@article {Elghomary202236,
	title = {Design of a Smart MOOC Trust Model: Towards a Dynamic Peer Recommendation to Foster Collaboration and Learner{\textquoteright}s Engagement},
	journal = {International Journal of Emerging Technologies in Learning},
	volume = {17},
	number = {5},
	year = {2022},
	note = {cited By 2},
	pages = {36-56},
	abstract = {Recent evolutions in the Internet of Things (IoT) and Social IoT (SIoT) are facilitating collaboration as well as social interactions between entities in various environments, especially Smart Learning Ecosystems (SLEs). However, in these contexts, trust issues become more intense, learners feel suspicious and avoid collaborating with their peers, leading to their demotivation and disengagement. Hence, a Trust Management System (TMS) has become a crucial challenge to promote qualified collaboration and stimulate learners{\textquoteright} engagement. In the literature, several trust models were proposed in various domains, but rarely those that address trust issues in SLEs, especially in MOOCs. While these models exclusively rank the best nodes and fail to detect the untrustworthy ones. Therefore, in this paper, we propose Machine Learning-based trust evaluation model that considers social and dynamic trust parameters to quantify entities{\textquoteright} behaviors. It can distinguish trustworthy and untrustworthy behaviors in MOOCs to recommend benign peers while blocking malicious ones to build a dynamic trust-based peer recommendation in the future phase. Our model prevents learners from wasting their time in unprofitable interactions, protects them from malicious actions, and boosts their engagement. A simulation experiment using real-world SIoT datasets and encouraging results show the performance of our trust model {\textcopyright} 2022, International Journal of Emerging Technologies in Learning. All Rights Reserved.},
	keywords = {Curricula, e-learning, Internet of things, Learning ecosystems, Machine learning, Massive open online course, Peer recommendation, Security of data, Smart education, Social internet of thing, Trust management system, Trust management systems, Trust models},
	doi = {10.3991/ijet.v17i05.27705},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127011761\&doi=10.3991\%2fijet.v17i05.27705\&partnerID=40\&md5=5d062bc0485ddb7b7d27830779b55330},
	author = {Elghomary, K. and Bouzidi, D. and Daoudi, N.}
}
@article {Elhachmi2022207,
	title = {Distributed reinforcement learning for dynamic spectrum allocation in cognitive radio-based internet of things},
	journal = {IET Networks},
	volume = {11},
	number = {6},
	year = {2022},
	note = {cited By 0},
	pages = {207-220},
	abstract = {Cognitive Radio (CR) with other advancements such as the Internet of things and machine learning has recently emerged as the main involved technique to use spectrum in an efficient manner. It can access the spectrum in a fully dynamic way and exploit the unused spectrum resources without creating any harm to cognitive users. In this paper, the authors develop a CR access strategy founded on the implementation of an efficient Deep Multi-user Reinforcement Learning algorithm based on a combination of a Deep neural network, Q-learning, and cooperative multi-agent systems. The proposed approach consists of two stages: the user choice algorithm to set up an agent{\textquoteright}s activation order, and the frequency choice method to select the optimal channel on the appropriate bandwidth. Reasonable implementation is proposed, and the obtained results demonstrate that the authors{\textquoteright} approach can improve wireless communication for all CR terminals. It shows satisfactory performances in terms of user satisfaction degree and the number of used channels and can keep the channel allocation plan always in the appropriate state. {\textcopyright} 2022 The Authors. IET Networks published by John Wiley \& Sons Ltd on behalf of The Institution of Engineering and Technology.},
	keywords = {Cognitive radio, Deep learning, Deep neural networks, Dynamic spectrum allocations, Intelligent agents, Internet of things, Learning algorithms, Machine-learning, Multi agent systems, Multiusers, Q-learning, Radio access, Reinforcement learning, Reinforcement learning algorithms, Reinforcement learnings, Spectra{\textquoteright}s, Spectrum allocation},
	doi = {10.1049/ntw2.12051},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136563113\&doi=10.1049\%2fntw2.12051\&partnerID=40\&md5=af41f0c1a8d989dead96990172cd073c},
	author = {Elhachmi, J.}
}
@article {Douch202269264,
	title = {Edge Computing Technology Enablers: A Systematic Lecture Study},
	journal = {IEEE Access},
	volume = {10},
	year = {2022},
	note = {cited By 1},
	pages = {69264-69302},
	abstract = {With the increasing stringent QoS constraints (e.g., latency, bandwidth, jitter) imposed by novel applications (e.g., e-Health, autonomous vehicles, smart cities, etc.), as well as the rapidly increasing number of connected IoT (Internet of Things) devices, the core network is becoming increasingly congested. To cope with those constraints, Edge Computing (EC) is emerging as an innovative computing paradigm that leverages Cloud computing and brings it closer to the customer. {\textquoteright}EC{\textquoteright} refers to transferring computing power and intelligence from the central Cloud to the network{\textquoteright}s Edge. With that, EC promotes the idea of processing and caching data at the Edge, thus reducing network congestion and latency. This paper presents a detailed, thorough, and well-structured assessment of Edge Computing and its enabling technologies. Initially, we start by defining EC from the ground up, outlining its architectures and evolution from Cloudlets to Multi-Access Edge Computing. Next, we survey recent studies on the main cornerstones of an EC system, including resource management, computation offloading, data management, network management, etc. Besides, we emphasized EC technology enablers, starting with Edge Intelligence, the branch of Artificial Intelligence (AI) that integrates AI models at resource-constrained edge nodes with significant heterogeneity and mobility. Then, moving on to 5G and its empowering technologies, we explored how EC and 5G complement each other. After that, we studied virtualization and containerization as promising hosting runtime for edge applications. Further to that, we delineated a variety of EC use-case scenarios, e.g., smart cities, e-Health, military applications, etc. Finally, we concluded our survey by highlighting the role of EC integration with future concerns regarding green energy and standardization. {\textcopyright} 2013 IEEE.},
