Scheduling shared data acquisition for real-time decision making
Cheng, Tai-Sheng
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https://hdl.handle.net/2142/105267
Description
Title
Scheduling shared data acquisition for real-time decision making
Author(s)
Cheng, Tai-Sheng
Issue Date
2019-04-25
Director of Research (if dissertation) or Advisor (if thesis)
Abdelzaher, Tarek
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Real-time Scheduling
Data Freshness
Abstract
This work investigates scheduling policies for the acquisition of possibly overlapping sets of data items required to make multiple decisions by different deadlines. The work is motivated by military IoT applications in which a large number of sensors must collect intelligence data needed to make multiple decisions. For example, data from several cameras in a contested city might be needed to decide where targets of interest are. This work is based on the assumption that network bandwidth is limited, creating a significant resource bottleneck (perhaps between the sensors and the command center where decisions are made). This might be the case, for example, due to active interference by a determined adversary.
A relieved sub-problem is first discussed with a corresponding optimal algorithm. Then, an improved heuristic algorithm based on the insights from the optimal algorithm of the sub-problem is presented. Finally, the new algorithm is evaluated with multiple scheduling parameters and is compared with previous heuristics, demonstrating an improved performance of our solution.
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