IMPROVING REAL-TIME DATA DISSEMINATION PERFORMANCE BY MULTI PATH DATA SCHEDULING IN DATA GRIDS
COMPUTING AND INFORMATICS, vol.34, no.2, pp.402-424, 2015 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 34 Issue: 2
- Publication Date: 2015
- Journal Name: COMPUTING AND INFORMATICS
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.402-424
- Keywords: Data scheduling, data grids, real-time systems, simulation, performance evaluation, APPROXIMATION ALGORITHMS, BANDWIDTH, SCIENCE, HEURISTICS, TRANSFERS, ADVANCE
- Anadolu University Affiliated: Yes
Abstract
The performance of data grids for data intensive, real-time applications is highly dependent on the data dissemination algorithm employed in the system. Motivated by this fact, this study first formally defines the real-time splittable data dissemination problem (RTS/DDP) where data transfer requests can be routed over multiple paths to maximize the number of data transfers to be completed before their deadlines. Since RTS/DDP is proved to be NP-hard, four different heuristic algorithms, namely kSP/ESMP, kSP/BSMP, kDP/ESMP, and kDP/BSMP are proposed. The performance of these heuristic algorithms is analyzed through an extensive set of data grid system simulation scenarios. The simulation results reveal that a performance increase up to 8 % as compared to a very competitive single path data dissemination algorithm is possible.