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A genetic algorithm for selecting cooperative or direct communications between nodes in wireless sensor networks

机译:一种遗传算法,用于在无线传感器网络中选择节点之间的协作或直接通信

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Abstract An effective technique to reduce energy consumption in wireless sensor networks (WSNs) is to make use of cooperative communications between nodes. In this technique, all nodes contribute to the transmission of data as senders and may transmit their data through relay nodes instead of sending directly to the receivers. This paper has the goal of reducing energy consumption. In this way, two wasted energies are considered, including the consumption for data transfer between any given pair of nodes and the same for end-to-end data transfer. In practice, the problem can be modeled as an optimization problem. However, finding the solution for this problem needs large resources such as memory and processing units. We propose a multi-objective genetic algorithm to solve this problem. The proposed algorithm balances the per-hop energy consumption with the end-to-end ones using the Pareto analysis. The simulations show that the proposed method offers acceptable results in comparison with the optimization model. However, the proposed algorithm can be solved in a shorter time.
机译:摘要减少无线传感器网络(WSNS)中能耗的有效技术是利用节点之间的协同通信。在该技术中,所有节点都有助于数据的传输作为发送器,并且可以通过中继节点发送它们的数据而不是直接发送到接收器。本文的目标是降低能源消耗。以这种方式,考虑了两个浪费的能量,包括在任何给定对节点之间的数据传输的消耗,并且对于端到端数据传输。在实践中,问题可以被建模为优化问题。但是,查找此问题的解决方案需要大量资源,如内存和处理单元。我们提出了一种多目标遗传算法来解决这个问题。所提出的算法使用Pareto分析将每跳能量消耗与端到端分析平衡。模拟表明,与优化模型相比,该方法提供了可接受的结果。但是,所提出的算法可以在较短的时间内解决。

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