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提出了一种解决无线传感器网络覆盖问题的能量有效性启发式机制.该机制在节能的前提下,实现了对目标监控区域的完全覆盖,且覆盖精度与目标的重要性级别成正比关系.机制的实现运用了蚁群优化算法,算法的设计过程采用了新颖的启发式因子构造方法和基于评价函数的全局信息素更新规则,由此,人工蚂蚁被赋予了对目标监控区域的覆盖状况和对传感器网络区域能量状况的自适应感知能力,并通过增加优化解集中节点上的信息素量,加速求取最优解的收敛过程.最后,蚁群在迭代优化的基础上构建出解决无线传感器网络覆盖问题的健壮优化解,该优化解能够在能量有效性的基础上具备良好的覆盖有效性和较长的生命周期.
An energy-efficient heuristic mechanism is proposed to solve the problem of coverage in wireless sensor networks. This mechanism achieves the complete coverage of the target monitoring area under the premise of energy saving, and the coverage accuracy is directly proportional to the importance level of the target. , The ant colony optimization algorithm is used in the design. The algorithm uses a novel heuristic factor construction method and a global pheromone update rule based on the evaluation function. As a result, the artificial ant is endowed with the coverage of the target monitoring area and the Sensor network area, and improve the convergence of the optimal solution by increasing the pheromone quantity of the optimal solution node.Finally, the ant colony is constructed on the basis of iterative optimization to solve the problem of wireless sensor network Robust optimization solution to the problem, the optimal solution can have good coverage validity and long life cycle on the basis of energy efficiency.