A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments

G. Ritchie; J. Levine

A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments

G. Ritchie
, J. Levine

Computer And Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

84 Downloads (Pure)

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. In this paper we describe an ant colony optimisation (ACO) algorithm that, when combined with local and tabu search, can find shorter schedules on benchmark problems than other techniques found in the literature.

Original language	English
Title of host publication	Proceedings of the 23rd Workshop of the UK Planning and Scheduling Special Interest Group
Number of pages	7
Publication status	Published - 1 Dec 2004

Keywords

hybrid ant algorithm
heterogeneous computing environments
ant colony optimization

Access to Document

10Submitted manuscript, 77.1 KB

Cite this

@inproceedings{825d72c511aa49a3a874aedf6215f2cd,

title = "A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments",

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. In this paper we describe an ant colony optimisation (ACO) algorithm that, when combined with local and tabu search, can find shorter schedules on benchmark problems than other techniques found in the literature.",

keywords = "hybrid ant algorithm, heterogeneous computing environments, ant colony optimization",

author = "G. Ritchie and J. Levine",

year = "2004",

month = dec,

day = "1",

language = "English",

booktitle = "Proceedings of the 23rd Workshop of the UK Planning and Scheduling Special Interest Group",

}

TY - GEN

T1 - A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments

AU - Ritchie, G.

AU - Levine, J.

PY - 2004/12/1

Y1 - 2004/12/1

N2 - 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. In this paper we describe an ant colony optimisation (ACO) algorithm that, when combined with local and tabu search, can find shorter schedules on benchmark problems than other techniques found in the literature.

AB - 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. In this paper we describe an ant colony optimisation (ACO) algorithm that, when combined with local and tabu search, can find shorter schedules on benchmark problems than other techniques found in the literature.

KW - hybrid ant algorithm

KW - heterogeneous computing environments

KW - ant colony optimization

M3 - Conference contribution book

BT - Proceedings of the 23rd Workshop of the UK Planning and Scheduling Special Interest Group

ER -

A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments

Abstract

Keywords

Access to Document

Fingerprint

Cite this