	keywords = {5g, 5g mobile communication, 5G mobile communication systems, Cloud-computing, computation offloading, Containerization, Containers, Data handling, Edge computing, Edge intelligence, Fog computing, Information management, Internet of things, License, Military applications, Mobile communications, Multi-access edge computing, Multiaccess, Quality of service, Quality-of-service, Surveys},
	doi = {10.1109/ACCESS.2022.3183634},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132750947\&doi=10.1109\%2fACCESS.2022.3183634\&partnerID=40\&md5=88667ef450dd686759983878427de051},
	author = {Douch, S. and Abid, M.R. and Zine-Dine, K. and Bouzidi, D. and Benhaddou, D.}
}
@article {Bourja2022994,
	title = {End-to-End Car Make and Model Classification using Compound Scaling and Transfer Learning},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {13},
	number = {5},
	year = {2022},
	note = {cited By 0},
	pages = {994-1001},
	abstract = {Recently, Morocco has started to invest in IoT systems to transform our cities into smart cities that will promote economic growth and make life easier for citizens. One of the most vital addition is intelligent transportation systems which represent the foundation of a smart city. However, the problem often faced in such systems is the recognition of entities, in our case, car and model makes. This paper proposes an approach that identifies makes and models for cars using transfer learning and a workflow that first enhances image quality and quantity by data augmentation and then feeds the newly generated data into a deep learning model with a scaling feature{\textendash}that is, compound scaling. In addition, we developed a web interface using the FLASK API to make real-time predictions. The results obtained were 80\% accuracy, fine-tuning it to an accuracy rate of 90\% on unseen data. Our framework is trained on the commonly used Stanford Cars dataset. {\textcopyright} 2022. International Journal of Advanced Computer Science and Applications. All Rights Reserved.},
	keywords = {Application programming interfaces (API), Compound scaling, Deep learning, Economic growths, Economics, End to end, Image enhancement, Intelligent systems, Intelligent transportation systems, Internet of things, IOT, Model classification, Scalings, Smart city, Transfer learning, Vehicle classification},
	doi = {10.14569/IJACSA.2022.01305111},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131410221\&doi=10.14569\%2fIJACSA.2022.01305111\&partnerID=40\&md5=aeb1c5a894ab70005066f491ebf3623c},
	author = {Bourja, O. and Maach, A. and Zannouti, Z. and Derrouz, H. and Mekhzoum, H. and Abdelali, H.A. and Thami, R.O.H. and Bourzeix, F.}
}
@article {Kharbouch2022,
	title = {Internet-of-Things Based Hardware-in-the-Loop Framework for Model-Predictive-Control of Smart Building Ventilation},
	journal = {Sensors},
	volume = {22},
	number = {20},
	year = {2022},
	note = {cited By 0},
	abstract = {In this work, a Hardware-In-the-Loop (HIL) framework is introduced for the implementation and the assessment of predictive control approaches in smart buildings. The framework combines recent Internet of Things (IoT) and big data platforms together with machine-learning algorithms and MATLAB-based Model Predictive Control (MPC) programs in order to enable HIL simulations. As a case study, the MPC algorithm was deployed for control of a standalone ventilation system (VS). The objective is to maintain the indoor Carbon Dioxide (CO2) concentration at the standard comfort range while enhancing energy efficiency in the building. The proposed framework has been tested and deployed in a real-case scenario of the EEBLab test site. The MPC controller has been implemented on MATLAB/Simulink and deployed in a Raspberry Pi (RPi) hardware. Contextual data are collected using the deployed IoT/big data platform and injected into the MPC and LSTM machine learning models. Occupants{\textquoteright} numbers were first forecasted and then sent to the MPC to predict the optimal ventilation flow rates. The performance of the MPC control over the HIL framework has been assessed and compared to an ON/OFF strategy. Results show the usefulness of the proposed approach and its effectiveness in reducing energy consumption by approximately 16\%, while maintaining good indoor air quality. {\textcopyright} 2022 by the authors.},
	keywords = {Air conditioning, Air pollution, Building ventilations, Carbon dioxide, Control approach, Control program, Data platform, energy efficiency, Energy utilization, Hardware in the loops, Hardware-in-the-loop simulation, Hardwarein-the-loop simulations (HIL), Indoor, Indoor air pollution, Internet of things, Learning algorithms, Long short-term memory, Machine learning algorithms, Machine-learning, MATLAB, Model predictive control, Model-predictive control, Predictive control, procedures, Simulation platform, Synthetic apertures, Ventilation},
	doi = {10.3390/s22207978},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140844555\&doi=10.3390\%2fs22207978\&partnerID=40\&md5=85b1a27cdc872a2b2f27b188c17282c8},
