nonlinear programming, Optimization, Quality of service, Rats, Stable matching},
	doi = {10.1002/dac.4346},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078931379\&doi=10.1002\%2fdac.4346\&partnerID=40\&md5=159a3a40021d6b340c2873e4db73e2ac},
	author = {Amine, M. and Kobbane, A. and Ben-Othman, J. and Walid, A.}
}
@conference {Lhazmir2020,
	title = {UAV for Wireless Power Transfer in IoT Networks: A GMDP approach},
	booktitle = {IEEE International Conference on Communications},
	volume = {2020-June},
	year = {2020},
	note = {cited By 3},
	abstract = {Unmanned aerial vehicles (UAVs) are a promising technology employed as moving aggregators and wireless power transmitters for IoT networks. In this paper, we consider an UAV-IoT wireless energy and data transmission system and the decision-making problem is investigated. We aim at optimizing the nodes{\textquoteright} utilities by defining a good packet delivery and energy transfer policy according to the system state. We formulate the problem as a Markov Decision Process (MDP) to tackle the successive decision issues. As the MDP formalism achieves its limits when the neighbors{\textquoteright} interactions are considered, we formulate the problem as a Graph-based MDP (GMDP). We then propose a Mean-Field Approximation (MFA) algorithm to find a solution. The simulation results show that our framework achieves a good analysis of the system behavior. {\textcopyright} 2020 IEEE.},
	keywords = {Antennas, Approximation algorithms, Behavioral research, Decision making, Decision-making problem, Energy transfer, Graphic methods, Inductive power transmission, Internet of things, Markov Decision Processes, Markov processes, Mean field approximation, Packet Delivery, System behaviors, System state, Unmanned aerial vehicles (UAV), Wireless energy, Wireless power},
	doi = {10.1109/ICC40277.2020.9148956},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089418365\&doi=10.1109\%2fICC40277.2020.9148956\&partnerID=40\&md5=a3d1ed58b9a7436f2191be8372102f51},
	author = {Lhazmir, S. and Oualhaj, O.A. and Kobbane, A. and Amlioud, E.M. and Ben-Othman, J.}
}
@conference {Assila2019,
	title = {Caching as a Service in 5G Networks: Intelligent Transport and Video on Demand Scenarios},
	booktitle = {2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings},
	year = {2019},
	note = {cited By 0},
	doi = {10.1109/GLOCOM.2018.8648110},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063521486\&doi=10.1109\%2fGLOCOM.2018.8648110\&partnerID=40\&md5=b7935edacd24dfb7acbd2e5dbe0daed6},
	author = {Assila, B. and Kobbane, A. and El Koutbi, M. and Ben-Othman, J. and Mokdad, L.}
}
@conference {Abouaomar2019,
	title = {Matching-Game for User-Fog Assignment},
	booktitle = {2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings},
	year = {2019},
	note = {cited By 0},
	doi = {10.1109/GLOCOM.2018.8647545},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063543941\&doi=10.1109\%2fGLOCOM.2018.8647545\&partnerID=40\&md5=2e86072aa15d3175de06d25bff61c79f},
	author = {Abouaomar, A. and Kobbane, A. and Cherkaoui, S.}
}
@conference {Assila2018213,
	title = {Achieving low-energy consumption in fog computing environment: A matching game approach},
	booktitle = {19th IEEE Mediterranean Eletrotechnical Conference, MELECON 2018 - Proceedings},
	year = {2018},
	pages = {213-218},
	doi = {10.1109/MELCON.2018.8379096},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050157229\&doi=10.1109\%2fMELCON.2018.8379096\&partnerID=40\&md5=0250d5d03e5322d270460ae3af21ca94},
	author = {Assila, B. and Kobbane, A. and Walid, A. and El Koutbi, M.}
}
@conference {Assila20181193,
	title = {Caching as a Service for 5G Networks: A Matching Game Approach for CaaS Resource Allocation},
	booktitle = {Proceedings - IEEE Symposium on Computers and Communications},
	volume = {2018-June},
	year = {2018},
	pages = {1193-1198},
	doi = {10.1109/ISCC.2018.8538661},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059217607\&doi=10.1109\%2fISCC.2018.8538661\&partnerID=40\&md5=d33d4f8d2f2cd79a86990bb8aeeaed3a},
	author = {Assila, B. and Kobbane, A. and Ben-Othman, J. and Koutbi, M.E.}
}
@article {Mourchid2018,
	title = {CGAM: A community and geography aware mobility model},
	journal = {International Journal of Communication Systems},
	volume = {31},
	number = {1},
	year = {2018},
	doi = {10.1002/dac.3432},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030319469\&doi=10.1002\%2fdac.3432\&partnerID=40\&md5=9e90e1af7674bce27f60e78c6d502044},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@article {Mourchid2018,
	title = {CGAM: A community and geography aware mobility model},
	journal = {International Journal of Communication Systems},
	volume = {31},
	number = {1},
	year = {2018},
	note = {cited By 0},
	abstract = {The advances of localization-enabled technologies have led to huge volumes of large-scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context-aware advertising, city-wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio-temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members{\textquoteright} distribution, and radius of gyration. We validate the CGAM synthetic traces against real-world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding-based and community-based routing protocols. Copyright {\textcopyright} 2017 John Wiley \& Sons, Ltd.},
