Proceedings ArticleDOI
Max-min d-cluster formation in wireless ad hoc networks
Alan D. Amis,Ravi Prakash,T.H.P. Vuong,D.T. Huynh +3 more
- Vol. 1, pp 32-41
TLDR
A heuristic to form d-clusters in a wireless ad hoc network that tends to re-elect existing clusterheads even when the network configuration changes and has a tendency to evenly distribute the mobile nodes among the clusterheads, and evently distribute the responsibility of acting as clusterheads among all nodes.Abstract:
An ad hoc network may be logically represented as a set of clusters. The clusterheads form a d-hop dominating set. Each node is at most d hops from a clusterhead. Clusterheads form a virtual backbone and may be used to route packets for nodes in their cluster. Previous heuristics restricted themselves to 1-hop clusters. We show that the minimum d-hop dominating set problem is NP-complete. Then we present a heuristic to form d-clusters in a wireless ad hoc network. Nodes are assumed to have a non-deterministic mobility pattern. Clusters are formed by diffusing node identities along the wireless links. When the heuristic terminates, a node either becomes a clusterhead, or is at most d wireless hops away from its clusterhead. The value of d is a parameter of the heuristic. The heuristic can be run either at regular intervals, or whenever the network configuration changes. One of the features of the heuristic is that it tends to re-elect existing clusterheads even when the network configuration changes. This helps to reduce the communication overheads during transition from old clusterheads to new clusterheads. Also, there is a tendency to evenly distribute the mobile nodes among the clusterheads, and evently distribute the responsibility of acting as clusterheads among all nodes. Thus, the heuristic is fair and stable. Simulation experiments demonstrate that the proposed heuristic is better than the two earlier heuristics, namely the LCA and degree-based solutions.read more
Citations
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DissertationDOI
Wireless Sensor Networks in Motion - Clustering Algorithms for Service Discovery and Provisioning
TL;DR: This thesis proposes a set of algorithms that enable WSNs to self-organize efficiently in the presence of mobility, adapt to and even exploit dynamics to increase the functionality of the network.
Journal ArticleDOI
Bounded-distance multi-clusterhead formation in wireless ad hoc networks
TL;DR: A novel multi-core multicast protocol that applies the distributed solution for the election of cores and is compared against PUMA, one of the best performing multicast protocols for MANETS.
Proceedings ArticleDOI
Scenario-based stability anlysis of the distributed mobility-adaptive clustering (DMAC) algorithm
TL;DR: This paper investigates the Distributed Mobility-Adaptive Clustering (DMAC) algorithm and evaluates how the cluster stability is influenced by the speed, the choice of the weight, and the failure rate of nodes.
Proceedings ArticleDOI
An efficient leader election protocol for mobile networks
TL;DR: A leader election protocol that works under frequent network changes and node mobility, based on electing a unique node that outperforms all the other nodes in a cluster identified by the protocol is presented.
Journal ArticleDOI
Energy constraint clustering algorithms for wireless sensor networks
TL;DR: This work presents an Energy Constrained minimum Dominating Set based efficient clustering called ECDS and proposes multiple extensions to the distributed algorithm for the energy constrained dominating set that perform well in terms of energy usage, node lifetime, and clustering time in comparison and are very suitable for wireless sensor networks.
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