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A Prediction Algorithm based on Markov Chains for finding the Minimum Cost Path in a Mobile WSNs

机译:一种基于Markov链接的预测算法,用于在移动WSN中找到最小成本路径的

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In this paper we propose the usage of a prediction technique based on Markov Chains to predict nodes positions with the aim of obtain short paths at minimum energy consumption. Specifically, the valuable information from the mobility prediction method is provided to our distributed routing algorithm in order to take the best network decisions considering future states of network resources. In this sense, in each network node, the mobility method employed is based on a Markov model to forecast future RSSI states of neighboring nodes for determining if they will be farther or closer within the next steps. The approach is evaluated considering different algorithms such as: Distance algorithm, Distance Away algorithm and Random algorithm. In addition, with the aim of performing comparisons against optimal values, we present a mathematical optimization model for finding the minimum cost path between a source and a destination node considering all network nodes are mobile. This paper is an extended variant of [8].
机译:在本文中,我们提出了基于马尔可夫链的预测技术的使用,以预测节点位置,目的是在最小能量消耗下获得短路径。具体地,向我们的分布式路由算法提供来自移动预测方法的宝贵信息,以便考虑未来网络资源状态的最佳网络决策。从这个意义上讲,在每个网络节点中,所采用的移动方法基于Markov模型来预测相邻节点的未来RSSI状态,以确定它们是否在下一步骤中更远或更靠近。考虑到不同算法,例如:距离算法,距离算法和随机算法,评估该方法。另外,在考虑所有网络节点是移动的情况下,我们介绍了用于查找源和目的地节点之间的最小成本路径的数学优化模型。本文是[8]的扩展变体。

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