	doi = {10.1002/dac.3432},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030319469\&doi=10.1002\%2fdac.3432\&partnerID=40\&md5=9e90e1af7674bce27f60e78c6d502044},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@conference {Lhazmir2018322,
	title = {Channel Assignment for D2D communication : A Regret Matching Based Approach},
	booktitle = {2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018},
	year = {2018},
	pages = {322-327},
	doi = {10.1109/IWCMC.2018.8450520},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053868247\&doi=10.1109\%2fIWCMC.2018.8450520\&partnerID=40\&md5=627b0b881ea4d1310141874723652d7b},
	author = {Lhazmir, S. and Kobbane, A. and Ben-Othman, J.}
}
@conference {Assila20181345,
	title = {A Cournot Economic Pricing Model for Caching Resource Management in 5G Wireless Networks},
	booktitle = {2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018},
	year = {2018},
	pages = {1345-1350},
	doi = {10.1109/IWCMC.2018.8450538},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053888603\&doi=10.1109\%2fIWCMC.2018.8450538\&partnerID=40\&md5=7f9917ffc8d0c6f0be1c40a7bb027e30},
	author = {Assila, B. and Kobbane, A. and El Koutbi, M.}
}
@conference {Oualahj2018,
	title = {A Decentralized Control of Autonomous Delay Tolerant Networks: Multi Agents Markov Decision Processes Framework},
	booktitle = {IEEE International Conference on Communications},
	volume = {2018-May},
	year = {2018},
	doi = {10.1109/ICC.2018.8422718},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051430605\&doi=10.1109\%2fICC.2018.8422718\&partnerID=40\&md5=ea20d47bd369c11fe0555f1224db09f3},
	author = {Oualahj, O.A. and Kobbane, A. and Ben-Othman, J.}
}
@conference {Boudagdigue2018,
	title = {A Distributed Advanced Analytical Trust Model for IoT},
	booktitle = {IEEE International Conference on Communications},
	volume = {2018-May},
	year = {2018},
	doi = {10.1109/ICC.2018.8422726},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051430306\&doi=10.1109\%2fICC.2018.8422726\&partnerID=40\&md5=8907401b5d112341154ed5ed64157168},
	author = {Boudagdigue, C. and Benslimane, A. and Kobbane, A. and Elmachkour, M.}
}
@conference {Lhazmir20181,
	title = {Feature extraction based on principal component analysis for text categorization},
	booktitle = {PEMWN 2017 - 6th IFIP International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks},
	volume = {2018-January},
	year = {2018},
	pages = {1-6},
	doi = {10.23919/PEMWN.2017.8308030},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047773608\&doi=10.23919\%2fPEMWN.2017.8308030\&partnerID=40\&md5=6289e35e09bfba42463a76d9788407ed},
	author = {Lhazmir, S. and Moudden, I.E. and Kobbane, A.}
}
@conference {Oualhaj20181,
	title = {Graph-Based MDP to Mobile Source with Energy Harvesting in Delay Tolerant Networks System},
	booktitle = {2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings},
	volume = {2018-January},
	year = {2018},
	pages = {1-6},
	doi = {10.1109/GLOCOM.2017.8253948},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046359869\&doi=10.1109\%2fGLOCOM.2017.8253948\&partnerID=40\&md5=ad621053c85f2d4d1fe75a91423a6718},
	author = {Oualhaj, O.A. and Elmachkour, M. and Kobbane, A. and Ben-Othman, J.}
}
@conference {Lhazmir20181,
	title = {Green opportunistic access for cognitive radio networks: A regret matching based approach},
	booktitle = {Proceedings - 2018 International Conference on Advanced Communication Technologies and Networking, CommNet 2018},
	year = {2018},
	pages = {1-6},
	doi = {10.1109/COMMNET.2018.8360261},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048334349\&doi=10.1109\%2fCOMMNET.2018.8360261\&partnerID=40\&md5=74465a0ecf291e5fb7822c88709e0c5b},
	author = {Lhazmir, S. and Elmachkour, M. and Kobbane, A.}
}
@conference {BenHafaiedh20181,
	title = {LTE-U and WiFi coexistence in the 5 GHz unlicensed spectrum: A survey},
	booktitle = {PEMWN 2017 - 6th IFIP International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks},
	volume = {2018-January},
	year = {2018},
	pages = {1-7},
	doi = {10.23919/PEMWN.2017.8308025},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047727398\&doi=10.23919\%2fPEMWN.2017.8308025\&partnerID=40\&md5=65a02857c329a81d3574c38db67a7f92},
	author = {Ben Hafaiedh, H. and El Korbi, I. and Saidane, L.A. and Kobbane, A.}
}
@conference {Assila20181,
	title = {A Many-To-One Matching Game Approach to Achieve Low-Latency Exploiting Fogs and Caching},
	booktitle = {2018 9th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2018 - Proceedings},
	volume = {2018-January},
	year = {2018},
	pages = {1-2},
	doi = {10.1109/NTMS.2018.8328671},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051102582\&doi=10.1109\%2fNTMS.2018.8328671\&partnerID=40\&md5=93f51b2e077f7f00d3d0e5e5a8123950},
	author = {Assila, B. and Kobbane, A. and El Koutbi, M.}
}
@article {AitOualhaj2018,
	title = {Mobile delay-tolerant networks with energy-harvesting and wireless energy transfer cooperation},
	journal = {Concurrency Computation},
	year = {2018},
	doi = {10.1002/cpe.5112},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059067813\&doi=10.1002\%2fcpe.5112\&partnerID=40\&md5=4d5955405a79b55e86781f7a65a66687},
