Joint topology optimization, power control and spectrum allocation for intra-vehicular multi-hop sensor networks using dandelion-encoded heuristics
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2016
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Springer Verlag
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Abstract
In the last years the interest in multi-hop communications has gained momentum within the research community due to the challenging characteristics of the intra-vehicular radio environment and the stringent robustness imposed on critical sensors within the vehicle. As opposed to point-to-point network topologies, multi-hop networking allows for an enhanced communication reliability at the cost of an additional processing overhead. In this context this manuscript poses a novel bi-objective optimization problem aimed at jointly minimizing (1) the average Bit Error Rate (BER) of sensing nodes under a majority fusion rule at the central data collection unit; and (2) the mean delay experienced by packets forwarded by such nodes due to multi-hop networking, frequency channel switching time multiplexing at intermediate nodes. The formulated paradigm is shown to be computationally tractable via a combination of evolutionary meta-heuristic algorithms and Dandelion codes, the latter capable of representing tree-like structures like those modeling the multi-hop routing approach. Simulations are carried out for realistic values of intra-vehicular radio channels and co-channel interference due to nearby IEEE 802.11 signals. The obtained results are promising and pave the way towards assessing the practical performance of the proposed scheme in real setups.
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Publisher Copyright: © Springer International Publishing Switzerland 2016.
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Del Ser , J , Bilbao , M N , Perfecto , C , Gonzalez-Pardo , A & Campos-Cordobes , S 2016 , Joint topology optimization, power control and spectrum allocation for intra-vehicular multi-hop sensor networks using dandelion-encoded heuristics . in P Burelli & G Squillero (eds) , Applications of Evolutionary Computation - 19th European Conference, EvoApplications 2016, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 9597 , Springer Verlag , pp. 235-250 , 19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016 , Porto , Portugal , 30/03/16 . https://doi.org/10.1007/978-3-319-31204-0_16
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