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An artificial bee colony algorithm for data collection path planning in sparse wireless sensor networks

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Abstract

In sparse wireless sensor networks, a mobile robot is usually exploited to collect the sensing data. Each sensor has a limited transmission range and the mobile robot must get into the coverage of each sensor node to obtain the sensing data. To minimize the energy consumption on the traveling of the mobile robot, it is significant to plan a data collection path with the minimum length to complete the data collection task. In this paper, we observe that this problem can be formulated as traveling salesman problem with neighborhoods, which is known to be NP-hard. To address this problem, we apply the concept of artificial bee colony (ABC) and design an ABC-based path planning algorithm. Simulation results validate the correctness and high efficiency of our proposal.

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Authors and Affiliations

  1. School of Computer Science and Engineering, The University of Aizu, Aizu-wakamatsu, Japan

    Wei-Lun Chang, Deze Zeng & Song Guo

  2. Department of Information Management, Choayang University of Technology, Taichung, Taiwan

    Wei-Lun Chang & Rung-Ching Chen

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  1. Wei-Lun Chang
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  2. Deze Zeng
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  3. Rung-Ching Chen
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  4. Song Guo
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Correspondence to Song Guo.

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Chang, WL., Zeng, D., Chen, RC. et al. An artificial bee colony algorithm for data collection path planning in sparse wireless sensor networks. Int. J. Mach. Learn. & Cyber. 6, 375–383 (2015). https://doi.org/10.1007/s13042-013-0195-z

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  • DOI: https://doi.org/10.1007/s13042-013-0195-z

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