Associativity-based Adaptive Weighted Clustering for Large-Scale Mobile Ad Hoc Networks

S. Ur Rehman, W.-C. Song, J. Lee, G.-L. Park (Korea), and H. Lutfiyya (Canada)


MANETs, clutering, associativity, and load-balancing


We propose and analyze a distributed adaptive clustering algorithm for large-scale ad hoc networks. The algorithm calculates a stability weight for each node based on its power and spatial and temporal stability. The nodes hav ing the highest stability weight get elected as clusterheads. Frequent clusterhead change is minimized by cautious in vocation of re-clustering. Frequency of control messages is adapted to the mobility pattern of clustermembers. The al gorithm balances load across clusterheads and adapts hop distance to the network density by keeping the cluster size around an optimum value. It reduces the overall commu nication complexity by minimizing the control traffic over head and by eliminating the ripple effect of re-clustering. We analyze effectiveness of the algorithm through simula tions.

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