	author = {Kharbouch, A. and Berouine, A. and Elkhoukhi, H. and Berrabah, S. and Bakhouya, M. and El Ouadghiri, D. and Gaber, J.}
}
@article {Ismaili-Alaoui2022900,
	title = {IoDEP: Towards an IoT-Data Analysis and Event Processing Architecture for Business Process Incident Management},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {13},
	number = {4},
	year = {2022},
	note = {cited By 0},
	pages = {900-915},
	abstract = {IoT is becoming a hot spot area of technological innovations and economic development promises for many industries and services. This new paradigm shift affects all the enterprise architecture layers from infrastructure to business. Business Process Management (BPM) is a field among others that is affected by this new technology. To assist data and events explosion resulting, among others, from IoT, data analytic processes combined with event processing techniques, examine large data sets to uncover hidden patterns, unknown correlations between collected events, either at a very technical level (incident/anomaly detection, predictive maintenance) or at business level (customer preferences, market trends, revenue opportunities) to provide improved operational efficiency, better customer service and competitive advantages over rival organizations. In order to capitalize the business value of data and events generated by IoT sensors, IoT, Data Analytics and BPM need to meet in the middle. In this paper, we propose an end-to-end IoT-BPM integration architecture (IoDEP: IoT-Data-Event-Process) for a proactive business process incident management. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions. {\textcopyright} 2022. All Rights Reserved.},
	keywords = {Big data, Business Process, Competition, Complex event processing, Complex events, Data Analytics, Data handling, Economic development, Efficiency, Enterprise resource management, Event Processing, Event processing architectures, Hot spot area, Incident Management, Information management, Internet of things, Machine learning, Technological innovation},
	doi = {10.14569/IJACSA.2022.01304104},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130098329\&doi=10.14569\%2fIJACSA.2022.01304104\&partnerID=40\&md5=af3b2fd1443242906731e18007ed61ab},
	author = {Ismaili-Alaoui, A. and Baina, K. and Benali, K.}
}
@article {ElHaddouti2022575,
	title = {A Secure and Trusted Fog Computing Approach based on Blockchain and Identity Federation for a Granular Access Control in IoT Environments},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {13},
	number = {3},
	year = {2022},
	note = {cited By 0},
	pages = {575-584},
	abstract = {Fog computing is a new computing paradigm that is an extension of the standard cloud computing model, which can be adopted as a cost effective strategy for managing connected objects, by enabling real-time computing and communication for analytical and decision making. Nonetheless, even though Fog-based Internet of Things networks optimize the standard architecture by moving computing, storage, communication, and control decision closer to the edge network, the technology becomes open to malicious attackers and remains many business risks that are not yet resolved. In fact, access control, privacy as well as trust risks present major challenges in Internet of Things environments based on Fog computing due to the large scale distributed nature of devices at the Fog layer. In addition, the traditional authentication methods are not adequate in Fog-based Internet of Things contexts since they consume significantly more computation power and incur high latency. To deal with these gaps, we present in this paper a secure and trusted Fog Computing approach based on Blockchain and Identity Federation technologies for a granular access control in IoT environments. The proposed scheme uses Smart Contract concept and Attribute-Based Access Control model to ensure the level of security and scalability required for data integrity without resorting to a central authority to make an access decision {\textcopyright} 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved.},
	keywords = {Access control, Block-chain, Cloud-computing, Computing model, Computing paradigm, Cost effective strategies, Cost effectiveness, Decision making, Decisions makings, Digital storage, Fog, Fog computing, Identity federation, Internet of things, IOT, Real-time communication, Real-time computing, Smart contract, Trusted computing},
	doi = {10.14569/IJACSA.2022.0130368},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129902962\&doi=10.14569\%2fIJACSA.2022.0130368\&partnerID=40\&md5=65966293c50d57a061513c913c7b5bb3},
	author = {El Haddouti, S. and El Kettani, M.D.E.-C.}
}
@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.}
}
@conference {Mouchfiq2021,
	title = {Blockchain-based Model Against selfish Attacks in Mobile ad hoc Networks},
	booktitle = {Proceedings - 4th International Conference on Advanced Communication Technologies and Networking, CommNet 2021},
	year = {2021},
	note = {cited By 0},
	abstract = {Over the past several decades, the importance of security has been increasing, in particular in the area of research addressing the Internet of Things (IoT) and, implicitly, ad hoc networks since they are part of it. Researchers have adopted blockchain as an interesting and trendy research topic in the wireless ad hoc environment. Due to its strong characteristics, such as consensus, immutability, finality and provenance, it{\textquoteright}s used not only as a secure data storage for critical data, but also as a platform that facilitates trustless data exchange between independent parties. However, the main challenge of applying blockchain in an ad hoc network is what kind of nodes should be involved in the validation process and how to adopt the heavy computational complexity of block validation in an appropriate way while maintaining its authentic characteristics. In this paper, we propose a new blockchain-based model against selfish attacks in ad hoc networks and optimize it in this context, to this end, we investigate the presence of MPR nodes to adapt and integrate the blockchain principle in MANETs and based on this we conduct a security analysis to evaluate our model by discussing the ability of our model to meet major security issues related to confidentiality, integrity, availability, non-repudiation, and vulnerability to attacks. {\textcopyright} 2021 IEEE.},
