Master of Science / Department of Computing and Information Sciences / Gurdip Singh / Wireless sensor networks are characterized by severe energy constraints, one to many
flows and low rate redundant data. Most of the routing algorithms for traditional networks
are address centric, and the ad hoc nature of wireless sensor network makes them unsuitable
for practical applications. Also the algorithms designed for mobile ad hoc networks are
unsuitable for wireless sensor networks due to severe energy constraints that require nodes to
perform for months with limited resources, as well as the low data rate which the constraint
implies.
This thesis examines a model driven data gathering algorithm framework for wireless
sensor networks. It was designed with a goal to decrease the overall cost in transmission
by lowering the number of messages transmitted in the network. A combination of data-
centric and address-centric approaches was used as guidelines during the design process. A
shortest path heuristic where intermediate nodes forward interest messages whenever it is
of lower cost is one of the heuristics used. Another heuristic used is the greedy incremental
approach to build a lower cost tree from a graph with various producers and consumers. A
cost division heuristic is used to divide cost of shared path into distinct paths as the path
forks in a tree.
This thesis analyzes the effects of these heuristics on the performance of the algorithm
and how it lowers the overall cost with the addition of each heuristic.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/540 |
| Date | January 1900 |
| Creators | Kunnamkumarath, Dhinu Johnson |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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