Spread and shrink: Point of interest discovery and coverage with mobile wireless sensors

Abstract : In this paper we tackle the problem of deploying mobile wireless sensors while maintaining connectivity with a sink throughout the deployment process. These mobile sensors should discover some points of interest (PoI) in an autonomous way and continuously report information from the observed events to the sink. Unlike previous works, we design an algorithm that uses only local information and local interactions with surrounding sensors. Moreover, unlike other approaches, our algorithm implements both the discovery and the coverage phase. In the discovery phase, the mobile sensors spread to discover new events all over the field and in the second phase, they shrink to concentrate only on the discovered events, named points of interest. We prove that connectivity is preserved during both phases and the spreading phase is terminated in a reasonable amount of time. Real experiments are conducted for small-scale scenarios that are used as a “proof of concept”, while extensive simulations are performed for more complex scenarios to evaluate the algorithm performance. A comparison with an existing work which uses virtual forces has been made as well. The results show the capability of our algorithm to scale fast in both discovery, coverage and shrinking phases.
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Tahiry Razafindralambo, Milan Erdelj, Dimitrios Zorbas, Enrico Natalizio. Spread and shrink: Point of interest discovery and coverage with mobile wireless sensors. Journal of Parallel and Distributed Computing, Elsevier, 2017, 102, pp.16-27. ⟨10.1016/j.jpdc.2016.09.003⟩. ⟨hal-01406492⟩

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