一种有效的簇头选择算法ACO
An ACO Algorithm for Effective Cluster Head Selection
摘要：
提出了一种基于蚁群算法的移动自组网簇头选择算法。自组织网络中的簇由簇头和距离簇头一跳的簇成员组成。簇头将资源分配给其簇成员。移动自组织网络中的分簇可以减少通信开销，从而提高网络性能。一个移动自组网中可以有多个簇，本文提出了一种算法，该算法是基于ID的分簇，基于连通性的分簇，基于概率的分簇和加权的分簇方法的组合。提出了一种基于蚁群优化的方法来最小化移动自组网中的分簇数目。这也可以看作是图论中的最小支配集问题。该算法考虑了各种参数，如节点数，传输范围等实验结果表明，该算法是一种有效的方法，找出最小数目的簇头。
英文摘要：
This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
