Colony of cooperating agents based independent job scheduling in a computation grid
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 7 June 2011
Abstract
Purpose
Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding the diversity of available resources among different jobs in the grid. However, the major problem is the optimal job scheduling for heterogeneous resources, in which each job needs to be allocated to a proper grid's node with the appropriate resources. An important challenge is to solve optimally the scheduling problem, because the capability and availability of resources vary dynamically and the complexity of scheduling increases with the size of the grid. The purpose of this paper is to present a framework which combines the fuzzy C‐mean (FCM) clustering with an ant colony optimization (ACO) algorithm to improve the scheduling decision when the grid is heterogeneous.
Design/methodology/approach
In the proposed model, the FCM algorithm classifies the jobs into appropriate classes, and the ACO algorithm maps the jobs to the appropriate resources. The ACO is characterized by ant‐like mobile agents that cooperate and stochastically explore a network, iteratively building solutions based on their own memory and on the traces (pheromone levels) left by other agents.
Findings
The simulation is done by using historical information on jobs in a grid. The experimental results show that the proposed algorithm can allocate jobs more efficiently and more effectively than the traditional algorithms for scheduling policies.
Originality/value
The paper provides a scheduling model based on FCM clustering and ACO algorithm for grid scheduling. The authors compared the performance of the proposed algorithm with the performance of various job‐scheduling algorithms in the grid computing environment. The comparison results show that the proposed algorithm outperforms other algorithms and gives optimal results.
Keywords
Citation
Helmy, T. and Rasheed, Z. (2011), "Colony of cooperating agents based independent job scheduling in a computation grid", International Journal of Intelligent Computing and Cybernetics, Vol. 4 No. 2, pp. 243-264. https://doi.org/10.1108/17563781111136720
Publisher
:Emerald Group Publishing Limited
Copyright © 2011, Emerald Group Publishing Limited