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Algorithm and Convergence of MST Problem for Energy Efficient Routing in Wireless Sensor Networks

机译:无线传感器网络中高能效路由的MST问题的算法和收敛性

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The rapid development of the theory and application makes it imperative to find the best strategies to improve the energy efficiency of wireless sensor networks. In this paper, we address the following question: given a multi-to-one wireless sensor network in physical space, what is the optimal routing strategy to enable the energy-efficiency of the network with regard to a given mission and a certain amount of initial energy. We have focused on energy consumption involving data generation, data fusion and data transmission. We model the wireless sensor network as an undirected graph and put that energy efficient routing problem into a constrained optimization problem. In order to solve the optimal routing, we introduce the Ant Colony Optimization Algorithm, which is relatively easier than other algorithms to implement in a distributed environment because of its distributed computing and positive feedback features. Then we prove the convergence of the algorithm. Finally, in the simulation experiments, we show that the routes derived from out algorithm yield noticeably energy efficiency. Our optimization strategy can be applied to other distributed networks.
机译:该理论和应用的迅速发展使得必须找到最佳策略来提高无线传感器网络的能效。在本文中,我们解决了以下问题:给定物理空间中的多对一无线传感器网络,对于给定的任务和一定数量的无线网络,使网络节能的最佳路由策略是什么?初始能量。我们专注于能源消耗,涉及数据生成,数据融合和数据传输。我们将无线传感器网络建模为无向图,然后将高能效路由问题放入约束优化问题中。为了解决最优路由问题,我们引入了蚁群优化算法,该算法比其他算法更容易在分布式环境中实现,因为它具有分布式计算和正反馈特性。然后证明了算法的收敛性。最后,在仿真实验中,我们证明了从算法导出的路由可显着提高能效。我们的优化策略可以应用于其他分布式网络。

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