CMIP：一种增强无线传感器网络事件-汇聚点响应的克隆移动代理路径规划方法
CMIP: Clone Mobile-agent Itinerary Planning Approach for Enhancing Event-to-Sink Throughput in Wireless Sensor Networks
摘要：
为了缓解无线传感器网络中数据拥塞、延迟增加和高能耗的问题，移动代理（MA）已被证明是传统客户端-服务器数据收集模型的可行替代方案。MA具有基于所分配的路线在网络节点之间迁移的能力，所述路线可以经由单路线规划（SIP）或多路线规划（MIP）形成。基于MIP的数据收集方法解决了与SIP相关的任务持续时间，能耗和可靠性方面的问题。然而，大多数现有的MIP方法只关注减少能耗和任务持续时间，而事件到宿吞吐量没有被考虑。在本文中，克隆移动代理行程规划方法（CMIP），提出了减少任务持续时间，同时提高事件到汇吞吐量的实时应用，特别是当MA被分配访问大量的源节点。仿真结果表明，CMIP方法优于中心位置为基础的MIP（CL-MIP）和最大信息最大内存为基础的MIP（GIGM-MIP）在减少约56%和16%的任务持续时间方面，分别。此外，与CL-MIP和GIGM-MIP方法相比，CMIP分别将事件到宿吞吐量提高了约93%和22%。
英文摘要：
In order to mitigate the problem of data congestion, increased latency, and high energy consumption in Wireless Sensor Networks (WSNs), Mobile Agent (MA) has been proven to be a viable alternative to the traditional client-server data gathering model. MA has the ability to migrate among network nodes based on an assigned itinerary, which can be formed via Single Itinerary Planning (SIP) or Multiple Itinerary Planning (MIP). MIP-based data gathering approach solves problems associated with SIP in terms of task duration, energy consumption, and reliability. However, the majority of existing MIP approaches focus only on reducing energy consumption and task duration, while the Event-to-sink throughput has not been considered. In this paper, a Clone Mobile-agent Itinerary Planning approach (CMIP) is proposed to reduce task duration while improving the Event-to-sink throughput in real-time applications, especially when the MA is assigned to visit a large number of source nodes. Simulation results show that the CMIP approach outperforms both Central Location-based MIP (CL-MIP) and Greatest Information in Greatest Memory-based MIP (GIGM-MIP) in terms of reducing task duration by about 56% and 16%, respectively. Furthermore, CMIP improves the Event-to-sink throughput by about 93% and 22% as compared to both CL-MIP and GIGM-MIP approaches, respectively.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
