Multi-Objective Genetic Algorithm for Task Assignment on Heterogeneous Nodes. (19th January 2012)

• Record Type: Journal Article
• Authors: del Notario, Carolina Blanch Perez; Baert, Rogier; D'Hondt, Maja
• Other Names: He Yifeng Academic Editor.
• Is Part Of: International journal of digital multimedia broadcasting. Volume 2012(2012)
• Publication Date: 2012-01-19
• Subjects: Multimedia communications -- Periodicals; Digital audio broadcasting -- Periodicals; Mobile communication systems -- Periodicals; Digital audio broadcasting; Mobile communication systems; Multimedia communications; Periodicals; 621.382
• DOI: 10.1155/2012/716780
• Languages: English
• ISSNs: 1687-7578

Abstract

Abstract : Task assignment in grid computing, where both processing and bandwidth constraints at multiple heterogeneous devices need to be considered, is a challenging problem. Moreover, targeting the optimization of multiple objectives makes it even more challenging. This paper presents a task assignment strategy based on genetic algorithms in which multiple and conflicting objectives are simultaneously optimized. Specifically, we maximize task execution quality while minimizing energy and bandwidth consumption. Moreover, in our video processing scenario; we consider transcoding to lower spatial/temporal resolutions to tradeoff between video quality; processing, and bandwidth demands. The task execution quality is then determined by the number of successfully processed streams and the spatial-temporal resolution at which they are processed. The results show that the proposed algorithm offers a range of Pareto optimal solutions that outperforms all other reference strategies.