Distributed Clustering Algorithm for Cognitive Radio Ad Hoc Networks
Clustering is believed as an efficient method to improve the performance of mobile ad hoc networks (MANETs). It is the same for cognitive radio ad hoc networks (CRAHNs). However, the introduction of cognitive radio technology brings new challenges. We proposed a CogAd-hoc cluster structure in our precious work . This paper designed a distributed clustering algorithm to construct the CogAd-hoc cluster structure. The clustering algorithm is based on Minimal Connected Dominating Set (MCDS) and requires only single-hop neighborhood knowledge. In the best case, its approximation factor is 12 and it has O(nlogn) message complexity and O(n) time complexity. In addition, the algorithm has good load-balancing feature and can avoid the ripple effect of re-clustering.
KeywordsCognitive radio ad hoc networks minimal connected dominating set distributed clustering algorithm
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