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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

Multi-hop clustering based on neighborhood benchmark in mobile ad-hoc networks

TL;DR: A technique is presented to construct multi-hop clusters with balanced sizes, based on the neighborhood benchmark (NB) to quantify the connectivity and link stability of mobile nodes.
Proceedings ArticleDOI

A scalable framework for distributed time synchronization in multi-hop sensor networks

O. Younis, +1 more
TL;DR: This paper proposes a clustering- based time synchronization framework for multi-hop sensor net- works that exploits the tradeoff between rapid convergence (and consequently energy-efficiency) and perceived accuracy, and formulate a density model for analyzing inter- regional synchronization.
Proceedings ArticleDOI

A Fuzzy-Based Cluster-Head Selection System forWSNs Considering Different Parameters

TL;DR: A power reduction algorithm for sensor networks based on fuzzy logic and node movement that is able to predict if the node will leave the cluster by considering the moving speed of the sensor.
Book ChapterDOI

Correction, generalisation and validation of the max-min d-cluster formation heuristic

TL;DR: The first section of this paper simplifies and proves the correctness of the generalised algorithm to select clusterheads and the cluster formation process proposed in [2] is extensively studied and is proved to be false.
Proceedings Article

Bandwidth-constrained clustering in ad hoc networks

TL;DR: A survey of the basic mechanisms and properties of existing clustering algorithms for wireless ad hoc networks and a new algorithm with improved properties is proposed.
References
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