WSN中基于线性规划的多类别目标覆盖算法

多类别目标覆盖问题是目前无线传感器网络中的研究热点。针对现有目标覆盖算法在时间效率、网络生命周期等方面的不足,将多类别目标覆盖问题建模为基于线性规划的网络生命周期最大化问题,提出一种基于分簇的目标覆盖算法。该算法依据节点的剩余能量和感应能力,在每个簇结构内求解最优覆盖集的基础上得到接近于最优解的全局覆盖集,进而调度节点相应的感应模块去覆盖其感知范围内同属性的目标。实验结果表明,该算法是有效的,在网络生命周期和时间效率等方面均优于CWGC方案,接近于线性规划最优值。

Multi-class Target Coverage Algorithm Based on Linear Programming in Wireless Sensor Networks

The multi-class target coverage problem is currently research hot in Wireless Sensor Networks（WSN）. Aiming at the disadvantage of the existing target coverage algorithms, the multi-class target coverage problem is modeled as a maximization lifetime problem based on the Linear Programming（LP）. This paper proposes a target coverage algorithm based on the clustering. According to the residual energy and sensing capability of nodes, the global coverage set is obtained on the basis of solving optimal solution within the each cluster structure, which is close to the optimal solution, moreover, the algorithm dispatches the corresponding sensing module to cover the target of having the same attributes within its sensing range. Experimental results show that the performance of this algorithm is superior to the CWGC algorithms in terms of the lifetime of network and time efficiency, close to the optimal value of LE