Type
Text
Type
Dissertation
Advisor
Advisor: Robertazzi, Thomas | Committee members: Tang, Wendy; Hong, Sangjin; Skiena, Steven
Date
2020-05-01
Keywords
Signal Searching
Department
Department of Electrical and Computer Engineering
Language
en
Source
This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.
Identifier
https://hdl.handle.net/11401/79110
Publisher
The Graduate School, Stony Brook University: Stony Brook, NY.
Format
application/pdf
Abstract
Signature searching is the process of finding a signature “pattern” of interest in a data file. Signature searching can be found in many applications such as radar, sensor and data processing. The objective of this research is to provide approaches for optimal signature searching. The plan is to study the signature searching optimization problem from multiple aspects such as mathematical programming, divisible load scheduling and topology. The focus of this research is sensor applications. An active sensor emits signals for detection and information acquisition purposes. Optimal sensing means the best sensing quality with the least time and energy cost, which allow processing more data. Intuitively, optimal sensing leads to optimal signature searching. This dissertation presents novel work by using an integer linear programming “algorithm” to achieve the optimal sensing by selecting the best possible number of signals of a type or a combination of multiple types to ensure the best sensing quality possible considering all given constraints. Then, a solution based on a heuristic algorithm is implemented to improve the performance. Finally, an optimal processing method is presented. The considered processing methods are local computing, cloud computing or a combination of both methods. | 103 pages
Recommended Citation
Alqarni, Abdulaziz, "Optimal Signature Searching" (2020). Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions). 3973.
https://commons.library.stonybrook.edu/stony-brook-theses-and-dissertations-collection/3973