	author = {Ait Oualhaj, O. and Kobbane, A. and Ben-Othman, J.}
}
@article {Gmira20181436,
	title = {A New Energy Efficiency/Spectrum Efficiency Model for Cooperative Cognitive Radio Network},
	journal = {Mobile Networks and Applications},
	volume = {23},
	number = {5},
	year = {2018},
	pages = {1436-1448},
	doi = {10.1007/s11036-018-1078-z},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055932107\&doi=10.1007\%2fs11036-018-1078-z\&partnerID=40\&md5=2a9aa8fcbffa8cca76f1910b052525eb},
	author = {Gmira, S. and Kobbane, A. and Ben-Othman, J. and El Machkour, M.}
}
@article {Gmira2018405,
	title = {A new model for cooperative cognitive radio network using coalitional game},
	journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST},
	volume = {230},
	year = {2018},
	pages = {405-415},
	doi = {10.1007/978-3-319-90802-1_36},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048046108\&doi=10.1007\%2f978-3-319-90802-1_36\&partnerID=40\&md5=aecbb539131a30d55d9c7252d88f268a},
	author = {Gmira, S. and Kobbane, A. and Machkour, M.E. and Ben-Othman, J.}
}
@conference {Amine2018,
	title = {New user association scheme based on multi-objective optimization for 5G ultra-dense multi-RAT HetNets},
	booktitle = {IEEE International Conference on Communications},
	volume = {2018-May},
	year = {2018},
	doi = {10.1109/ICC.2018.8422154},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051424239\&doi=10.1109\%2fICC.2018.8422154\&partnerID=40\&md5=3572d774ac502ed9eb6c557554de3420},
	author = {Amine, M. and Walid, A. and Kobbane, A. and Ben-Othman, J.}
}
@conference {Filali2018,
	title = {SDN Controller Assignment and Load Balancing with Minimum Quota of Processing Capacity},
	booktitle = {IEEE International Conference on Communications},
	volume = {2018-May},
	year = {2018},
	doi = {10.1109/ICC.2018.8422750},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051428081\&doi=10.1109\%2fICC.2018.8422750\&partnerID=40\&md5=950211c49ab90c21d84d57b5ecf8c58f},
	author = {Filali, A. and Kobbane, A. and Elmachkour, M. and Cherkaoui, S.}
}
@conference {Mabrouk2018495,
	title = {Signaling game-based approach to improve security in vehicular networks},
	booktitle = {VEHITS 2018 - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems},
	volume = {2018-March},
	year = {2018},
	pages = {495-500},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051947337\&partnerID=40\&md5=fd17d3ff35b56253285bf7d433abcfa8},
	author = {Mabrouk, A. and Kobbane, A. and El Koutbi, M.}
}
@conference {Abouaomar201814,
	title = {Users-Fogs association within a cache context in 5G networks:Coalition game model},
	booktitle = {Proceedings - IEEE Symposium on Computers and Communications},
	volume = {2018-June},
	year = {2018},
	pages = {14-19},
	doi = {10.1109/ISCC.2018.8538500},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059221795\&doi=10.1109\%2fISCC.2018.8538500\&partnerID=40\&md5=e324f3454d662cef58a9c78528c68a60},
	author = {Abouaomar, A. and Elmachkour, M. and Kobbane, A. and Tembine, H. and Ayaida, M.}
}
@conference {Abouaomar2017,
	title = {Caching, device-to-device and fog computing in 5th cellular networks generation: Survey},
	booktitle = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
	year = {2017},
	note = {cited By 0},
	abstract = {Many researches and standardization work on the challenges that 5th networks generation raised from the radio perspective while employing advanced techniques such as massive MIMO (Multiple-Input-Multiple-Output) and CoMP (Cooperative Multi-points Processes). However the backhaul problems such as bottlenecks has emerged due to the deployment of ultradense and heavy traffic that should be connected to the core networks. In this paper we investigate the caching as a promising solution to deal with the backhaul problems and the offload of the network. By caching the content near the users, at the base stations or at the device side via device-to-device communications or in advanced architecture of the cloud (In the Fog) is a promising solution to bring the interesting content closer to the users. Caching techniques are many, in this paper we grouped the most interesting ones with regard to different architectures, considering the cases and the quality of the solutions. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/WINCOM.2017.8238174},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041450036\&doi=10.1109\%2fWINCOM.2017.8238174\&partnerID=40\&md5=08c633efad0f6759f14c9373be0f0b07},
	author = {Abouaomar, A. and Filali, A. and Kobbane, A.}
}
@conference {Harbouche2017,
	title = {Dynamic coalitional matching game approach for fair and swift data-gathering in wireless body sensor networks},
	booktitle = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
	year = {2017},
	note = {cited By 0},
