Date of Award

Summer 8-2011

Degree Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Computing

Committee Chair

Sumanth Yenduri

Committee Chair Department

Computing

Committee Member 2

Louise Perkins

Committee Member 2 Department

Computing

Committee Member 3

John Harris

Committee Member 3 Department

Mathematics

Abstract

Energy efficiency is a vital part of wireless sensor networks (WSN). Using correct techniques, we can improve the overall data throughput of the network and, at the same time, cut down the cost of running it. The efficient utilization of the life of the sensor node in a WSN is a critical problem. This is a problem since the sensor nodes closest to the sink node expend more energy because they send more messages, mostly for routing, than any other node on the network.

This decreases the life of those sensor nodes and will lead to dead spots in the network. Having dead spots in the network lead to the eventual isolation of the sink node from various parts of the network. This isolation occurs if the node that is dying has no viable backups to reconnect to the sink on the network. We attempt to solve the problems of the WSN by distributing multiple sink nodes around the sensor field. This will enable us to utilize the network at its maximal capacity as the sensor nodes start to die off because of energy depletion, interference from nearby objects, or some type of mechanical failure. By adding multiple sink nodes, we will be able switch between the various sink nodes and choose the sink node that will yield the optimal network coverage after the initial sink node is no longer viable to service the network or cannot service the network optimally.

We will be exploring the switching of sink nodes in three ways. First we will switch the sink node when we can no longer reach 85% of the network. The second thing we will try to do is keep the network optimal by always using the sink node that has the farthest network reach. Finally, we will use a combination of highest percentage of network coverage combined with the highest areas of node density on the network to derive the optimal use of the network. This is a technique in which we have created called the Cluster Algorithm for Sink Selection (CASS). With these techniques we intend to extend the life of the network and also keep the cost of the network down.

Download

Share

COinS