An Ant Colony Optimization Algorithm for Multi-Objective Clustering in Mobile Ad-Hoc Networks

• Main Authors: Chung-Wei Wu, 吳仲偉
• Other Authors: 傅立成
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/50735878665131729613

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 102 === With the rise of the fourth generation (4G) communication standards and the growing usage of mobile computing devices, mobile ad hoc network becomes a hot topic and getting more and more attention in recent years. In this thesis, we address the clustering problem in mobile ad hoc network (MANET). Due to the convenient deployment and the flexibility for variety terrains, MANET has been widely used in various fields. Routing protocols are the most important issue of MANETs, however, it has been proved that both proactive and reactive routing schemes cannot perform well or even didn’t work in a large scale size of MANET, and clustering is the most efficient method to deal with it. Clustering leads a hierarchical structure, for each cluster a cluster head will be chosen for intra- and inter- communication. However clustering in MANET is NP-hard and needs to consider multiple objectives. In this thesis, we propose a Pareto-based ant colony optimization (ACO) algorithm to deal with this multiobjective optimization problem. We proposed a clustering matrix encoding to reflect the cluster selection and cluster formation without any bias and redundant solutions. A repair function is proposed for upgrading the quality of solutions. Apart from this, we also propose a mechanism to maintain the cluster structure for dynamic situations. The experiment results confirm that it outperforms several state-of-the-art algorithms and indicates the potential to be applied to practical use.