	abstract = {Wireless Sensor Networks are deployed in different fields of application to gather data on the monitored environment. The Wireless Body Sensor Network (WBSN) is a wireless sensor network designed to monitor a human body vital and environment parameters. The design and development of such WBSN systems for health monitoring have been motivated by costly healthcare and propelled by the development of miniature health monitoring devices. This paper presents the architecture design of a preventive health care monitoring system. This architecture is designed for monitoring multiple patients in a hospital. It is based on a set of mobile data collectors and static sensors for analysis of various patient{\textquoteright}s parameters. The data collectors need to cooperate together in order to gather the data from the sensor nodes. The point of this paper is how to dynamically and effectively appoint and deploy several data collectors in the hospital to gather the measured data in minimal time. We formulate the problem as a coalitional matching game between patients and data collectors, and we propose a patientdata collector association algorithm that ensures fairness and minimum total course in the stable matchings. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/WINCOM.2017.8238179},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041451720\&doi=10.1109\%2fWINCOM.2017.8238179\&partnerID=40\&md5=44ef24b18e66b8fb24573d73db99025f},
	author = {Harbouche, A. and Elmachkour, M. and Djedi, N. and Erradi, M. and Kobbane, A.}
}
@conference {Kobbane2017,
	title = {Foreword},
	booktitle = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
	year = {2017},
	note = {cited By 0},
	doi = {10.1109/WINCOM.2017.8238019},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041601748\&doi=10.1109\%2fWINCOM.2017.8238019\&partnerID=40\&md5=b17c0b90bf6d6ab4bc5cb5be61f70c8c},
	author = {Kobbane, A. and Ibrahimi, K.}
}
@conference {Mourchid20171315,
	title = {A game-theoretic approach for non-overlapping communities detection},
	booktitle = {2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017},
	year = {2017},
	note = {cited By 1},
	pages = {1315-1320},
	abstract = {In this paper, we propose a game-theoretic approach to find the community structure in complex networks based on a non-cooperative game. This approach optimizes a node-based modularity for non-overlapping communities. Experiments show that our approach is effective to discover non-overlapping communities and obtain high values of modularity and Normalized Mutual Information (NMI) for real-world and synthetic networks in a reasonable time. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/IWCMC.2017.7986475},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027835444\&doi=10.1109\%2fIWCMC.2017.7986475\&partnerID=40\&md5=b0751b99b8a2552e780d327bef409ddf},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@conference {Amine20171245,
	title = {A many-to-many matching game in ultra-dense LTE HetNets},
	booktitle = {2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017},
	year = {2017},
	note = {cited By 0},
	pages = {1245-1250},
	abstract = {In this work, we focus our study to improving the energy efficiency of mobile cellular users in ultra-dense LTE HetNets. The hyper-dense co-channel deployment of indoor LTE small cell networks (SCNs) within LTE macro cell networks (MCNs) will aggravate the effect of cross-tier interferences caused by the uplink transmissions of macro-indoor users located inside the overlapping zones of small base station (SBS) coverage areas. Hence, degrading the uplink performance at the level of SBSs adopting closed access policy. In order to eliminate the severe cross-tier interferences, each SBS attempts to open the access for macro-indoor users that accept only the SBS with Max-SINR offer. This will lead to network congestion problems in several SCNs. Wherefore, we formulate our problem as a many-to-many matching game. Then, we introduce an algorithm that computes the optimal many-to-many stable matching which consist of assigning each macro-indoor user with multi-homing capabilities to the most suitable set of SBSs and vice versa based on their preference profiles. With regard to the conventional Max-SINR association scheme, our solution can effectively improve the energy efficiency of cellular users. Moreover, it can ensure load balancing in ultra-dense LTE HetNets. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/IWCMC.2017.7986463},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027886532\&doi=10.1109\%2fIWCMC.2017.7986463\&partnerID=40\&md5=a4a95449b5ea20b54454dcf7b7bd1e59},
	author = {Amine, M. and Walid, A. and Kobbane, A. and Cherkaoui, S.}
}
@conference {Azougaghe2017,
	title = {Many-to-one matching game towards secure virtual machines migration in cloud computing},
	booktitle = {2016 International Conference on Advanced Communication Systems and Information Security, ACOSIS 2016 - Proceedings},
	year = {2017},
	note = {cited By 0},
	abstract = {Virtual machine migration represents a new topic of research last years. In this context, we present a new system based on matching game theory to design efficient and practical migration algorithms that work well with huge numbers of VMs and servers. This strategy solves VM migration, resources managements and load balancing problems in cloud computing environment. The experimental results show that our algorithm not only obtains multi-resource load balancing performance but also improves the cloud security services and gets a gain of resources consummation on all servers. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/ACOSIS.2016.7843922},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015191060\&doi=10.1109\%2fACOSIS.2016.7843922\&partnerID=40\&md5=6b59b3295f8598830c0771717fb9a86b},
