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Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks

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Abstract

In wireless sensor networks (WSNs), sensor nodes near static sink will have more traffic load to forward and the network lifetime will get largely reduced. This problem is referred to as the hotspot problem. Recently, adopting sink mobility has been considered as a good strategy to overcome the hotspot problem. Despite its many advantages, due to the dynamic network topology caused by sink mobility, data transmission to the mobile sink is a challenging task. To achieve efficient data dissemination, nodes need to reconstruct their routes toward the latest location of the mobile sink, which weakens the energy conservation aim. In this paper, we proposed an energy-efficient cluster-based dynamic routes adjustment approach (EECDRA) which aims to minimize the routes reconstruction cost of the sensor nodes while maintaining nearly optimal routes to the latest location of the mobile sinks. The network is divided into several equal clusters and cluster heads are selected within each cluster. We also set some communication rules that manage routes reconstruction process accordingly requiring only a limited number of nodes to readjust their data delivery routes toward the mobile sinks. Simulation results show that the mobile sinks for reducing reconstruction of route have improved the energy efficiency and prolonged lifetime of wireless sensor network.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61402234, 61672290) and Ministry of Science, ICT and Future Planning (KR) (IITP-2016-H8501-16-1014). Prof. Jong Hyuk Park is the corresponding author.

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Correspondence to Jong Hyuk Park.

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Wang, J., Cao, J., Ji, S. et al. Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. J Supercomput 73, 3277–3290 (2017). https://doi.org/10.1007/s11227-016-1947-9

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  • DOI: https://doi.org/10.1007/s11227-016-1947-9

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