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Mobile agent itinerary planning for WSN data fusion: consideringmultiple sinks and heterogeneous networks

机译:移动代理WSN数据融合的行程规划:考虑多个水槽和异构网络

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摘要

Mobile agent (MA)-based middleware has been thoroughly investigated in the past few years as a means to address the efficiency, scalability, and reliability issues of data fusion applications on wireless sensor networks. Deriving an efficient itinerary for each MA to follow is of high importance, because itineraries determine to a large extent the overall performance of data fusion tasks. In this article, we present a novel algorithmic approach for efficient itinerary planning of MA objects undertaking data fusion tasks. We adopt a method based on iterated local search to construct the itineraries (ie, visiting sequences of source nodes) assigned to multiple traveling MAs. We apply alternative optimization criteria which aim either at minimizing the overall energy expenditure over all derived MA itineraries or prolonging the network lifetime. Furthermore, we propose algorithmic solutions for 2 realistic settings which have not been investigated in the past: firstly, the employment of multiple sinks that share the responsibility of MA-based data fusion tasks across the sensor field, and secondly, the consideration of heterogeneous sensor networks comprising nodes powerful enough to host the runtime environment required to execute MA code as well as "ordinary" nodes which lack these resources. Simulation tests verify the performance gain attained by our algorithmic methods against alternative itinerary planning approaches which involve multiple MAs. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:基于移动代理(MA)的中间件在过去几年中已经彻底调查了以解决无线传感器网络上数据融合应用的效率,可扩展性和可靠性问题的手段。为每个MA推导出一个有效的行程,遵循的重要性很高,因为行程在很大程度上决定了数据融合任务的整体性能。在本文中,我们提出了一种新颖的算法方法,以便有效的管理数据融合任务的MA对象的行程规划。我们采用基于迭代本地搜索的方法来构建分配给多个旅行MAS的行程(即,访问源节点序列)。我们应用替代优化标准,旨在最大限度地减少所有衍生的MA行程的整体能源支出或延长网络寿命。此外,我们提出了过去尚未调查的2个现实设置的算法解决方案:首先,在传感器领域的基于MA的数据融合任务的责任中使用多个水槽,其次,对异构传感器的考虑包括足够强大的节点的网络,以托管执行MA代码所需的运行时环境以及缺少这些资源的“普通”节点。仿真试验验证了我们算法方法对涉及多个MAS的替代行程规划方法而获得的性能增益。版权所有(c)2016 John Wiley&Sons,Ltd。

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