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Flow based efficient data gathering in wireless sensor network using path-constrained mobile sink

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Abstract

In wireless sensor networks (WSNs), sensors are equipped with limited power batteries. Data collection from sensors is one of the fundamental tasks in WSNs. Maximizing the data collection with minimum energy consumption is one of the major challenging issues in WSNs. In this article, we consider data collection using a mobile sink, where the mobile sink efficiently collects data from nearby sensors while moving along a pre-specified path with constant speed. We refer this problem as a Maximizing Data Gathering with Minimum Energy Consumption (MDGMEC) problem. So far, existing works have heuristic algorithms for MDGMEC problem. Their solutions, being heuristic, could not ensure the optimality. In this article, we propose two efficient algorithms to improve the data gathering process. Our algorithms use network flow approach for efficient data forwarding. In the first proposed algorithm, the mobile sink can receive data from multiple nearby sensors simultaneously, while in the second, the mobile sink can receive data from only one nearby sensor at a time. The proposed algorithms run in polynomial time and are also scalable for large networks. We evaluate the proposed algorithms by implementing them in MATLAB. The obtained results show that our proposed schemes outperform other existing schemes in terms of collecting total data and energy efficiency.

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Acknowledgements

This work is supported by the Science & Engineering Research Board, DST, Govt. of India [Grant numbers: ECR/2016/001035].

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  1. Department of Computer Science and Engineering, National Institute of Technology Patna, Bihar, 800005, India

    Naween Kumar & Dinesh Dash

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  1. Naween Kumar
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  2. Dinesh Dash
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Correspondence to Naween Kumar.

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Kumar, N., Dash, D. Flow based efficient data gathering in wireless sensor network using path-constrained mobile sink. J Ambient Intell Human Comput 11, 1163–1175 (2020). https://doi.org/10.1007/s12652-019-01245-x

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