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https://hdl.handle.net/1959.11/26492
Title: | A Genetic Algorithm for Layered Multi-Source Video Distribution | Contributor(s): | Cheok, Lai-Tee (author) ; Eleftheriadis, Alexandros (author) | Publication Date: | 2005 | DOI: | 10.1117/12.596947 | Handle Link: | https://hdl.handle.net/1959.11/26492 | Abstract: | We propose a genetic algorithm -- MckpGen -- for rate scaling and adaptive streaming of layered video streams from multiple sources in a bandwidth-constrained environment. A genetic algorithm (GA) consists of several components: a representation scheme; a generator for creating an initial population; a crossover operator for producing offspring solutions from parents; a mutation operator to promote genetic diversity and a repair operator to ensure feasibility of solutions produced. We formulated the problem as a Multiple-Choice Knapsack Problem (MCKP), a variant of Knapsack Problem (KP) and a decision problem in combinatorial optimization. MCKP has many successful applications in fault tolerance, capital budgeting, resource allocation for conserving energy on mobile devices, etc. Genetic algorithms have been used to solve NP-complete problems effectively, such as the KP, however, to the best of our knowledge, there is no GA for MCKP. We utilize a binary chromosome representation scheme for MCKP and design and implement the components, utilizing problem-specific knowledge for solving MCKP. In addition, for the repair operator, we propose two schemes (RepairSimple and RepairBRP ). Results show that RepairBRP yields significantly better performance. We further show that the average fitness of the entire population converges towards the best fitness (optimal) value and compare the performance at various bit-rates. | Publication Type: | Conference Publication | Conference Details: | SPIE Image and Video Communications and Processing Conference, San Jose, United States of America, 17th January, 2005 | Source of Publication: | Proceedings of Electronic Imaging: Science and Technology, v.5685, p. 1086-1097 | Publisher: | SPIE Digital Library | Place of Publication: | United States of America | ISSN: | 0277-786X | Fields of Research (FoR) 2008: | 080108 Neural, Evolutionary and Fuzzy Computation | Socio-Economic Objective (SEO) 2008: | 970108 Expanding Knowledge in the Information and Computing Sciences | Peer Reviewed: | Yes | HERDC Category Description: | E1 Refereed Scholarly Conference Publication | Publisher/associated links: | http://spie.org/Publications/Proceedings/Paper/10.1117/12.596947?origin_id=x4325&start_volume_number=05600 | WorldCat record: | http://www.worldcat.org/oclc/839642717 |
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Appears in Collections: | Conference Publication School of Science and Technology |
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