Abstract
The efficient scheduling of independent computational jobs in a heterogeneous computing (HC) environment is an important problem in domains such as grid computing. Finding optimal schedules for such an environment is (in general)
an NP-hard problem, and so heuristic approaches must be used. Work with other NP-hard problems has shown that solutions found by heuristic algorithms can often be improved by applying local search procedures to the solution found. This paper describes a simple but effective local search procedure for scheduling independent jobs in HC environments which, when combined with fast construction heuristics, can
find shorter schedules on benchmark problems than other solution techniques found in the literature, and in significantly less time.
an NP-hard problem, and so heuristic approaches must be used. Work with other NP-hard problems has shown that solutions found by heuristic algorithms can often be improved by applying local search procedures to the solution found. This paper describes a simple but effective local search procedure for scheduling independent jobs in HC environments which, when combined with fast construction heuristics, can
find shorter schedules on benchmark problems than other solution techniques found in the literature, and in significantly less time.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 22nd Workshop of the UK Planning and Scheduling Special Interest Group |
| Number of pages | 6 |
| Publication status | Published - 1 Dec 2003 |
Keywords
- heterogeneous computing environments
- grid computing
- heuristic algorithms
- solution techniques