Multi-constrained QoS Routing and Energy Optimization for Wireless Sensor Networks

Abstract : In this thesis, we focus on routing protocols for Wireless Sensor Networks (WSNs). The main research problems in the domain of routing data packets in a multi-hop network are the optimisation of the energy and the routing under multi-criteria QoS constraints (e.g., energy, reliability, delay, …). To address these problems, this dissertation proposes two contributions. Firstly, an optimal probabilistic routing protocol which balances the usage of energy and secondly, a routing protocol which is able to simultaneously take into account multiple QoS metrics. In fact, for balancing the energy consumption between the multiple existing links, the existing probabilistic routing protocols assign a probability to each link, either in an empirical way or depending on proportional energy level of the path. We did not know what are the optimal probabilities which lead to the optimal network lifetime. Our first contribution proposes optimal probabilities by modeling and solving a linear programming problem. As for the multi-constrainted QoS routing problem, multiple metrics are defined by RPL (a standard of IETF) but the existing protocols chose paths either according to only one metric or using a single aggregated function with multiple metrics, but never all the metrics simultaneously. In this dissertation, we first evaluate the performance of the operator calculus algebra introduced by R. Schott and S. Staples which defines an efficient algorithm allowing to find all the paths which satisfy the multiple constraints in a graph, and secondly we proposed a distributed version of this algorithm based on which a routing protocol has been designed. Both contributions are implemented in Contiki environment and simulated/emulated under Cooja (a software designed for simulating protocols of WSNs)
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Evangelia Tsiontsiou. Multi-constrained QoS Routing and Energy Optimization for Wireless Sensor Networks. Networking and Internet Architecture [cs.NI]. Université de Lorraine, 2017. English. ⟨NNT : 2017LORR0340⟩. ⟨tel-01735239⟩

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