To mimic the operations in fixed infrastructures and to solve the routing scalability problem in large Mobile Ad Hoc Networks (MANET), forming clusters of nodes has been proven to be a promising approach. However, when existing weighted clustering algorithms calculate each node’s weight, they either consider only one metric or rely on some metrics collected from extra devices. This often leads to a higher rate of re-clustering. This chapter presents a robust weighted clustering algorithm, called PMW (Power, Mobility and Workload), to form and maintain more stable clusters. In PMW, the weight of each node is calculated by its power, mobility and workload, which can be easily collected and computed locally and cover the major factors that cause re-clustering. Clustering overhead of PMW is analyzed. The simulation results confirm that PMW prolongs lifetime of MANETs and has a lower cluster head change rate and re-affiliation rate than other existing algorithms.
I would like to take the opportunity to thank the people who guided and supported me during this PhD study. Without their contributions, this research would not have been possible. First, I would like to thank my PhD advisor, Dr. Le Gruenwald. During my PhD study, Dr. Gruenwald taught me how to do research, and she was always patient and helpful whenever her guidance and assistance was needed. As an international student, I found technical writing was difficult. She contributed much of her valuable time to help me improve my writing skills. She also gave advice on how to communicate and cooperate with other researchers as a professional. Therefore, I do want to show my deep appreciation to her.
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