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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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Citations
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Journal ArticleDOI

An Entropy-Based Clustering Scheme in Mobile Ad Hoc Networks

TL;DR: This paper proposes a clustering scheme i.e., identify a subset of nodes among all the nodes that are best suited to be clusterheads and uses entropy as a measure of local and mutual information available to every node.
Posted Content

Component Based Clustering in Wireless Sensor Networks

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Journal ArticleDOI

Efficient Heuristic Based on Clustering Approach for OLSR

TL;DR: Experimental results show that the proposed novel version of OLSR based on the clustering approach which is inspired from Lin and Chu heuristic and adapted to be implemented inOLSR significantly reduces the traffic reserved to monitoring the network, which positively influences other performances such as throughput, delay, and loss.

Research Roadmap on Cooperating Objects (CONET Roadmap 2009)

TL;DR: The research Roadmap on Cooperating Objects Pedro José Marrón, Stamatis Karnouskos, Daniel Minder and the CONET consortium is presented, which aims to provide a road map for the development of smart cities in Europe.
Book ChapterDOI

A clustering-based channel assignment algorithm and routing metric for multi-channel wireless mesh networks

TL;DR: This paper proposes a 2-hop clustering based multi-interface, multi-channel network architecture and design a novel channel assignment algorithm and routing metric, which combines hop-count, channel diversity and channel switching capability together.
References
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