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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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Clustering and Data collection in Wireless Sensor network using Dual Data Uploading

Sonali Gadwar, +1 more
TL;DR: In this article, a three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called SenCar) layer.
Proceedings ArticleDOI

Scalable, Opportunistic, Energy Efficient Routing (SOEER) - A Novel Clustering Approach for Wireless Sensor Networks

TL;DR: A new clustering algorithm Scalable, Opportunistic, Energy Efficient Routing (SOEER) is presented in this paper, for improving the energy efficiency, life time, Packet Delivery Ratio and throughput of network.

Efficient channel allocation and medium access organization algorithms for vehicular networking

TL;DR: This document summarizes the findings of a post-mortem examination conducted at the request of the United States Department of Justice in connection with the death of American swimmer and Olympic gold medallist Michael Phelps at the 2016 Rio Games.
Journal ArticleDOI

Power Consumption Characteristics of Autonomous Decentralized Clustering Based on Local Interaction

TL;DR: This study proposes an autonomous decentralized structure formation technology based on local interaction, and applies it to implement autonomous decentralized clustering on MANETs, and configure clusters using the proposed method, the back-diffusion method, and a bio-inspired method which cannot reflect the network condition.
Journal ArticleDOI

A Study of Load Tolerance Node using Load-balance in Mobile Ad hoc Networks

TL;DR: The proposed Load Tolerance algorithm improves packet delivery ratio in cluster routing by sending a message by selected load tolerance node when cluster member node can’t send a message to cluster head node that exceed load-balancing.
References
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Proceedings ArticleDOI

Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers

TL;DR: The modifications address some of the previous objections to the use of Bellman-Ford, related to the poor looping properties of such algorithms in the face of broken links and the resulting time dependent nature of the interconnection topology describing the links between the Mobile hosts.
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Approximation algorithms for combinatorial problems

TL;DR: For the problem of finding the maximum clique in a graph, no algorithm has been found for which the ratio does not grow at least as fast as n^@e, where n is the problem size and @e>0 depends on the algorithm.
Proceedings ArticleDOI

A highly adaptive distributed routing algorithm for mobile wireless networks

TL;DR: The proposed protocol is a new distributed routing protocol for mobile, multihop, wireless networks that is highly adaptive, efficient and scalable; being best-suited for use in large, dense, mobile networks.
Journal ArticleDOI

Multicluster, mobile, multimedia radio network

TL;DR: A multi-cluster, multi-hop packet radio network architecture for wireless adaptive mobile information systems is presented that supports multimedia traffic and relies on both time division and code division access schemes.
Journal ArticleDOI

A design concept for reliable mobile radio networks with frequency hopping signaling

TL;DR: This paper outlines those features that distinguish the High Frequency (HF) Intra Task Force (ITF) Network from other packet radio networks, and presents a design concept for this network that encompasses organizational structure, waveform design, and channel access.
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