Increasing performance of ODMRP by using learning automata

A. Shafigh, K. Abdollahi
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引用次数: 0

Abstract

A Mobile ad hoc network is a collection of wireless communication nodes that dynamically form a network without any fixed infrastructure. One of the most important topics in these networks is multicast routing. Although multicast algorithms are desirable in many situations, their forwarding mechanism and network resource consumption makes them significantly less efficient than unicast routing algorithms. The most significant type of multicast protocols are mesh-based algorithms which, use periodic flooding mechanism to construct paths. Flooding rate in the multicast routing protocols depends on node mobility and input traffic. Thus, this rate should adaptively adjust to restrict overheads, while there are continuously a complete mesh between receivers and senders in network. In this paper, a novel prediction model is proposed to compute the best rate of flooding mechanism. Our results show substantial improvement in overhead while has no reduction in the performance of the multicast routing protocol.
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通过使用学习自动机提高ODMRP的性能
移动自组织网络是无线通信节点的集合,这些节点动态地形成一个没有任何固定基础设施的网络。在这些网络中最重要的课题之一是组播路由。虽然多播算法在许多情况下是可取的,但其转发机制和网络资源消耗使其效率明显低于单播路由算法。最重要的组播协议类型是基于网格的算法,它使用周期泛洪机制来构建路径。组播路由协议的泛洪速率取决于节点的移动性和输入流量。因此,该速率应自适应调整以限制开销,而网络中的接收方和发送方之间始终存在完整的网格。本文提出了一种新的预测模型来计算最佳驱油速率。我们的结果表明,在开销上有很大的改善,而组播路由协议的性能没有降低。
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