Date of Award
1-1-2021
Document Type
Dissertation
Degree Name
Ph.D. in Engineering Science
First Advisor
Feng Wang
Second Advisor
Dawn Wilkins
Third Advisor
Yixin Chen
Relational Format
dissertation/thesis
Abstract
As one of the latest advances in wireless sensor network (WSN), wireless visual sensor network (WVSN) bears a number of distinct features compared to its predecessor, mainly due to its directional visual coverage on the sensing field. This also renders previous solutions proposed for WSN may not work well for WVSN. For example, k-coverage has been introduced to WSNs for fault tolerance and high monitoring quality by omni-directional sensors but becomes incapable to cope with the directional coverage of sensors in WVSNs. Moreover, compared to scalar data in WSNs, visual data are much larger, difficult to aggregate and usually streamed in real-time, which also brings unprecedented challenges to data routing, load balance and traffic scheduling in the network. In this dissertation, we strive to tackle these issues with a top-down across layer approach. At the Application layer, we take an initial step to tackle 2-Angular-Coverage problem for WVSNs. To maximize the information captured by 2 visual sensors, we deploy the visual sensors from different directional angles and further extend the conventional concept of 2-coverage to ”2-angular-coverage”. With this as building block, we develop a greedy heuristic and an enhanced Depth First Search (DFS) algorithm to address 2-Angular-Coverage problem. At the Network layer, we note that the widely used tree topology in WSNs may yield sub-optimal results, and propose to optimally balance traffic load by using the full network topology, transforming it into a generalized max-flow problem and designing an efficient solution. Finally at the Link layer, we propose a Time Division Multiple Access (TDMA) based scheduling algorithm which is promising to achieve contention-free visual streaming data collection. The optimization information from upper layers will also be used for cross-layer optimization to further improve the quality of visual streaming and shorten the transmission delay.
Recommended Citation
Wang, Zhonghui, "Cross-Layer Optimization on Wireless Visual Sensor Networks for 3D Indoor Monitoring: A Top-Down Approach" (2021). Electronic Theses and Dissertations. 2181.
https://egrove.olemiss.edu/etd/2181
Concentration/Emphasis
Computer science