	author = {Azougaghe, A. and Oualhaj, O.A. and Hedabou, M. and Belkasmi, M. and Kobbane, A.}
}
@article {Harbouche20171339,
	title = {Model driven flexible design of a wireless body sensor network for health monitoring},
	journal = {Computer Networks},
	volume = {129},
	year = {2017},
	note = {cited By 1},
	pages = {1339-1351},
	abstract = {The Wireless Body Sensor Network (WBSN) is a wireless network that is designed to allow communication among sensor nodes that are attached to a human body to monitor the body{\textquoteright}s vital parameters and environment. The design and development of such WBSN systems for health monitoring have received a large amount of attention recently, in research studies and in industry. This attention is mainly motivated by costly health care and by recent advances in the development of miniature health monitoring devices as well as emerging technologies, such as the Internet of Things (IoT), which contribute to the main challenges of 5G. The existence of an explicit approach to address the required software design and verification should be very beneficial for the construction and maintenance of such systems. This paper presents a preventive health care system that has a flexible design. The proposed system is based on an architecture that has heterogeneous nodes and provides both daily continuous monitoring as well as specific controls. We defined a model to describe the WBSN{\textquoteright}s global behavior. An important aspect of this work is that we propose a model-driven engineering (MDE) approach to address the derivation of each node{\textquoteright}s behavior in the WBSN from the WBSN global behavior. This approach allows developers to obtain a system design from the global specification of its requirement. To ensure the conformance of this design to its specification, the derived behaviors should be validated and verified before their deployment. In fact, formal methods are powerful tools for software engineers to verify the logical correctness of concurrent software at different levels of its life cycle. Model checking is one of the most powerful formal methods for verifying the logical correctness of such concurrent systems. In this work, we make use of a model checking approach that is based on a model transformation to validate the automatically derived behavior of a WBSN for health monitoring. This model-driven approach will check whether the derived system behaves correctly according to its global specification, while the objective is to increase the system{\textquoteright}s performance and QoS. This approach allows the developer to reason about a model of the global system rather than about the system itself. {\textcopyright} 2017 Elsevier B.V.},
	doi = {10.1016/j.comnet.2017.06.014},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85022027303\&doi=10.1016\%2fj.comnet.2017.06.014\&partnerID=40\&md5=3d665e7ff240e8a6d9564857abf695da},
	author = {Harbouche, A. and Djedi, N. and Erradi, M. and Ben-Othman, J. and Kobbane, A.}
}
@conference {Khoufi2017,
	title = {Path planning of mobile sinks in charge of data gathering: A coalitional game theory approach},
	booktitle = {2016 IEEE 35th International Performance Computing and Communications Conference, IPCCC 2016},
	year = {2017},
	note = {cited By 0},
	abstract = {Game theory is often used to find equilibria where no player can unilaterally increase its own payoff by changing its strategy without changing the strategies of other players. In this paper, we propose to use coalition formation to compute the optimized tours of mobile sinks in charge of collecting data from static wireless sensor nodes. Mobile sinks constitute a very attractive solution for wireless sensor networks, WSNs, where the application requirements in terms of node autonomy are very strong unlike the requirement in terms of latency. Mobile sinks allow wireless sensor nodes to save energy The associated coalition formation problem has a stable solution given by the final partition obtained. However, the order in which the players play has a major impact on the final result. We determine the best order to minimize the number of mobile sinks needed. We evaluate the complexity of this coalitional game as well as the impact of the number of collect points per surface unit on the number of mobile sinks needed and on the maximum tour duration of these mobile sinks. In addition, we show how to extend the coalitional game to support different latencies for different types of data. Finally, we formalize our problem as an optimization problem and we perform a comparative evaluation. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/PCCC.2016.7820637},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013413857\&doi=10.1109\%2fPCCC.2016.7820637\&partnerID=40\&md5=3c4a3fe9d6f76ca57b380ffcb337856d},
	author = {Khoufi, I. and Minet, P. and Koulali, M.-A. and Kobbane, A.}
}
@conference {Mourchid2017,
	title = {Random walk based co-occurrence prediction in location-based social networks},