	keywords = {Ad hoc environment, Ad-hoc networks, Block-chain, Blockchain, Digital storage, Electronic data interchange, Internet of things, Mobile ad hoc networks, Mobile ad-hoc networks, Mobile security, MPR, Network security, Research topics, Secure data storage, Security, Selfish attack, Wireless ad hoc},
	doi = {10.1109/CommNet52204.2021.9641959},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124026049\&doi=10.1109\%2fCommNet52204.2021.9641959\&partnerID=40\&md5=83605288b49be75af72d459c6e278bdd},
	author = {Mouchfiq, N. and Habbani, A. and Benjbara, C. and Berradi, H.}
}
@article {Sabri2021708,
	title = {Internet of Things (IoT) based Smart Vehicle Security and Safety System},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {12},
	number = {4},
	year = {2021},
	note = {cited By 5},
	pages = {708-714},
	abstract = {The Internet of Things (IoT) is making human life easy in all aspects. The applications it offers are beyond comprehension. IoT is an abstract idea, a notion which interconnects all devices, tools, and gadgets over the Internet to enable these devices to communicate with one another. IoT finds application in various areas, such as intelligent cars and their safety, security, navigation, and efficient fuel consumption. This project puts forth a solution to achieve the desired outcome of saving precious human lives that are lost to road crashes. In this context, we propose to develop a system, we are designing and deploying a system that not only avoids accidents but also to take action accordingly. This research aims at dealing with the issues that cause fatal crashes and also integrates measures to ensure safety. Life without transportation is impossible to imagine; it makes far off places easy to reach and greatly reduces the travel time. But the problems which surface due to the ever-increasing number of vehicles on the road cannot be ignored. The project aims to eradicate a few of the major reasons of car crashes and also aims to integrate post-crash measures. {\textcopyright} 2021. All Rights Reserved.},
	keywords = {Accidents, Human lives, Intelligent cars, Internet of thing, Internet of things, Road crash, Roads and streets, Safety system, Security systems, Smart vehicle security, Smart vehicles, Travel time, Vehicle safety systems, Vehicle security, Vehicle security systems, Vehicles},
	doi = {10.14569/IJACSA.2021.0120487},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105821283\&doi=10.14569\%2fIJACSA.2021.0120487\&partnerID=40\&md5=189019e4527257ddbc9f3942fc925425},
	author = {Sabri, Y. and Siham, A. and Maizate, A.}
}
@article {Elmouatamid2021571,
	title = {A MicroGrid System Infrastructure Implementing IoT/Big-Data Technologies for Efficient Energy Management in Buildings},
	journal = {Green Energy and Technology},
	year = {2021},
	note = {cited By 4},
	pages = {571-600},
	abstract = {Recent studies showed that energy consumption in buildings could be efficiently reduced by including recent IoT (Internet of Things) and Big-Data technologies into microgrid systems. In fact, three major aspects could be further considered for reducing energy consumption while maintaining a suitable occupants{\textquoteright} comfort, (i) integrating renewable energy sources and storage devices, (ii) integrating programmable and less-energy-consuming equipment, and (iii) deploying innovative information and communication technologies. These aspects might contribute substantially to the improvement of winning and saving energy toward smart and energy-efficient buildings. In this chapter, a microgrid system infrastructure is developed together with a platform for data gathering, monitoring, and processing. We put more emphasis on microgrid systems as crucial infrastructures for leveraging energy-efficient and smart buildings by developing and deploying a holistic IoT/Big-Data platform in which sensing and actuation tasks are performed according to the actual contextual changes. Scenarios are presented in order to show the usefulness of this holistic platform for monitoring, data processing, and control in energy-efficient buildings. {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	keywords = {Data gathering, Data handling, Data technologies, energy efficiency, Energy efficient, Energy efficient building, Energy utilization, Information and Communication Technologies, Intelligent buildings, Internet of things, Micro-grid systems, Microgrids, Monitoring, Reducing energy consumption, Renewable energy resources, Renewable energy source, Virtual storage},
	doi = {10.1007/978-3-030-64565-6_20},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105764631\&doi=10.1007\%2f978-3-030-64565-6_20\&partnerID=40\&md5=b0a762b2a1e37fc93eff19c16f955daa},
	author = {Elmouatamid, A. and NaitMalek, Y. and Ouladsine, R. and Bakhouya, M. and El kamoun, N. and Khaidar, M. and Zine-Dine, K.}
}
@article {Mouchfiq2021288,
	title = {Security issues in manets: A survey},
	journal = {Advances in Intelligent Systems and Computing},
	volume = {1184},
	year = {2021},
	note = {cited By 2},
	pages = {288-295},
