Zhang Qingguo, Fok Mable P
College of Computer, Huazhong Normal University, Wuhan 430079, China.
Lightwave and Microwave Photonics Laboratory, College of Engineering, University of Georgia, Athens, GA 30602, USA.
Sensors (Basel). 2017 Jan 9;17(1):117. doi: 10.3390/s17010117.
Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate's target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate's target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors, when compare with other approaches.
提供区域覆盖是许多传感器网络应用中的一项关键任务。在某些场景中,由于传感器的随机初始部署,传感器区域可能存在覆盖漏洞;因此,无法实现所需的覆盖水平。混合无线传感器网络是解决此问题的一种经济高效的解决方案,它通过重新定位网络中的一部分移动传感器来满足网络覆盖要求。本文研究如何重新部署移动传感器节点以提高混合无线传感器网络的网络覆盖。我们提出了一种用于混合无线传感器网络的两阶段覆盖增强算法。在第一阶段,我们使用差分进化算法来计算移动传感器节点中可能潜在提高覆盖的候选目标位置。在第二阶段,我们对从第一阶段计算出的候选目标位置使用一种优化方案,以减少移动传感器的累积潜在移动距离,从而可以确定需要移动的具体移动传感器节点及其最终目标位置。实验结果表明,与其他方法相比,所提出的算法在区域覆盖率、平均移动距离、区域覆盖 - 距离率以及移动的移动传感器数量方面有显著改进。