@conference { ISI:000367072600061,
	title = {Modeling and Enforcing Security and Service Control Policies using FlexRFID Middleware Healthcare Scenarios},
	booktitle = {2014 SCIENCE AND INFORMATION CONFERENCE (SAI)},
	year = {2014},
	note = {Science and Information Conference (SAI), Sci \& Informat Org, London, ENGLAND, AUG 27-29, 2014},
	pages = {461-467},
	publisher = {Microsoft; RK Trans2Cloud; Springer; IEEE Comp Soc, UKRI Sect; IEEE Computat Intelligence Soc, UKRI Sect; IEEE},
	organization = {Microsoft; RK Trans2Cloud; Springer; IEEE Comp Soc, UKRI Sect; IEEE Computat Intelligence Soc, UKRI Sect; IEEE},
	abstract = {RFID and WSN technologies are widely used in today{\textquoteright}s pervasive computing. In Wireless Sensor Networks, sensor nodes sense the physical environment and send the sensed data to the sink by multi-hops. WSN are used in many applications such as military and environment monitoring. In Radio Frequency Identification, a unique ID is assigned to a RFID tag which is associated with a real world object. RFID applications cover many areas such as Supply Chain Management (SCM), healthcare, library management, automatic toll collection, etc. The integration of both technologies will bring many advantages in the future of ubiquitous computing, through the provision of real-world tracking and context information about the objects. This will increase considerably the automation of an information system. In order to process the large volume of data captured by sensors and RFID readers in real time, a middleware solution is needed. This middleware should be designed in a way to allow the aggregation, filtering and grouping of the data captured by the hardware devices before sending them to the backend applications. In this paper we demonstrate how our middleware solution called FlexRFID handles large amount of RFID and sensor scan data, and executes applications{\textquoteright} business rules in real time through its policy-based Business Rules layer. The FlexRFID middleware provides easy addition and removal of hardware devices that capture data, as well as uses the business rules of the applications to control all its services. We demonstrate how the middleware controls some defined healthcare scenarios, and deals with the access control security concern to sensitive healthcare data through the use of policies.},
	isbn = {978-0-9893193-1-7},
	author = {El Khaddar, Mehdia Ajana and Chraibi, Mhammed and Harroud, Hamid and Boulmalf, Mohammed and Elkoutbi, Mohammed and Maach, Abdelilah}
}
@conference { ISI:000346142800015,
	title = {Modeling and Evaluating a Cloudlet-based Architecture for Mobile Cloud Computing},
	booktitle = {2014 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA{\textquoteright}14)},
	year = {2014},
	note = {9th International Conference on Intelligent Systems - Theories and Applications (SITA), Inst Natl Postes \& Telecommunicat, Rabat, MOROCCO, MAY 07-08, 2014},
	publisher = {IEEE; IEEE Morocco},
	organization = {IEEE; IEEE Morocco},
	abstract = {With the rising popularity of Internet-enabled mobile devices, users are increasingly demanding better quality of service (QoS). However, the resources of these devices and their connectivity levels remain insufficient, even though they are improving, for offering acceptable levels of QoS to users. Cloud computing infrastructures offer large and scalable resources that allow shifting the physical location of computation and storage to the cloud. Nevertheless, the integration of mobile computing with cloud computing would not guarantee adequate levels of service for mobile users. It rather delivers scalability at the cost of higher delay and higher power consumption on the mobile device. Instead, using local resources based on users geographical locations has the potential to improve the performance and QoS for mobile users. In this paper, we present and study a centralized architecture that relies on the concept of local clouds, cloudlets, to leverage the geographical proximity of resources to mobile users and offer them a better user experience. We use a continuous time Markov-chain (CTMC) to model the different nodes of the architecture: user nodes, cloudlets, and the main cloud. We estimate the delay incurred in the proposed architecture by simulating search engine queries generated by mobile users using the CTMC state models. Initial simulation results show that the usage of a cloudlet-based architecture especially centralized architecture has an efficient gains in terms of latency delay and synchronisation mechanisms.},
	isbn = {978-1-4799-3566-6},
	author = {Routaib, Hayat and Elmachkour, Mouna and Sabir, Essaid and Badidi, Elarbi and Elkoutbi, Mohammed}
}
