Award Date
1-1-2007
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Committee Member
Ajoy K. Datta
Number of Pages
83
Abstract
Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors' internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors' variables at a time, instead of reading all neighbors' variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms.
Keywords
Covering; Distributed; Networks; Query; Region; Self; Sensor
Controlled Subject
Computer science
File Format
File Size
2252.8 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Permissions
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Repository Citation
Yamazaki, Ai, "Self-* distributed query region covering in sensor networks" (2007). UNLV Retrospective Theses & Dissertations. 2199.
http://dx.doi.org/10.25669/dr3w-6xca
Rights
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