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EFMMRP: Design of efficient fuzzy based multi-constraint multicast routing protocol for wireless ad-hoc network

机译:EFMMRP:用于无线自组织网络的基于有效模糊的多约束多播路由协议的设计

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Mobile Ad-hoc Network (MANET) is a temporarily wireless network constructed by a set of mobile devices which are communicated over wireless channel without having any fixed infrastructure and centralized administration. Multicasting is a mechanism to send a data packet from one node to a group of receivers node at a time. There are various challenges in a MANET due to dynamic network topology and limited resources. Since the network performance metrics such as delay, bandwidth and energy changes very frequently due to node mobility i.e. these network metrics have the uncertainty issues in a wireless mobile ad-hoc network. The impact of these uncertainty issues creates a problem in the selection of optimal path from source node to a group of receiver nodes. So, in this paper, we have tried to control these uncertainties issues in order to conserve the network resources using fuzzy logic tool. In this mechanism all the available network metrics of the routes is converted into a single metric i.e. fuzzy cost or communication cost. The routes having minimum fuzzy cost will be considered as optimal path and the data is to be transmitted over this path from source node to a set of receivers. The simulation has been conducted using NS-2 and MATLAB, the results shows the effectiveness of the proposed protocol (EFMMRP) over ODMRP and MAODV in terms of pacaket delivery ratio, packet delivery delay and control overhead. (C) 2017 Elsevier B.V. All rights reserved.
机译:移动自组织网络(MANET)是由一组移动设备构建的临时无线网络,这些移动设备通过无线通道进行通信,而无需任何固定的基础结构和集中管理。组播是一次将数据包从一个节点发送到一组接收者节点的机制。由于动态网络拓扑和有限的资源,MANET中存在各种挑战。由于诸如延迟,带宽和能量之类的网络性能度量由于节点移动性而非常频繁地改变,即,这些网络度量在无线移动自组织网络中具有不确定性问题。这些不确定性问题的影响在选择从源节点到一组接收器节点的最佳路径时产生了问题。因此,在本文中,我们尝试使用模糊逻辑工具来控制这些不确定性问题,以节省网络资源。在这种机制中,路由的所有可用网络度量都转换为单个度量,即模糊成本或通信成本。具有最小模糊成本的路由将被视为最佳路径,并且数据将通过该路径从源节点传输到一组接收器。仿真是使用NS-2和MATLAB进行的,结果表明,在小蛋糕传送率,数据包传送延迟和控制开销方面,所提出的协议(EFMMRP)优于ODMRP和MAODV。 (C)2017 Elsevier B.V.保留所有权利。

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