The sink hole problem is a critical issue for data collection in wireless sensor networks. Recent research has indicated that the mobility of actuators in wireless sensor actuator networks (WSANs) alleviates the sink hole problem. However, mobile actuator-based data collection may result in unsatisfactory data gathering delay, which is not acceptable for delay-sensitive real time applications. Thus, planning the optimal path for mobile collector is a critical challenge in WSANs to balance between the prolongation of network lifetime and the reduction of the data gathering delay. To address this issue, we propose a mobile collector-based cost balancing algorithm to achieve uniform data gathering delay and energy consumption based on the adaptive region partitioning and dynamic polling point selection. The proposed algorithm uses multiple mobile collectors and partitions the sensing area into several regions that are monitored by the mobile collectors according to the distribution of cost in the area. It also dynamically determines moving trajectory of each mobile collector by selecting the polling points to visit considering the distance to travel and the nodes’ energy consumption. The superiority of the proposed algorithm is validated by theoretical analysis and simulation results.

中文翻译：

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无线传感器执行器网络系统中统一数据收集延迟和能耗的基于移动收集器的成本平衡方案

下沉孔问题是无线传感器网络中数据收集的关键问题。最近的研究表明，无线传感器执行器网络 (WSAN) 中执行器的移动性缓解了下沉孔问题。然而，基于移动执行器的数据收集可能会导致令人不满意的数据收集延迟，这对于延迟敏感的实时应用程序来说是不可接受的。因此，规划移动收集器的最佳路径是 WSAN 中平衡网络寿命延长和数据收集延迟减少之间的关键挑战。为了解决这个问题，我们提出了一种基于移动收集器的成本平衡算法，以基于自适应区域划分和动态轮询点选择来实现统一的数据收集延迟和能耗。所提出的算法使用多个移动采集器，并根据区域内的成本分布将传感区域划分为多个由移动采集器监控的区域。它还通过考虑移动距离和节点能量消耗选择要访问的轮询点来动态确定每个移动收集器的移动轨迹。理论分析和仿真结果验证了所提算法的优越性。