	abstract = {Recently, the notion of security has become increasingly important to research on wireless networks, later the Internet of things (IoT) and ad hoc networks that are a part of IoT environment. The various changes in the digital environment, as it must identify the different changes in the digital environment, are namely the protection of the personal and professional data of this intelligent world. In the work already done, there are several methods and levels of security. In this study, we identify that security aggression MANETs are facing with the security services to provide in each layer. In order to reach our target, we did a literature search gathering information on different types of attacks and solutions, as well as the latest security work. Then, we discuss the proposed solutions to ensure a high level of security in networks by recalling the latest work of our team. Finally, we propose a method of security better adapted to our needs based on blockchain technology. {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.},
	keywords = {Digital environment, In networks, Internet of thing (IOT), Internet of things, Literature search, Mobile ad hoc networks, Network security, Security issues, Security services},
	doi = {10.1007/978-981-15-5859-7_28},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091934292\&doi=10.1007\%2f978-981-15-5859-7_28\&partnerID=40\&md5=94af6860a11351f3307ffc8d94ae12a3},
	author = {Mouchfiq, N. and Habbani, A. and Benjbara, C.}
}
@article {Talei2021,
	title = {Smart building energy inefficiencies detection through time series analysis and unsupervised machine learning},
	journal = {Energies},
	volume = {14},
	number = {19},
	year = {2021},
	note = {cited By 6},
	abstract = {The climate of Houston, classified as a humid subtropical climate with tropical influences, makes the heating, ventilation, and air conditioning (HVAC) systems the largest electricity consumers in buildings. HVAC systems in commercial buildings are usually operated by a centralized control system and/or an energy management system based on a fixed schedule and scheduled control of a zone setpoint, which is not appropriate for many buildings with changing occupancy rates. Lately, as part of energy efficiency analysis, attention has focused on collecting and analyzing smart meters and building-related data, as well as applying supervised learning techniques, to propose new strategies to operate HVAC systems and reduce energy consumption. On the other hand, unsupervised learning techniques have been used to study the consumption information and profile characterization of different buildings after cluster analysis is performed. This paper adopts a different approach by revealing the power of unsupervised learning to cluster data and unveiling hidden patterns. In this study, we also identify energy inefficiencies after exploring the cluster results of a single building{\textquoteright}s HVAC consumption data and building usage data as part of the energy efficiency analysis. Time series analysis and the K-means clustering algorithm are successfully applied to identify new energy-saving opportunities in a highly efficient office building located in the Houston area (TX, USA). The paper uses 1-year data from a highly efficient Leadership in Energy and Environment Design (LEED)-, Energy Star-, and Net Zero-certified building, showing a potential energy savings of 6\% using the K-means algorithm. The results show that clustering is instrumental in helping building managers identify potential additional energy savings. {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.},
	keywords = {Clusterings, Conditioning systems, energy efficiency, Energy management systems, Energy savings, Energy utilization, Energy-savings, Harmonic analysis, Heating ventilation and air conditioning, Houston, HVAC, Internet of things, K-means clustering, Leadership in energy and environment design building, Leadership in energy and environment designs, Learning algorithms, Office buildings, Potential energy, Time series analysis, Time-series analysis, Times series, Tropics, Unsupervised learning},
	doi = {10.3390/en14196042},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115608885\&doi=10.3390\%2fen14196042\&partnerID=40\&md5=e01e465020f683b8a7ccebf61bf08077},
	author = {Talei, H. and Benhaddou, D. and Gamarra, C. and Benbrahim, H. and Essaaidi, M.}
}
@article {Majdoubi2021,
	title = {SmartMedChain: A Blockchain-Based Privacy-Preserving Smart Healthcare Framework},
	journal = {Journal of Healthcare Engineering},
	volume = {2021},
	year = {2021},
	note = {cited By 6},
	abstract = {Nowadays, the adoption of Internet of Things (IoT) technology worldwide is accelerating the digital transformation of healthcare industry. In this context, smart healthcare (s-healthcare) solutions are ensuring better and innovative opportunities for healthcare providers to improve patients{\textquoteright} care. However, these solutions raise also new challenges in terms of security and privacy due to the diversity of stakeholders, the centralized data management, and the resulting lack of trustworthiness, accountability, and control. In this paper, we propose an end-to-end Blockchain-based and privacy-preserving framework called SmartMedChain for data sharing in s-healthcare environment. The Blockchain is built on Hyperledger Fabric and stores encrypted health data by using the InterPlanetary File System (IPFS), a distributed data storage solution with high resiliency and scalability. Indeed, compared to other propositions and based on the concept of smart contracts, our solution combines both data access control and data usage auditing measures for both Medical IoT data and Electronic Health Records (EHRs) generated by s-healthcare services. In addition, s-healthcare stakeholders can be held accountable by introducing an innovative Privacy Agreement Management scheme that monitors the execution of the service in respect of patient preferences and in accordance with relevant privacy laws. Security analysis and experimental results show that the proposed SmartMedChain is feasible and efficient for s-healthcare environments. Copyright {\textcopyright} 2021 Driss El Majdoubi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.},
