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Adaptive Mobile Sink for Energy Efficient WSN Using Biogeography-Based Optimization

Adaptive Mobile Sink for Energy Efficient WSN Using Biogeography-Based Optimization

Ajay Kaushik, S. Indu, Daya Gupta
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 22
ISSN: 1937-9412|EISSN: 1937-9404|EISBN13: 9781522564843|DOI: 10.4018/IJMCMC.2019070101
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MLA

Kaushik, Ajay, et al. "Adaptive Mobile Sink for Energy Efficient WSN Using Biogeography-Based Optimization." IJMCMC vol.10, no.3 2019: pp.1-22. http://doi.org/10.4018/IJMCMC.2019070101

APA

Kaushik, A., Indu, S., & Gupta, D. (2019). Adaptive Mobile Sink for Energy Efficient WSN Using Biogeography-Based Optimization. International Journal of Mobile Computing and Multimedia Communications (IJMCMC), 10(3), 1-22. http://doi.org/10.4018/IJMCMC.2019070101

Chicago

Kaushik, Ajay, S. Indu, and Daya Gupta. "Adaptive Mobile Sink for Energy Efficient WSN Using Biogeography-Based Optimization," International Journal of Mobile Computing and Multimedia Communications (IJMCMC) 10, no.3: 1-22. http://doi.org/10.4018/IJMCMC.2019070101

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Abstract

Early death of cluster heads (CHs) located near the sink due to excessive data relay load causes energy holes in wireless sensor networks (WSNs). A widely adopted solution to energy hole problem is to divide the deployment region into multiple sub regions and use mobile sink (MS) to aggregate data from each sub-region. However, inside a sub-region, CHs close to MS dissipate their energy quickly and die despite of the sink mobility. The authors map the problem of distributing data relay load optimally to multiple CHs and locating MS near these multiple CHs using metaheuristic algorithm biogeography-based optimization (BBO). Furthermore, there is a need of optimum routing of data to the MS inside each sub-region of a MS WSN. Proposed mobile sink distributed load routing algorithm (MSDR-BBO) selects the optimum routing CHs in MS WSN as per data transfer requirements of sensor nodes (SNs) and CHs. MSDR-BBO is validated using Matlab simulation as well as Netsim emulator, and it outperforms latest MS WSN algorithms like nested routing, SENMA, and CMS2TO by 4.6%, 11.7%, and 17.4%, respectively.

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