A Global Best Path Meteorological Data Gathering Algorithm for Wireless Sensor Networks

نویسندگان

  • Yinghui Peng
  • Bo Tang
  • Yuan Xin
  • Jin Wang
  • Jeong-Uk Kim
چکیده

Sink mobility has been viewed as an important technique to improve network performance for wireless sensor networks (WSNs) such as energy consumption and balancing, network lifetime, throughput, end-to-end delay etc. Also, it can largely mitigate the hot spots near sink node as sink node moves randomly or autonomously. In many applications of WSNs, sensors are deployed in areas accessed by laid roads and sinks can be assembled on mobile devices like bus or handcart. In this paper, we propose a Global Best Path (GBP) data gathering algorithm based on wireless Sensor Networks with single Mobile Sink (GBP-MSSN). It aims at determining the best position for the single mobile sink and further using global sensors information to generate the best scheme to gather data from specified node. Generating of best scheme is conducted by GBP algorithm which can balance energy consumption among whole sensor networks and further prolong the network lifetime. Simulation results show that our GBP-MSSN algorithm outperforms conventional algorithms like LEACH, GAF, etc.

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تاریخ انتشار 2014