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Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs

机译:使用链路断开熵混乱来检测MANET中的快速移动节点

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摘要

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder.
机译:移动自组织网络(MANET)本质上是动态的。这种动态性来自节点移动性,流量拥塞和其他传输条件。评估这些条件影响的度量标准可以揭示Ad-hoc网络中节点的行为,有助于识别具有更好连接条件的一个或多个节点。在本文中,我们基于以邻居节点为参考的链路断开熵紊乱,提出了一个相对指标来评估单节点可靠性。链路断开熵混乱最好用于识别快速移动的节点或通信不稳定的节点,而无需专用传感器(如GPS)。研究了几种方案来验证索引,测量速度和流量密度对链路断开熵熵的影响。数据包传递比率与检测到强关系的度量相关联,从而可以使用链路断开熵熵来评估节点与其他节点进行通信的稳定性。为了扩大链接熵无序度的利用,我们仅通过使用链接熵无序度就能识别出网络模拟中具有较高速度的节点。

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