A new distributed algorithm to find breadth first search trees
IEEE Transactions on Information Theory
Discrete Mathematics - Topics on domination
A cluster-based approach for routing in dynamic networks
ACM SIGCOMM Computer Communication Review
Multicluster, mobile, multimedia radio network
Wireless Networks
Hierarchically-organized, multihop mobile wireless networks for quality-of-service support
Mobile Networks and Applications - Special issue: mobile multimedia communications
A Distributed Algorithm for Minimum-Weight Spanning Trees
ACM Transactions on Programming Languages and Systems (TOPLAS)
Message-optimal connected dominating sets in mobile ad hoc networks
Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing
K-clustering in wireless ad hoc networks
Proceedings of the second ACM international workshop on Principles of mobile computing
WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks
Cluster Computing
Graphs with Bounded Induced Distance
WG '98 Proceedings of the 24th International Workshop on Graph-Theoretic Concepts in Computer Science
Connectivity-Based k-Hop Clustering in Wireless Networks
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
New Distributed Algorithm for Connected Dominating Set in Wireless Ad Hoc Networks
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 9 - Volume 9
Distributed Clustering for Ad Hoc Networks
ISPAN '99 Proceedings of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks
A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks
ICDCSW '01 Proceedings of the 21st International Conference on Distributed Computing Systems
Distributed construction of connected dominating set in wireless ad hoc networks
Mobile Networks and Applications - Discrete algorithms and methods for mobile computing and communications
A Light-Weight Contention-Based Clustering Algorithm for Wireless Ad Hoc Networks
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
A Self-stabilizing Link-Cluster Algorithm in Mobile Ad Hoc Networks
ISPAN '05 Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks
Hierarchical Routing Overhead in Mobile Ad Hoc Networks
IEEE Transactions on Mobile Computing
Adaptive clustering for mobile wireless networks
IEEE Journal on Selected Areas in Communications
A distributed group mobility adaptive clustering algorithm for mobile ad hoc networks
Computer Communications
Fair and flexible budget-based clustering
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Cluster-based optimisation of load and energy aware routing in MANET
International Journal of Mobile Network Design and Innovation
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Mobile ad hoc networks may be composed of a large number of nodes and hence a hierarchical cluster-based structure can be employed to address the scalability issues of the large network. In this paper we propose a size-restricted, distributed clustering strategy (cluster formation and cluster maintenance) for mobile ad hoc networks. A distributed approach where every node is responsible for the clustering decisions would avoid single-point bottleneck failures. We use a size restriction S, for the cluster formation and cluster maintenance. In addition, while forming the cluster we also use a diameter restriction K. The simulations show that our strategy gives rise to a lesser number of clusters when compared to other clustering algorithms proposed by Gerla et al., Fernadess et al. and Lin et al. This is attributed to the size restriction and cluster merging that we have incorporated. The size restriction helps in better management of resources inside the cluster. Our clustering technique uses a weight-based cluster head election strategy which results in less change in cluster head and higher cluster head lifetime when compared to the Least Cluster Head Changes (LCC) with lowest ID algorithm. The low change in cluster head and higher cluster head lifetime make our proposed algorithm suitable for high-mobility situations. The proposed clustering strategy could be used for building the clusters required in a hierarchical structure of the ad hoc network.