Name
Abstract | ||
|---|---|---|
Nowadays, scientists and companies are confronted with multiple competing goals such as makespan in high-performance computing and economic cost in Clouds that have to be simultaneously optimized. Multi-objective scheduling of scientific workflows in distributed systems is therefore receiving increasing research attention. Most existing approaches typically aggregate all objectives in a single function, defined a-priori without any knowledge about the problem being solved, which negatively impacts the quality of the solutions. In contrast, Pareto-based approaches having as outcome a set of several (nearly-) optimal solutions that represent a tradeoff among the different objectives, have been scarcely studied. In this paper, we propose a new Pareto-based list scheduling heuristic that provides the user with a set of tradeoff optimal solutions from where the one that better suits the user requirements can be manually selected. We demonstrate the potential of MOHEFT for a bi-objective scheduling problem that optimizes makespan and economic cost in a Cloud-based computing scenario. We compare MOHEFT with two state-of-the-art approaches using different synthetic and real-world workflows: the classical HEFT algorithm used in single-objective scheduling and the SPEA2∗ genetic algorithm used for multi-objective optimisation problems. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CloudCom.2012.6427573 | CloudCom |
Keywords | Field | DocType |
Pareto analysis,cloud computing,parallel processing,workflow management software,MOHEFT,Pareto-based list scheduling heuristic,biobjective scheduling problem,cloud-based computing scenario,distributed systems,economic cost,high-performance computing,multiobjective heterogeneous earliest finish time,multiobjective list-based method,multiobjective scientific workflow scheduling,multiple competing goals,optimal solutions | Job shop scheduling,Fair-share scheduling,Computer science,Flow shop scheduling,Two-level scheduling,Nurse scheduling problem,Real-time computing,Rate-monotonic scheduling,Earliest deadline first scheduling,Dynamic priority scheduling,Distributed computing | Conference |
Citations | PageRank | References |
13 | 0.61 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan J. Durillo | 1 | 747 | 25.47 |
| Radu Prodan | 2 | 2314 | 152.27 |
| Hamid Mohammadi Fard | 3 | 168 | 7.21 |