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Author: search.filters.author.Bouabdallah, AbdelmadjidSubject: search.filters.subject.End-to-End Delay

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    Efficient QoS-aware Heterogeneous Architecture for Energy-Delay Constrained Connected Objects
    (IFIP, 2016-07-11) Doudou, Messaoud; Rault, Tifenn; Bouabdallah, Abdelmadjid
    Connected objects such as smart phones and wireless sensors becomes very attractive for our assisted daily life applications, because it offers continuous monitoring capability of both personal and environmental parameters. However, these systems still face a major energy issue that prevent their wide adoption. Indeed, continuous sampling and communication tasks quickly deplete sensors and gateways battery reserves, and frequent battery replacement are not convenient. One solution to address such a challenge consists in minimizing the activation of radio interfaces and switching between them in order to achieve very low duty-cycle. In this paper, we propose a new efficient communication architecture for patient supervision in the context of healthcare application making use of dual radio. At runtime, our solution determines the optimal interval parameters of switching on/off each radio interfaces in order to minimize the energy consumption of both sensors and mobile phones while satisfying the QoS requirements. The proposed solution is adequately analyzed and numerically compared against a solution without QoS. The results show that our proposed architecture exhibits better duty-cycle reduction while satisfying the delay constraints.
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    Game Theory Framework for MAC Parameter Optimization in Energy-Delay Constrained Sensor Networks
    (ACM, 2016-05-15) Doudou, Messaoud; M. Barcelo-Ordinas, Jose; Djenouri, Djamel; Garcia-Vidal, Jorge; Bouabdallah, Abdelmadjid; Badache, Nadjib
    Optimizing energy consumption and end-to-end (e2e) packet delay in energy-constrained, delay-sensitive wireless sensor networks is a conflicting multi-objective optimization problem. We investigate the problem from a game theory perspective, where the two optimization objectives are considered as game players. The cost model of each player is mapped through a generalized optimization framework onto protocol specific MAC parameters. From the optimization framework, a game is first defined by the Nash Bargaining Solution (NBS) to assure energy-consumption and e2e delay balancing. Secondly, the Kalai-Smorodinsky Bargaining Solution (KSBS) is used to find equal proportion of gain between players. Both methods offer a bargaining solution to the duty-cycle MAC protocol under different axioms. As a result, given the two performance requirements, i.e., the maximum latency tolerated by the application and the initial energy budget of nodes, the proposed framework allows to set tunable system parameters to reach a fair equilibrium point which dually minimizes the system latency and energy consumption. For illustration, this formulation is applied to six state-of-the-art Wireless Sensor Network (WSN) MAC protocols; B-MAC, X-MAC, RI-MAC, SMAC, DMAC, and LMAC. The paper shows the effectiveness and scalability of such framework in optimizing protocol parameters that achieve a fair energy-delay performance trade-off under the application requirements.