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A Spawn Mobile Agent Itinerary Planning Approach for Energy-Efficient Data Gathering in Wireless Sensor Networks

机译:用于无线传感器网络中节能数据收集的Spawn移动代理路线计划方法

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摘要

Mobile agent (MA), a part of the mobile computing paradigm, was recently proposed for data gathering in Wireless Sensor Networks (WSNs). The MA-based approach employs two algorithms: Single-agent Itinerary Planning (SIP) and Multi-mobile agent Itinerary Planning (MIP) for energy-efficient data gathering. The MIP was proposed to outperform the weakness of SIP by introducing distributed multi MAs to perform the data gathering task. Despite the advantages of MIP, finding the optimal number of distributed MAs and their itineraries are still regarded as critical issues. The existing MIP algorithms assume that the itinerary of the MA has to start and return back to the sink node. Moreover, each distributed MA has to carry the processing code (data aggregation code) to collect the sensory data and return back to the sink with the accumulated data. However, these assumptions have resulted in an increase in the number of MA’s migration hops, which subsequently leads to an increase in energy and time consumption. In this paper, a spawn multi-mobile agent itinerary planning (SMIP) approach is proposed to mitigate the substantial increase in cost of energy and time used in the data gathering processes. The proposed approach is based on the agent spawning such that the main MA is able to spawn other MAs with different tasks assigned from the main MA. Extensive simulation experiments have been conducted to test the performance of the proposed approach against some selected MIP algorithms. The results show that the proposed SMIP outperforms the counterpart algorithms in terms of energy consumption and task delay (time), and improves the integrated energy-delay performance.
机译:最近,移动代理(MA)作为移动计算范例的一部分,被提出用于无线传感器网络(WSN)中的数据收集。基于MA的方法采用两种算法:单代理程序行程计划(SIP)和多移动代理程序行程计划(MIP),以实现节能数据收集。通过引入分布式多MA来执行数据收集任务,提出了MIP以克服SIP的弱点。尽管MIP有很多优点,但找到分布式MA的最佳数量及其行程仍然被视为关键问题。现有的MIP算法假定MA的行程必须开始并返回到宿节点。此外,每个分布式MA都必须携带处理代码(数据聚合代码)以收集感官数据并与所积累的数据一起返回到接收器。但是,这些假设导致MA的迁移跃点数量增加,从而导致能耗和时间消耗增加。在本文中,提出了一种产卵多移动代理路线计划(SMIP)方法,以减轻数据收集过程中能源成本和时间的大量增加。所提出的方法基于代理产生,使得主MA能够产生具有从主MA分配的不同任务的其他MA。已经进行了广泛的仿真实验,以针对某些选定的MIP算法测试所提出方法的性能。结果表明,所提出的SMIP在能耗和任务延迟(时间)方面均优于同类算法,并提高了综合能量延迟性能。

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