认知启发的VANET中OLSR最优路径

Thompson Stephan, K. Karuppanan
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引用次数: 6

摘要

车载自组织网络(vanet)是随着无线技术的发展而发展起来的。在这种网络中,信号覆盖的局限性和节点的高移动性导致拓扑结构频繁变化。由于VANET的拓扑不稳定性,VANET中的被动路由协议的范围受到限制,而为MANET设计的主动路由协议(如OLSR)也无法满足VANET所设想的广泛数据服务。这是由于现有的OLSR协议无法感知信道状况和预测信道过载。为了提高路由效率,网络需要具备考虑链路状态和信道信息选择最优路径的认知能力,从而克服信道无容量的问题。本文试图通过获取和存储路由策略知识的认知过程来增强OLSR路由,从而选择最合适的路由和合适的传输通道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive inspired optimal routing of OLSR in VANET
Vehicular Ad Hoc Networks (VANETs) evolved as a result of recent advances in wireless technologies. In such networks, the limitation of signal coverage and the high mobility of the nodes generate frequent changes in topology. The scope of reactive routing protocol in VANET is limited due to the topology instability of VANET whereas proactive routing protocol such as OLSR, designed for MANET is also unable to meet the broad range of data services envisioned for VANET. It is due to the inability of existing OLSR protocol to sense channel conditions and predict channel overload. In order to improve the routing efficiency, the network needs to possess some cognitive capacity to choose an optimal path accounting both link state and channel information and thereby overcoming the problem of channel incapacity. This paper attempts to enhance OLSR routing with help of cognitive process that involve in obtaining and storing knowledge on routing strategies to opt for the most suitable route and also appropriate channel for transmission.
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