	booktitle = {IEEE International Conference on Communications},
	year = {2017},
	note = {cited By 0},
	abstract = {In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental results demonstrate that our LBRW-Co model have substantial advantages over baseline approaches in predicting and ranking co-occurrence interactions. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/ICC.2017.7997209},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028326862\&doi=10.1109\%2fICC.2017.7997209\&partnerID=40\&md5=f865adbae7afd91e045cf307bb52ae7f},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@conference {Aitfares2017113,
	title = {Suspicious behavior detection of people by monitoring camera},
	booktitle = {International Conference on Multimedia Computing and Systems -Proceedings},
	year = {2017},
	note = {cited By 0},
	pages = {113-117},
	abstract = {The analytic video is a very challenging area of research in computer vision. Ensure a high level of security in a public space monitored by a surveillance camera is a difficult task in recent years. Understanding people behaviors in real time allows the surveillance systems to analyze unusual events through the video frames. In this paper, we propose a new approach for detecting suspicious behavior of moving people. We are not interested in a simple motion detection of a moving object, but we analyze the trajectory of this latter; relying on the object motion vector. Once a suspicious behavior suddenly occurs in this trajectory, we segment and track this object during its motion within the camera{\textquoteright}s field of view. Experiments with real-world images validate the efficiency of the proposed approach. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/ICMCS.2016.7905601},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019074005\&doi=10.1109\%2fICMCS.2016.7905601\&partnerID=40\&md5=72fbf7b2e7ea117ae6bf2217a9fdc658},
	author = {Aitfares, W. and Kobbane, A. and Kriouile, A.}
}
@article {Walid201756,
	title = {Toward Eco-Friendly Smart Mobile Devices for Smart Cities},
	journal = {IEEE Communications Magazine},
	volume = {55},
	number = {5},
	year = {2017},
	note = {cited By 0},
	pages = {56-61},
	abstract = {It is expected that the incessant use of SBSs by indoor mobile users to achieve high data rate and high energy efficiency for their smart mobile devices will drive ultra dense deployment of SCNs within MCNs, specifically in future smart cities. However, SCN densification has a hard effect on the deterioration of the energy efficiency and QoS throughput of mobile users equipped with smart mobile devices like smartphones, laptops, PDAs, and tablets. This degradation is due to the severe cross-tier interferences occurring in ultra dense co-channel deployments of SCNs within MCNs. The present article intends to study the energy efficiency of mobile users for better battery life management of their smart mobile devices through minimal energy consumption during their uplink transmissions. The proposed solution, based on a fully decentralized algorithm for sharing time access executed by SBSs and multi-homing capabilities of macrocellular users, improves the energy efficiency of mobile users for better battery life, and keeps their QoS throughput requirements. Therefore, it leads to the eco-friendly smart mobile devices required in future smart cities. The results validate our proposed solution and show the improvement achieved compared to the conventional access control mechanisms. Furthermore, our scheme requires no coordination among SBSs and macro base stations, which reduces the huge signaling overhead when using cooperative schemes. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/MCOM.2017.1600271},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019660063\&doi=10.1109\%2fMCOM.2017.1600271\&partnerID=40\&md5=72802ad5f91b7f2273d0c16e81e53251},
	author = {Walid, A. and Kobbane, A. and Ben-Othman, J. and El Koutbi, M.}
}
@article {Mezouary2016325,
	title = {An energy-aware clustering approach based on the k-means method for wireless sensor networks},
	journal = {Lecture Notes in Electrical Engineering},
	volume = {366},
	year = {2016},
	note = {cited By 0},
	pages = {325-337},
	abstract = {This paper describes a new approach to build energy aware clusters for Wireless Sensor Networks (WSN). The algorithm behind is based on the k-means method which is well known as a clustering technique and widely used in several fields of engineering and research. K-means clustering tends to find clusters of comparable spatial extent (density clustering). We try to enhance the clustering process by selecting nodes as clusters that are centric and have a high level of energy. This will give the same QoS results as given by the K-means approach with a reduction of energy consumption and a prolongation of the lifetime of the sensor network. For the simulation purposes, we have implemented our approach on the OLSR routing protocol which has been selected by our research team as a test bed routing protocol. We have compared our new approach (OLSR-Kmeans-Energy) with a previous work we developed and where we use a Max-Min heuristic (OLSR-MaxMin-Energy) to enhance QoS parameters and the lifetime of the WSN. Our new approach seems to give better results than the MaxMin approach. {\textcopyright} Springer Science+Business Media Singapore 2016.},
