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Topology Control in MANETs Using the Bayesian Pursuit Algorithm

机译:使用贝叶斯追求算法的船只拓扑控制

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A way of optimizing energy consumption in mobile ad hoc networks is topology control. Various topology control algorithms have been proposed, but a few of them have used meta-heuristic methods such as genetic algorithms, neural networks, and learning automata. This paper presents a new algorithm based on the Bayesian pursuit (BPST) algorithm. The proposed algorithm predicts node mobility parameters by learning from the environment and uses these parameters to predict link availability duration. The algorithm, then, finds the paths with maximum lifetime by removing the links with a short lifetime using the local Dijkstra algorithm. In this way, an efficient and reliable topology is constructed. The paper also provides the proof of the convergence of the propounded BPST algorithm. The simulation results show that this algorithm can efficiently reduce energy consumption and improve throughput and end-to-end delay as two parameters of the quality of service.
机译:一种优化移动临时网络中能量消耗的方法是拓扑控制。 已经提出了各种拓扑控制算法,但其中一些使用了诸如遗传算法,神经网络和学习自动机等元启发式方法。 本文介绍了一种基于贝叶斯追求(BPST)算法的新算法。 该算法通过从环境中学习来预测节点移动性参数,并使用这些参数来预测链接可用性持续时间。 然后,算法通过使用本地Dijkstra算法删除具有短寿命的链路,找到具有最大寿命的路径。 以这种方式,构建了高效可靠的拓扑。 本文还提供了BPST算法的收敛性证明。 仿真结果表明,该算法可以有效地降低能量消耗,提高吞吐量和端到端延迟作为服务质量的两个参数。

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