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数据收集是无线传感器网络(Wireless Sensor Network,WSN)的基本问题.近年来的研究表明相比于WSN的静态多跳转发数据收集,利用移动机器人作为移动节点辅助WSN进行数据收集能够有效地减少数据转发跳数,提高WSN的生命周期,然而由于移动机器人移动速度相对较慢的机械特性,使得WSN的数据收集时间产生了较大的延迟.为了较好地解决WSN生命周期与移动机器人数据收集时间延迟间的相互矛盾问题,提出基于动态分簇的多移动机器人数据收集问题(Dynamic Cluster Based Multi-robot Data Collection,DC-MDC),并将其公式化为一个整数线性规划.在公式化过程中,先将WSN划分成簇,然后再将每个簇划分成具有最大深度为d的子簇路由树,最后利用移动机器人在每个簇的子簇路由树的根节点之间进行数据收集.为了解决DC-MDC问题,本文给出了一个分布式的启发性数据收集算法(Distributed Heuristic Data Collection Algorithm,DHDCA),并利用大量的对比仿真实验验证了此算法的有效性.
Data collection is a basic problem of Wireless Sensor Network (WSN) .Recent studies have shown that the use of mobile robots as a mobile node to assist WSN in data collection can effectively reduce the number of data collected compared to WSN’s static multi-hop forwarding However, due to the relatively slow moving speed of mobile robot, the data collection time of WSN has a big delay.To solve the problem of WSN life cycle and mobile robot data collection (DC-MDC) based on dynamic clustering is proposed, which is formulated as an integer linear programming.In the process of formulation, Firstly, the WSN is divided into clusters, and then each cluster is divided into the sub-cluster routing tree with the maximum depth d, and finally the mobile robot is used to collect the data between the root nodes of the sub-cluster routing tree of each cluster.In order to solve DC-MDC problem, this paper presents a distributed heuristic data collection algorithm (Distributed Heuristic Data Col lection Algorithm, DHDCA), and verify the effectiveness of this algorithm by using a large number of comparative experiments.