	keywords = {Access control, adult, Article, Block-chain, Blockchain, Centralised, controlled study, Data Management, Delivery of Health Care, Digital storage, Digital transformation, Distributed ledger, electronic health record, Electronic Health Records, Health care, health care delivery, Health care providers, Healthcare environments, Healthcare industry, human, Humans, Information management, information processing, information storage, Internet of things, Internet of things technologies, Network security, patient care, patient preference, Privacy, Privacy preserving, Privacy-preserving techniques, Security and privacy, Smart contract},
	doi = {10.1155/2021/4145512},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121960725\&doi=10.1155\%2f2021\%2f4145512\&partnerID=40\&md5=0f8afcea0c53e46d9f3863d4ed04b5b8},
	author = {Majdoubi, D.E. and Bakkali, H.E. and Sadki, S.}
}
@article {LHAZMIR2020102102,
	title = {A decision-making analysis in UAV-enabled wireless power transfer for IoT networks},
	journal = {Simulation Modelling Practice and Theory},
	volume = {103},
	year = {2020},
	pages = {102102},
	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.},
	keywords = {GMDP, Internet of things, Unmanned aerial vehicle, Wireless energy transfer},
	issn = {1569-190X},
	doi = {https://doi.org/10.1016/j.simpat.2020.102102},
	url = {https://www.sciencedirect.com/science/article/pii/S1569190X2030040X},
	author = {Safae Lhazmir and Omar Ait Oualhaj and Abdellatif Kobbane and Lynda Mokdad}
}
@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 {Hafdi2020,
	title = {Formal Modeling and Validation of Micro Smart Grids Based on ReDy Architecture},
	booktitle = {Proceedings of 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications, CloudTech 2020},
	year = {2020},
	note = {cited By 0},
	abstract = {Several cities in the world are moving from traditional power grid to Smart Grids. In order to set up Smart Grids, we should be able to face many challenges related to reliability, scalability, dynamism, technological solutions, security, etc. In this paper, we propose a case study where we model a micro Smart Grid according to the ReDy architecture, which is intended for IoT applications. The ReDy architecture provides a base to implement a scalable, reliable, and dynamic IoT network ready to meet Smart Grid needs. In order to prove those requirements, we opted for formal modeling and validation approach using model checking techniques. This formal analysis is carried out using the CADP toolbox. {\textcopyright} 2020 IEEE.},
	keywords = {Artificial intelligence, Binary alloys, Cloud computing, Dysprosium alloys, Electric power transmission networks, Formal analysis, Formal model, Internet of things, IOT applications, IOT networks, Microgrids, Model checking, Model-checking techniques, Network architecture, Power grids, Rhenium alloys, Smart grid, Smart power grids, Technological solution},
	doi = {10.1109/CloudTech49835.2020.9365923},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102629868\&doi=10.1109\%2fCloudTech49835.2020.9365923\&partnerID=40\&md5=7c48017aaa6f8aa00a31f5ae27bd816c},
	author = {Hafdi, K. and Kriouile, A.}
}
@conference {Fagroud2020572,
	title = {IoT search engines: Exploratory data analysis},
	booktitle = {Procedia Computer Science},
	volume = {175},
	year = {2020},
	note = {cited By 4},
	pages = {572-577},
	abstract = {IOT search engine (IOTSE) is a search tool proposed with the aim to allow research, list and identification of IOT devices (All devices connected to the internet represent an IOT device). This tool provides a huge amount of data, which is justified by the exponential increase of the number of objects connected in the world. The data provided must be analyzed and interpreted in the aim to give a better understanding, quickly description and help to make decisions. In this work we applied exploratory data analysis on IOT search engine data in order to give an analysis of IOTSE data with visual method. {\textcopyright} 2020 The Authors.},
	keywords = {Data handling, Exploratory data analysis, Exponential increase, Information analysis, Internet of things, Search engines, Search tools, Ubiquitous computing},
	doi = {10.1016/j.procs.2020.07.082},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094620165\&doi=10.1016\%2fj.procs.2020.07.082\&partnerID=40\&md5=d36b954ecd9cc39a0e670b7bcb86a85b},
	author = {Fagroud, F.Z. and Ajallouda, L. and Lahmar, E.H.B. and Toumi, H. and Achtaich, K. and El Filali, S.}
}
@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.}
}
@conference {Fellir2020377,
	title = {A multi-Agent based model for task scheduling in cloud-fog computing platform},
	booktitle = {2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020},
	year = {2020},
	note = {cited By 9},
	pages = {377-382},
