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Cost Efficient Deployment and Reliable Routing Modeling Based Multi-Objective Optimization for Dynamic Wireless Body Sensor Networks Topology
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Author(s): Hassine Moungla (University of Paris Descartes, Paris, France), Nora Touati (Ecole Spéciale de Mécanique et d'Electricité-Sudria, Paris, France)and Ahmed Mehaoua (University of Paris Descartes, Paris, France)
Copyright: 2013
Volume: 4
Issue: 4
Pages: 18
Source title:
International Journal of E-Health and Medical Communications (IJEHMC)
Editor(s)-in-Chief: Joel J.P.C. Rodrigues (Senac Faculty of Ceará, Fortaleza-CE, Brazil; Instituto de Telecomunicações, Portugal)
DOI: 10.4018/ijehmc.2013100102
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Abstract
Wireless Body Sensor Networks (WBSNs), like any other sensor networks, suffer from limited energy and are highly distributed network, where its nodes organize by themselves and each of them has the flexibility of collecting and transmitting patient biomedical information to a sink. When a knowledge was sent to a sink from a path that doesn't have a definite basis, the routing is a crucial challenge in Wireless Body Area Sensor Networks. Furthermore, reliability and routing delay are the considerable factors in these types of networks. More attention should be given to the energy routing issue and frequent topology's change in WBSNs. That increases the dynamics of network topology, and complicates the relay selection process in cooperative communications. Unreliable communication over the wireless channel complicates communication protocols and results in low data yield (Stathopoulos 2005). The deployment sensors step is a crucial and complex task due to several independent objectives and constraints. This paper presents a Min-Max multi-commodity flow model for WBSNs which allows preventing sensor node saturation and taking best action against reliability and the path loss, by imposing an equilibrium use of sensors during the routing process. This model is based on the authors' optimal sensors deployment method for WBSNs. Simulations results show that the algorithm balances the energy consumption of nodes effectively and maximize the network lifetime. It will meet the enhanced WBSNs requirements, including better delivery ratio, less reliable routing overhead.
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