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Proceedings ArticleDOI

Max-min d-cluster formation in wireless ad hoc networks

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.

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Cluster Based Efficient Location Aware - Source Multicast Routing Approach for Wireless Sensor Networks

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An efficient algorithm for backbone construction in cognitive radio networks

TL;DR: This paper proposes a tree‐based backbone formation protocol based on non‐iterative approach, thus leading towards limited message overhead and faster convergence speed in cognitive radio network (CRN).

A Penalty-Based Approach to Handling Cluster Sizing in Mobile Ad Hoc Networks

Ryan Florin
TL;DR: A penalty-bas ed approach to handle cluster sizing in mobile ad Hoc Networks in a more appropriate manner is proposed and the penalty function allows for a m ore complex clustering sizing strategy.
Proceedings ArticleDOI

Towards Efficient Use of Radio Resources in Single Channel Wireless Mesh Networks

TL;DR: This paper proposes two clustering schemes that take into consideration the mobility properties of users in order to improve the WMN performance and proves that both schemes can achieve significant gains in terms of radio resource utilization, especially when the number of simultaneous connections in the network increases.
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