	abstract = {The Internet-of-Things (IoT) is a network of physical objects that communicate and exchange data between them over the Internet. These objects, or things, generate a massive amount of data that require powerful analytics approaches and data storage platforms - this is where cloud computing may well come into play. The classic cloud computing paradigm, however, faces several serious issues, due to centralization, such as low performance, latency issues, security issues, bandwidth obstacle, etc.. The Fog (Edge) computing paradigm has been proposed to improve the performance and to address other weaknesses, by providing IoT data processing and storage capabilities locally at the edges (IoT devices), instead of sending all the data to the centralized cloud. Whether in cloud or in fog computing, with billions of devices and a huge number of simultaneous requests, managing limited resources becomes essential. One of the important steps in resource management is task scheduling. In this paper, we consider task scheduling in a cloud-fog computing platform, we propose a multi-agent based model that aims at serving the most important task first, taking into consideration the task priority, its wait time, its status and the resources required to complete it successfully. Furthermore, in the scheduling process, we first propose an update to the priority value of the task, while taking into consideration its dependencies to other tasks and their priorities. Simulation results show that our proposed model can lead to better resource utilization and improve performance. {\textcopyright} 2020 IEEE.},
	keywords = {Autonomous agents, Computational methods, Computing paradigm, Computing platform, Data handling, Digital storage, Fog, Fog computing, Improve performance, Internet of thing (IOT), Internet of things, Multi agent systems, Multi-agent based modeling, Multitasking, Resource Management, Resource utilizations, Scheduling, Scheduling algorithms, Simulation platform, Storage capability},
	doi = {10.1109/ICIoT48696.2020.9089625},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085496418\&doi=10.1109\%2fICIoT48696.2020.9089625\&partnerID=40\&md5=4ee0e2ab76422fc76603ec3b6f6942cb},
	author = {Fellir, F. and El Attar, A. and Nafil, K. and Chung, L.}
}
@article {ElMahdi2020,
	title = {Optimized Scheme to Secure IoT Systems Based on Sharing Secret in Multipath Protocol},
	journal = {Wireless Communications and Mobile Computing},
	volume = {2020},
	year = {2020},
	note = {cited By 1},
	abstract = {Internet of Things (IoT) is a hot and emerging topic nowadays. In the world of today, all kinds of devices are supposed to be connected and all types of information are exchanged. This makes human daily life easier and much more intelligent than before. However, this life mode is vulnerable to several security threats. In fact, the mobile networks, by nature, are more exposed to malicious attacks that may read confidential information and modify or even drop important data. This risk should be taken in consideration prior to any construction of mobile networks especially in the coming 5G technology. The present paper aims to provide a contribution in securing such kinds of environment by proposing a new protocol that can be implemented in ad hoc networks. {\textcopyright} 2020 Fatna El Mahdi et al.},
	keywords = {5G mobile communication systems, ad hoc networks, Confidential information, Daily lives, Emerging topics, Internet of things, Internet of Things (IOT), Malicious attack, Mobile security, Mobile telecommunication systems, Multipath protocols, Network security, New protocol, Security threats},
	doi = {10.1155/2020/1468976},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083513010\&doi=10.1155\%2f2020\%2f1468976\&partnerID=40\&md5=a7326029a67a6d4fc68c90a958148708},
	author = {El Mahdi, F. and Habbani, A. and Kartit, Z. and Bouamoud, B.}
}
@article {Elkhoukhi2020,
	title = {A platform architecture for occupancy detection using stream processing and machine learning approaches},
	journal = {Concurrency and Computation: Practice and Experience},
	volume = {32},
	number = {17},
	year = {2020},
	note = {cited By 15},
	abstract = {Context-awareness in energy-efficient buildings has been considered as a crucial fact for developing context-driven control approaches in which sensing and actuation tasks are performed according to the contextual changes. This could be done by including the presence of occupants, number, actions, and behaviors in up-to-date context, taking into account the complex interlinked elements, situations, processes, and their dynamics. However, many studies have shown that occupancy information is a major leading source of uncertainty when developing control approaches. Comprehensive and real-time fine-grained occupancy information has to be, therefore, integrated in order to improve the performance of occupancy-driven control approaches. The work presented in this paper is toward the development of a holistic platform that combines recent IoT and Big Data technologies for real-time occupancy detection in smart building. The purpose of this work focuses mainly on the presence of occupants by comparing both static and dynamic machine learning techniques. An open-access occupancy detection dataset was first used to assess the usefulness of the platform and the effectiveness of static machine learning strategies for data processing. This dataset is used for applications that follow the strategy aiming at storing data first and processing it later. However, many smart buildings{\textquoteright} applications, such as HVAC and ventilation control, require online data streams processing. Therefore, a distributed real-time machine learning framework was integrated into the platform and tested to show its effectiveness for this kind of applications. Experiments have been conducted for ventilation systems in energy-efficient building laboratory (EEBLab) and preliminary results show the effectiveness of this platform in detecting on-the-fly presence of occupants, which is required to either make ON or OFF the system and then activate the corresponding embedded control technique (eg, ON/OFF, PID, state-feedback). {\textcopyright} 2019 John Wiley \& Sons, Ltd.},
	keywords = {Context- awareness, Data streams, Embedded systems, energy efficiency, Energy efficient building, Intelligent buildings, Internet of things, Learning systems, Machine learning, Machine learning approaches, Machine learning techniques, Occupancy detections, Platform architecture, Real-time data processing, State feedback, Ventilation, Ventilation control},
