Abstract

AbstractClustering is a fundamental mechanism used in the design of Wireless Sensor Network (WSN) protocols. The performance of WSNs can be improved by selecting the most suitable nodes to form a stable backbone structure with guaranteed network coverage. This paper proposes a base station-controlled centralized algorithm for static sensor networks and a distributed, weighted algorithm for dynamic sensor networks. The solutions are based on a (k,r)-Connected Dominating Set, which is suitable for cluster-based hierarchical routing. The clusterhead redundancy parameterkimproves reliability, the multi-hop parameterraddresses the scalability issue and the combined weight metric improves the network lifespan and reduces the number of re-affiliations. To create a stable and efficient backbone structure, the backbone sensor nodes are selected based on quality, which is a function of the residual battery power, node degree, transmission range, and mobility of the sensor nodes. Simulation experiments are conducted to evaluate the performance of both the algorithms in terms of the number of elements in the backbone structure, re-affiliation frequency, load balancing, network lifespan, and the power dissipation. The results establish the potential of these algorithms for use in WSNs.

Highlights

  • Development of wireless sensor networks (WSN) is enabled with the recent technological advancement in wireless communications, low-power consumption processors, and highly integrated digital electronics

  • These algorithms are based on a (k, r)-Connected Dominating Set (CDS) and the nodes for the construction of the B-structure are elected based on the residual battery power, node degree, transmission range, and mobility

  • In this paper, we propose the design of an adaptive clustering protocol, that is scalable, stable, adaptable, power efficient, and allows load balancing

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Summary

Introduction

Development of wireless sensor networks (WSN) is enabled with the recent technological advancement in wireless communications, low-power consumption processors, and highly integrated digital electronics. Bluetooth allows users to make ad hoc wireless connections between devices like mobile phones, desktop, or notebook computers without any cable. It supports uni-cast and multi-cast connections and uses the concept of master and slave. The use of networked system of sensors can limit the chance for personal interaction in the usually dangerous reconnaissance missions [3]

Background
Related work
The network model
Design parameters
The proposed protocols
Example
Analysis
Location learning
CDS-computation
Cluster formation and management
Findings
Load balancing

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