An efficient weighted distributed clustering algorithm for mobile ad hoc networks

A. Hussein, S. Yousef, S. Al-Khayatt, O. Arabeyyat
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引用次数: 43

Abstract

Clustering approach is an important research topic for MANETs and widely used in efficient network management, hierarchical routing protocol design, network modeling, Quality of Service, etc. Many researchers' recent focus has been on clustering management which is one of the fundamental problems in mobile ad hoc networks. The main objective of clustering in mobile ad-hoc network environments is how can an optimal clusterhead be elected and how can the optimal number of clusters be achieved through division without degrading the whole network's performance. In this paper, we propose new weighted distributed clustering algorithm, called CBMD. It takes into consideration the parameters: connectivity (C), residual battery power (B), average mobility (M), and distance (D) of the nodes to choose locally optimal clusterheads. The goals of this algorithm are maintaining stable clustering structure with a lowest number of clusters formed, to minimise the overhead for the clustering formation and maintenance and to maximise the lifespan of mobile nodes in the system. Simulation experiments are conducted to evaluate the performance of our algorithm in terms of the number of clusters formed, reaffiliation count and numbers of clusterhead changes. Results show that our algorithm performs better than existing ones and is also tuneable to different kinds of network conditions.
移动自组织网络中一种有效的加权分布式聚类算法
聚类方法是manet的一个重要研究课题,广泛应用于高效网络管理、分层路由协议设计、网络建模、服务质量等方面。集群管理是移动自组织网络的基本问题之一,近年来受到众多研究者的关注。移动ad-hoc网络环境中聚类的主要目标是如何在不降低整个网络性能的前提下选出最优簇头,以及如何通过划分实现最优簇数。本文提出了一种新的加权分布式聚类算法CBMD。它考虑节点的连通性(C)、电池剩余电量(B)、平均迁移率(M)和距离(D)等参数来选择局部最优簇头。该算法的目标是以最少的聚类数量保持稳定的聚类结构,最小化聚类形成和维护的开销,最大化系统中移动节点的寿命。通过仿真实验对算法的性能进行了评价,包括形成的簇数、重新隶属的次数和簇头变化的次数。结果表明,该算法的性能优于现有的算法,并且可以适应不同类型的网络条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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