A model driven data gathering algorithm for Wireless Sensor Networks

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dc.contributor.author Kunnamkumarath, Dhinu Johnson
dc.date.accessioned 2008-01-11T15:31:56Z
dc.date.available 2008-01-11T15:31:56Z
dc.date.issued 2008-01-11T15:31:56Z
dc.identifier.uri http://hdl.handle.net/2097/540
dc.description.abstract 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. en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject Wireless Sensor Networks en
dc.subject Heuristics en
dc.subject Data gathering en
dc.title A model driven data gathering algorithm for Wireless Sensor Networks en
dc.type Thesis en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Computing and Information Sciences en
dc.description.advisor Gurdip Singh en
dc.subject.umi Computer Science (0984) en
dc.date.published 2008 en
dc.date.graduationmonth May en

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