异构传感器网络多目标多重覆盖策略  

Multi-objective Strategy of Multiple Coverage in Heterogeneous Sensor Networks

作　　者：罗旭[1] 柴利[1] 杨君[1] 

机构地区：[1]武汉科技大学冶金自动化与检测技术教育部工程研究中心,武汉430081

出　　处：《电子与信息学报》2014年第3期690-695,共6页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(60974012;61171160)资助课题

摘　　要：在传感器网络环境监测应用中,常存在多种监测对象。此类应用中,每个异构网络节点搭配不同类型的传感器,要求网络部署可多重覆盖监测区以监测各个子对象。针对节点随机分布的传感器网络,该文提出一种平均子网寿命模型以评价网络中某子对象的监测寿命。在给定成本预算与各子对象的基本覆盖率需求下,采用一种基于整数向量规划的多目标多重覆盖算法权衡成本、网络覆盖性能以及网络中不同子对象的监测寿命。该算法分两部分,首先确定监测不同子对象的传感器数量,然后基于平均子网寿命模型,确定不同类型的异构节点数量。针对向量规划问题,文中给出两种不同次优解法。在仿真实验部分,将不同次优解法进行了对比,并分析了算法计算复杂度。仿真示例验证了该文的覆盖算法在多对象监测应用中的有效性。In environmental monitoring applications, there are often various objects to be monitored by sensor networks. In this scenario, each heterogeneous node carries some different sensors, and the coverage of multiple areas is required in order to monitor every different subobject. In sensor networks with random distributed nodes, an average subnet lifetime model is proposed to evaluate the average lifetime of nodes sensing one subobject. Given the constraints of cost budget and area coverage of different objects, a multi-objective multi-coverage algorithm based on integer vector programming is proposed to balance the cost and coverage performance, as well as the monitoring life of different subobjects. The algorithm is divided into two steps. The first step is to compute the number of each type of sensors used to monitor one subobject, and the second step is to determine the number of different kinds of heterogeneous nodes based on the average subnet life model. To solve the proposed vector programming issues, two suboptimal methods are given. In the simulation experiments, different suboptimal methods are compared, and the computational complexity of the proposed algorithm is analysed. Simulation examples verify the effectiveness of the proposed algorithm in the multi-objects monitoring applications.

关 键 词：传感器网络 多对象监测 平均子网寿命 向量规划 异构节点 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]