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提出了一种解决无线传感器网络覆盖问题的分布式启发式机制。该机制在节能前提下,得到优化的目标覆盖集合,以实现对目标监控区域的完全覆盖,并通过对其中重点目标集合的冗余覆盖来满足对重点目标集的可靠监控。同时,该目标覆盖集合与数据汇集点在通信结构上保持连通性。本文采用了改进的蚁群优化算法(最大最小蚁群混合算法)来实现上述启发式机制。通过构造新颖的启发式因子,人工蚂蚁能够由局域信息感知传感器网络的能量状况和覆盖能力,从而自适应地建立具备通信连通性的数据汇集路径。此外,将信息素浓度调节因子和评价函数引入了信息素更新规则的设计,使得蚁群在扩大搜索范围的基础上,提高了解的质量,且避免了求解过程陷入局部最优。算法的输出为能量有效的优化解集,具备较长生命周期,能够在保证与数据汇集点可靠连通的同时实现对目标区域的有效覆盖。
A distributed heuristic to solve the problem of wireless sensor network coverage is proposed. Under the precondition of energy conservation, this mechanism obtains the optimized target coverage set to realize the complete coverage of the target monitoring area and satisfies the reliable monitoring of the key target set through the redundant coverage of the key target set. At the same time, the target coverage set and data collection point maintain the communication structure. In this paper, an improved ant colony optimization algorithm (maximum and minimum ant colony hybrid algorithm) to achieve the above heuristic mechanism. By constructing a novel heuristic factor, artificial ant can perceive the energy status and coverage of the sensor network from the local information, so as to adaptively establish a data collection path with communication connectivity. In addition, the pheromone concentration adjustment factor and evaluation function are introduced into the design of the pheromone updating rule, so that the ant colony can improve the quality of the solution and enlarge the search scope, and avoid the solution process falling into the local optimum. The output of the algorithm is an energy-efficient optimized solution set with a long life cycle, which can ensure the effective coverage of the target area while ensuring reliable communication with the data collection point.