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A Tree Based Data Aggregation Scheme for Wireless Sensor Networks Using GA

机译:基于遗传算法的无线传感器网络基于树的数据聚合方案

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Energy is one of the most important items to determine the network lifetime due to low power energy nodes included in the network. Generally, data aggregation tree concept is used to find an energy efficient solution. However, even the best aggregation tree does not share the load of data packets to the transmitting nodes fairly while it is consuming the lowest possible energy of the network. Therefore, after some rounds, this problem causes to consume the whole energy of some heavily loaded nodes and hence results in with the death of the network. In this paper, by using the Genetic Algorithm (GA), we investigate the energy efficient data collecting spanning trees to find a suitable route which balances the data load throughout the network and thus balances the residual energy in the network in addition to consuming totally low power of the network. Using an algorithm which is able to balance the residual energy among the nodes can help the network to withstand more and consequently extend its own lifetime. In this work, we calculate all possible routes represented by the aggregation trees through the genetic algorithm. GA finds the optimum tree which is able to balance the data load and the energy in the network. Simulation results show that this balancing operation practically increases the network lifetime.
机译:由于网络中包含低功耗能源节点,能源是确定网络寿命的最重要项目之一。通常,数据聚合树概念用于找到节能解决方案。但是,即使最佳的聚合树在消耗网络的最低​​能量的同时,也不会公平地分担数据包对传输节点的负载。因此,经过一轮回合后,此问题导致消耗了一些重负载节点的全部能量,从而导致网络瘫痪。在本文中,通过使用遗传算法(GA),我们研究了生成树的节能数据,以找到合适的路由,该路由平衡了整个网络中的数据负载,从而平衡了网络中的剩余能量,而且消耗的能量非常低。网络的力量。使用能够在节点之间平衡剩余能量的算法,可以帮助网络承受得更多,从而延长其自身的寿命。在这项工作中,我们通过遗传算法计算由聚集树表示的所有可能的路线。 GA找到了可以平衡数据负载和网络能量的最佳树。仿真结果表明,这种平衡操作实际上增加了网络寿命。

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