Abstract
Wireless sensor networks based on mobile sink (MS) can significantly alleviate the problem of network congestion and energy hole, but it results in large delay because of restriction of moving speed and lead to the loss of data due to the limited communication time. In this paper, a grid-based efficient scheduling and data gathering scheme (GES-DGS) is proposed for maximizing the amount of data collected and reducing energy consumption simultaneously within the delay of network tolerance. The main challenges of our scheme are how to optimize the trajectory and the sojourn times of MS and how to deliver the sensed data to MS in an energy-efficient way. To deal with the above problems, we first divide the monitoring field into multiple grids and construct the hop gradient of each grid. Second, we design a heuristic rendezvous point selection strategy to determine the trajectory of MS and devise a routing protocol based on hops and energy. With extensive simulation, we demonstrate that GES-DGS scheme not only significantly extends network lifespan compared with MS-based data gathering schemes, but also pro-actively adapts to the changes in delay in specific applications.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61170232 and 81160183, Australian Research Council Discovery Project under Grant DP150104871 and the Fundamental Research Funds for the New Teachers’ Scientific Research Fund of People’s Public Security University of China under its projects number 2018JKF609.
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Chen, Z., Shen, H., Zhao, X., Wang, T. (2019). Efficient Scheduling Strategy for Data Collection in Delay-Tolerant Wireless Sensor Networks with a Mobile Sink. In: Park, J., Shen, H., Sung, Y., Tian, H. (eds) Parallel and Distributed Computing, Applications and Technologies. PDCAT 2018. Communications in Computer and Information Science, vol 931. Springer, Singapore. https://doi.org/10.1007/978-981-13-5907-1_2
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DOI: https://doi.org/10.1007/978-981-13-5907-1_2
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