大数据环境下传感器网络节点覆盖优化研究

Research on Coverage Optimization of Sensor Network Node in Large Data Environment

针对无线传感器网络具有规模大、节点计算能力有限等特点,为提高无线传感器节点的覆盖率,提出一种大数据环境下的传感器网络节点覆盖优化算法。首先将整个无线传感器网络监控区域划分多个子区域,每一子区域采用人工鱼群算法对传感器网络节点覆盖优化问题求解,然后利用Map/Reduce机制对优化结果进行融合,最后采用具体传感器网络节点覆盖实验对性能进行分析,结果表明,本文算法可以有效确保节点对整个监控区域的覆盖,提高了传感器网络节点覆盖率,而且可以保证整个网络的能量更加均衡。

Wireless sensor networks have large scale, the calculating ability of node is limited, and a new sensor network node coverage optimization algorithm in large data environment is proposed to improve the coverage rate of wireless sensor nodes. Firstly, the wireless sensor network monitoring area is divided into several sub regions, artificial fish swarm algorithm is used to solve the optimization problem of sensor network coverage nodes by each sub region, and then Map/Reduce mechanism is used to fuse the optimization results, at last, the performance is analyzed by using specific sensor network node covering experimental, The results show that the proposed algorithm can effectively ensure coverage of the entire monitoring area, improve the coverage rate of the sensor network nodes, and ensure energy balance of whole network.