Optimizing execution time and cost while scheduling scientific workflow in edge data center with fault tolerance awareness
| Autor: | Kadum Muhanad Mohammed, Deng Xiaoheng |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Nonlinear Engineering, Vol 13, Iss 1, Pp 2370-82 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2192-8029 2024-0015 |
| DOI: | 10.1515/nleng-2024-0015 |
| Popis: | Scheduling scientific workflows is essential for edge data centers operations. Fault tolerance is a crucial focus in workflow scheduling (WS) research. This study proposed fault-tolerant WS in edge data centers using Task Prioritization Adaptive Particle Swarm Optimization (TPAPSO). The aim is to minimize the Makespan, execution costs, and overcoming failures at all workflow processing stages, including when virtual machines are insufficient or tasks fail. The approach proposes three components: initial heuristic list, scheduling tasks with TPAPSO, and implementing performance monitoring with fault tolerance (PMWFT). TPAPSO-PMWFT is simulated using CloudSim 4.0. The experiments indicate that the suggested approach shows superior results compared to existing methods. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|