	doi = {10.1002/cpe.5651},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076920865\&doi=10.1002\%2fcpe.5651\&partnerID=40\&md5=f34bbe0cd8dadd04282227e1a5698c57},
	author = {Elkhoukhi, H. and NaitMalek, Y. and Bakhouya, M. and Berouine, A. and Kharbouch, A. and Lachhab, F. and Hanifi, M. and El Ouadghiri, D. and Essaaidi, M.}
}
@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 {Mouchfiq2020219,
	title = {Security in MANETs: The Blockchain Issue},
	journal = {Communications in Computer and Information Science},
	volume = {1264},
	year = {2020},
	note = {cited By 2},
	pages = {219-232},
	abstract = {With the emergence of the IoT (Internet of Things) technology, security features must take into account the developments and possible uses. The blockchain is considered as a new technology devoted to data sharing, it allows to guarantee the integrity of data by IoT devices thanks to intelligent contracts allowing to verify and enforce the conditions of the monitored goods during their processing. In our work, we will address the security of Blockchain-based systems and networks to improve and simplify the communication of messages and informations, using the most innovative and sophisticated processes and a form of device independent control. In order to do so, we will analyse the solutions advanced by researchers from all over the world who are dedicated to guaranteeing a good state of security on these networks. Finally, our manuscript will present an approach to enhance security which is founded on the Blockchain principle and which we have entitled {\textquotedblleft}MPR Blockchain{\textquotedblright}. This solution proves to be the most appropriate to our requirements and expectations as a team working within IoT systems and especially ad hoc networks. {\textcopyright} 2020, Springer Nature Switzerland AG.},
	keywords = {Blockchain, Data communication systems, Data Sharing, Independent control, Internet of things, Mobile ad hoc networks, Mobile security, Network security, Security features, Team working},
	doi = {10.1007/978-3-030-61143-9_18},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097368928\&doi=10.1007\%2f978-3-030-61143-9_18\&partnerID=40\&md5=d277597a52117999b5b738db40aa811f},
	author = {Mouchfiq, N. and Benjbara, C. and Habbani, A.}
}
@conference {Brihi2020,
	title = {UAV for IoT Communications: Beam Selection Using Matching Game and Network Slicing},
	booktitle = {Proceedings - 2020 International Conference on Wireless Networks and Mobile Communications, WINCOM 2020},
	year = {2020},
	note = {cited By 0},
	abstract = {In cellular communication networks, researchers are trying to improve network communication and adapt it to meet the requirements of new technologies such as the Internet of Things. The next generation of wireless networks (5G) promises new network features such as low latency, peripheral computing and radio convergence that will pave the way for a world that is ubiquitously connected. In this context and for the provision of the necessary high-quality services and connection, continuously and everywhere, even under poor network conditions, any network failures must be managed quickly and efficiently. Covering the network in remote areas, providing services in overcrowded areas, or safeguarding the network in the event of damage to the cellular infrastructure (for example, a physical disaster) are a number of challenges. In this paper we discuss the architecture and possible applications of flight modes as a part of a 5G network supporting network splitting and lightweight virtualization at the extent of relay Unmanned Aerial Vehicles (UAVs) as being small cells. It also provides 5G aerial measurement results to support the feasibility check of UAV use in two possible scenarios, namely improving the position of UAVs relative to the position and circulation of users (UEs) additionally because the increased network coverage through algorithms supported theory of games. {\textcopyright} 2020 IEEE.},
	keywords = {5G mobile communication systems, Antennas, Beam selection, Cellular communication networks, Communication beams, Computation theory, Flying relay unmanned aerial vehicle, Game theory, Internet of things, Matching game, Matching networks, Network communications, Network features, Network function virtualization, Network slicing, SDN, Unmanned aerial vehicles (UAV)},
	doi = {10.1109/WINCOM50532.2020.9272510},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098730582\&doi=10.1109\%2fWINCOM50532.2020.9272510\&partnerID=40\&md5=2fd59efd80efa8be8e20ec7601c73dc9},
	author = {Brihi, S. and Ghamizi, A. and Chakri, K.}
}
@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.}
}
@article {12119042120160101,
	title = {Internet of Things Security: Layered classification of attacks and possible Countermeasures.},
	journal = {E-Ti: E-Review in Technologies Information},
	number = {9},
	year = {2016},
	pages = {66 - 80},
	abstract = {Internet of Things is undoubtedly a well-known research area. In fact, ensuring security of data exchange is among the great challenges of the Internet of things. In this paper, we endeavour to introduce a new classification of attacks in compliance with the OSI layers and the objective of security that we seek to attained in order to develop novel techniques and processes to fight against these attacks. (English) [ABSTRACT FROM AUTHOR]},
	keywords = {Attacks, Attaques, Computer network security, Contre-mesures, Countermeasures, Embedded Internet devices, Internet des Objets, Internet of things, RFID, S{\'e}curit{\'e}, Security, WSN},
	issn = {11148802},
	url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=121190421\&site=ehost-live},
	author = {mouaatamid, Otmane E. l. and Lahmer, Mohammed and Belkasmi, Mostafa}
}