	doi = {10.1007/978-981-287-990-5_26},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959098093\&doi=10.1007\%2f978-981-287-990-5_26\&partnerID=40\&md5=bcd3d9d29b98420d13c95f74f11a93c6},
	author = {Mezouary, R.E. and Choukri, A. and Kobbane, A. and Koutbi, M.E.}
}
@conference {Amine2016133,
	title = {Matching game for green uplink in hyper dense LTE HeTNets},
	booktitle = {Proceedings - 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016: Green Communications and Networking},
	year = {2016},
	note = {cited By 0},
	pages = {133-139},
	abstract = {In this paper, we aim to improve the energy efficiency of cellular users located in hyper-dense co-channel deployments of LTE small cell Networks (SCNs), randomly distributed within LTE macro cell networks (MCNs). Avoiding the severe cross-Tier interferences at the small base stations (SBSs) levels caused by the uplink transmissions between the macro indoor users (which are inside the SBS coverage area) and the macro base station (MBS), ensuring load balancing, and improving energy efficiency are critical technical challenges in hyper-dense co-channel LTE SCNs deployments. As a solution, we formulate our problem as a matching game, then we propose the deferred acceptance algorithm to compute the optimal stable matching consisting of assigning each macro indoor user to the most suitable SBS and vice versa. Simulation results validate our solution, and show how it can effectively improve the energy efficiency of cellular users in hyper-dense LTE HetNets compared to the default Max-SINR association scheme. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/WINCOM.2016.7777204},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010465149\&doi=10.1109\%2fWINCOM.2016.7777204\&partnerID=40\&md5=cfdd0315adeb3a468a5382cae7b1ed26},
	author = {Amine, M. and Walid, A. and Oualhaj, O.A. and Kobbane, A.}
}
@conference { ISI:000349673802062,
	title = {Packet dropping for Real-Time Applications in Wireless Networks},
	booktitle = {2013 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)},
	series = {IEEE International Conference on Communications},
	year = {2013},
	note = {IEEE International Conference on Communications (ICC), Budapest, HUNGARY, JUN 09-13, 2013},
	pages = {2949-2953},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper, we consider a multimedia data transmission system over a wireless channel, where packets are queued at the transmitter. Multimedia data transmission over wireless networks often suffers from delay, jitter and packet loss. The main problem to implement a wireless network is the high and variable bit error rate in the radio link (fading, shadowing etc). Among the most important performance measures for real time applications are the packet loss probability. In order to improve the radio link, one often retransmits packets that have not been well received (using the Automatic Retransmission reQuest). This however may lead to queuing phenomena and increased delay due to retransmissions, and to losses of packets due to buffer overflow. In this paper, we allow that the number of retransmission is finite. We model the system state by a three-dimensional Markov chain which represents the evolution the radio link state, the number of packets in the buffer and the number of transmission of a packet in the service. We use an advanced approach based on the theory of singular perturbation in order to compute some performance of interest.},
	isbn = {978-1-4673-3122-7},
	issn = {1550-3607},
	author = {Kobbane, A. and Ben-Othman, J. and El Koutbi, M.}
}
@conference {Belkasmi2012872,
	title = {Channel allocation strategies in opportunistic-based cognitive networks},
	booktitle = {IWCMC 2012 - 8th International Wireless Communications and Mobile Computing Conference},
	year = {2012},
	note = {cited By 4},
	pages = {872-877},
	doi = {10.1109/IWCMC.2012.6314319},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869167181\&doi=10.1109\%2fIWCMC.2012.6314319\&partnerID=40\&md5=8168e16ee34fac24497d20951170d54e},
	author = {Belkasmi, Y. and Kobbane, A. and Koutbi, M.E. and Ben-Othman, J.}
}
@article {Koulali2012,
	title = {Dynamic power control for energy harvesting wireless multimedia sensor networks},
	journal = {Eurasip Journal on Wireless Communications and Networking},
	volume = {2012},
	year = {2012},
	note = {cited By 3},
	doi = {10.1186/1687-1499-2012-158},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872869198\&doi=10.1186\%2f1687-1499-2012-158\&partnerID=40\&md5=2b0c34f9aac01ae9f865a22159e62779},
	author = {Koulali, M.-A. and Kobbane, A. and Koutbi, M.E. and Tembine, H. and Ben-Othman, J.}
}
@conference { ISI:000312855700097,
	title = {Dynamic Power Control with Energy Constraint for Multimedia Wireless Sensor Networks},
	booktitle = {2012 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)},
	series = {IEEE International Conference on Communications},
	year = {2012},
