Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Dandass, Yoginder
Committee Member
Ramkumar, Mahalingham
Committee Member
Banicescu, Ioana
Date of Degree
5-13-2006
Document Type
Graduate Thesis - Open Access
Major
Computer Science
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Computer Science and Engineering
Abstract
This research presents a hybrid algorithm that combines List Scheduling (LS) with a Genetic Algorithm (GA) for constructing non-preemptive schedules for soft real-time parallel applications represented as directed acyclic graphs (DAGs). The execution time requirements of the applications' tasks are assumed to be stochastic and are represented as probability distribution functions. The performance in terms of schedule lengths for three different genetic representation schemes are evaluated and compared for a number of different DAGs. The approaches presented in this research produce shorter schedules than HLFET, a popular LS approach for all of the sample problems. Of the three genetic representation schemes investigated, PosCT, the technique that allows the GA to learn which tasks to delay in order to allow other tasks to complete produced the shortest schedules for a majority of the sample DAGs.
URI
https://hdl.handle.net/11668/17315
Recommended Citation
Bugde, Amit, "A Study Of Genetic Representation Schemes For Scheduling Soft Real-Time Systems" (2006). Theses and Dissertations. 278.
https://scholarsjunction.msstate.edu/td/278