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ADAPTIVE CLUSTERING AND DATA AGGREGATION IN WIRELESS SENSOR NETWORKS (ACDA)

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Title: ADAPTIVE CLUSTERING AND DATA AGGREGATION IN WIRELESS SENSOR NETWORKS (ACDA)
Author: Sepehr, Babak
Department: School of Computer Science
Program: Computer Science
Advisor: McCuaig, Judi
Abstract: Wireless Sensor Networks (WSNs) are emerging ad hoc networks consist of small sensor nodes that sense, measure, observe, or monitor physical environmental phenomena. Sensors are small devices with limited computation power, limited bandwidth, and limited power supply. Power supply is a scarce, core resource in sensors. To address the core issue of power consumption, in this work, we propose a simple adaptive technique to pursue the purpose of saving energy in sensor nodes. The network lifetime is divided into different rounds and a probability, which is used to determine the cluster heads and clusters, is assigned to each node in a hierarchical manner by building the Bayesian Network for all sensor nodes. In each round the sensors’ probabilities are reassigned in response to the new network situation. The rounds and the changes of the probabilities give the system the advantage of adaptation while choosing cluster heads and forming clusters dynamically in reaction to the recent condition of the network and nodes.
Description: This thesis is written by Babak Sepehr in partial fulfillment of requirements for the degree of Master of Science in Computer Science in School of Computer science.
URI: http://hdl.handle.net/10214/7579
Date: 2013-10
Rights: Attribution 2.5 Canada
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Attribution 2.5 Canada Except where otherwise noted, this item's license is described as Attribution 2.5 Canada