Probabilistic Emergent Algorithm for Cluster Establishment
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Graphical Abstract
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Abstract
Emergent clustering algorithm ACE is one type of clustering algorithms based on swarm intelligence for mobile ad hoc networks. Aiming at the problems that exist during iterations in ACE, this paper introduces a probability mechanism and proposes a novel probability-based clustering algorithm named PACE. With the local information that the cluster head probability of nodes candidate is the highest, PACE can create a global clustering network. In the case of the same probability, the node identifier is used to arbitrate the elections of cluster heads. Meanwhile, the mergence of single node clusters and failure recovery can also be achieved by the strategies above. The theoretical analysis and simulation results show that PACE has a short convergence time, can find a stable and more optimized clustering structure, and provides a capability of failure recovery.
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