	note = {IEEE International Conference on Communications (ICC), Ottawa, CANADA, JUN 10-15, 2012},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In recent years, many approaches and techniques have been explored for the optimization of energy usage in Wireless Sensor Networks (WSN). It is well recognized that a proper energy consumption model is the foundation for developing and evaluating a power management scheme in WSN. In this paper, we propose a new complete information Markov Decision Process (MDP) model to characterize sensors energy levels. We also propose and compare several centralized power control policies to select the more efficient policy that optimizes throughput and energy consumption.},
	isbn = {978-1-4577-2053-6},
	issn = {1550-3607},
	author = {Kobbane, A. and Koulali, M. -A. and Tembine, H. and El Koutbi, M. and Ben-Othman, J.}
}
@conference {Kobbane2012518,
	title = {Dynamic power control with energy constraint for Multimedia Wireless Sensor Networks},
	booktitle = {IEEE International Conference on Communications},
	year = {2012},
	note = {cited By 2},
	pages = {518-522},
	doi = {10.1109/ICC.2012.6363971},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871981947\&doi=10.1109\%2fICC.2012.6363971\&partnerID=40\&md5=2e71bfe8b840a119435a1fb89dd122f0},
	author = {Kobbane, A. and Koulali, M.-A. and Tembine, H. and Koutbi, M.E. and Ben-Othman, J.}
}
@conference {Elmachkour201265,
	title = {New insights from a delay analysis for cognitive radio networks with and without reservation},
	booktitle = {IWCMC 2012 - 8th International Wireless Communications and Mobile Computing Conference},
	year = {2012},
	note = {cited By 5},
	pages = {65-70},
	doi = {10.1109/IWCMC.2012.6314179},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869156676\&doi=10.1109\%2fIWCMC.2012.6314179\&partnerID=40\&md5=9cfed6da1f67007546e0b300b3572406},
	author = {Elmachkour, M. and Kobbane, A. and Sabir, E. and Koutbi, M.E.}
}
@conference { ISI:000322375100023,
	title = {Optimal Distributed Relay Selection for Duty-Cycling Wireless Sensor Networks},
	booktitle = {2012 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
	series = {IEEE Global Communications Conference},
	year = {2012},
	note = {IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, DEC 03-07, 2012},
	pages = {145-150},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Recent advances in localization technologies and algorithms for Wireless Sensor Networks (WSN) motivate the exploitation of location information in routing protocols. In this paper we consider the geographic forwarding of sporadically generated alarm messages. Our objective is to optimize sensor{\textquoteright}s energy consumption while respecting QoS constraints on transmission delay. For instance, we propose an optimal distributed relay selection policy for WSN with duty-cycling sensors based on a Markov Decision Process (MDP) with complete information. Also, we establish sufficient conditions for optimality of threshold policies. Then, end-to-end performances for a heuristic multi-hop relay selection strategy are established. Finally, we extend our model to account for queuing capabilities at sensor level.},
	isbn = {978-1-4673-0921-9; 978-1-4673-0920-2},
	issn = {2334-0983},
	author = {Koulali, M. -A. and Kobbane, A. and El Koutbi, M. and Ben-Othman, J.}
}
@conference {Koulali2012145,
	title = {Optimal distributed relay selection for duty-cycling Wireless Sensor Networks},
	booktitle = {GLOBECOM - IEEE Global Telecommunications Conference},
	year = {2012},
	note = {cited By 5},
	pages = {145-150},
	doi = {10.1109/GLOCOM.2012.6503104},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877653430\&doi=10.1109\%2fGLOCOM.2012.6503104\&partnerID=40\&md5=96b3bdee645f0fc14aed4cb197e85ce0},
	author = {Koulali, M.-A. and Kobbane, A. and El Koutbi, M. and Ben-Othman, J.}
}
@conference {Koulali201247,
	title = {QDGRP: A hybrid QoS Distributed Genetic routing protocol for Wireless Sensor Networks},
	booktitle = {Proceedings of 2012 International Conference on Multimedia Computing and Systems, ICMCS 2012},
	year = {2012},
	note = {cited By 2},
	pages = {47-52},
	doi = {10.1109/ICMCS.2012.6320271},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869852900\&doi=10.1109\%2fICMCS.2012.6320271\&partnerID=40\&md5=d66a629d14ff4cf85a93e8ce6708dbb9},
	author = {Koulali, M.-A. and Kobbane, A. and El Koutbi, M. and Azizi, M.}
}
@article {Tembine20111529,
	title = {Dynamic robust power allocation games under channel uncertainty and time delays},
	journal = {Computer Communications},
	volume = {34},
	number = {12},
	year = {2011},
	note = {cited By 1},
	pages = {1529-1537},
	doi = {10.1016/j.comcom.2011.02.009},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79959380843\&doi=10.1016\%2fj.comcom.2011.02.009\&partnerID=40\&md5=5103dd198356953b3e6cf4a1d9c94519},
	author = {Tembine, H. and Kobbane, A. and Koutbi, M.E.}
}
@conference {Tembine2010,
	title = {Robust power allocation games under channel uncertainty and time delays},
	booktitle = {2010 IFIP Wireless Days, WD 2010},
	year = {2010},
	note = {cited By 0},
	doi = {10.1109/WD.2010.5657740},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751549432\&doi=10.1109\%2fWD.2010.5657740\&partnerID=40\&md5=d221e9e9441f6d59228be21fe99203da},
	author = {Tembine, H. and Kobbane, A. and El Koutbi, M.}
}
