Abstract
Grid computing is a newly developed technology for complex systems with large-scale resource sharing, wide-area communication, and multi-institutional collaboration. Grid scheduling is an important infrastructure in the grid computing environment. Most of the existing grids scheduling methods focus on maximizing processor utilization without taking grid load into consideration. This may lead to significant inefficiencies in performance such as large job queues and processing delays. In this paper, we propose a multiagent-based scheduling system for computational grids with a new approach. Agent technology is suitable for a computational grid because of the dynamic, heterogeneous, and autonomous nature of the grid. The main idea of the proposed system is a combination of a static scheduling using a fixed scheduling algorithm and a dynamic adjustment through the autonomous behavior of agents. The superiority of the proposed system, in reducing the load of the grid and minimizing the response time for executing user applications, is demonstrated by simulation experiments.
Similar content being viewed by others
References
A. Gounaris, “Resource Scheduling for Parallel Query Processing on Computational Grids,” in Proceeding of International Conference on Grid Computing. Pittsburgh, USA, 2004).
H. Casanova, “Distributed Computing Research Issues in Grid Computing,” ACM SIGACT News J. Sep. 33, 50–70 (2002).
P. Huang, H. Peng, P. Lin, et al., “Static Strategy and Dynamic Adjustment: An Effective Method for Grid Task Scheduling,” J. Future Generation Computer Systems 25, 884–892 (2009).
L. Lu and S. Yang, “DIRSS-G: An Intelligent Resource Scheduling System for Grid Environment Based on Dynamic Pricing,” Int. J. Information Technology 12(4), 120–127 (2006).
L. Chunlin, Z. J. Xiu, and L. Layuan, “Resource Scheduling with Conflicting Objectives in Grid Environments: Model and Evaluation,” J. Network and Computer Applications 32, 760–769 (2009).
K. Ranganathan and I. Foster, “Simulation Studies of Computation and Data Scheduling Algorithms for Data Grids,” J. Grid Computing 1, 53–62 (2003).
J. Cao, “ARMS: An Agent-Based Resource Management System for Grid Computing,” Scientific Programming, Special Issue on Grid Computing 10(2), 135–148 (2002).
K. Krauter, R. Buyya, and M. Maheswaran, “A Taxonomy and Survey of Grid Resource Management Systems,” Software: Practice and Experience 32(2), 135–164 (2002).
Chi-Yu Huang, Colin Pattinson, “Using Mobile Agent Techniques for Distributed Manufacturing Network Management,” in Proceedings PGNet 2nd Annual Conference Liverpool, UK, 2001.
B. Fechner, U. Honig, J. Keller, et al., “Fault-Tolerant Static Scheduling for Grids,” in Proceedings of IPDOS Conference, Miami, Florida, USA, 2008.
H. A. James, “Scheduling in Metacomputing Systems,” Ph.D. Thesis, Department of Computer Science, University of Adelaide, Australia (1999).
S. Mary, S. Bhanu, and N. P. Gopalan, “A Hyper-Heuristic Approach for Efficient Resource Scheduling in Grid,” IJCCC Int. J. Computers, Communications and Control III(3), 249–258 (2008).
R. Moreno and A. B. Conde, “Job Scheduling and Resource Management Techniques in Economic Grid Environments,” Lect. Notes Comp. Sci. 2970, 25–32 (2004).
R. Pfeifer and C. Scheier, Understanding Intelligence (MIT Press, 1999).
G. Weiss, “Multiagent Systems,” in A Modern Approach to Distributed Artificial Intelligence (MIT Press, 1999).
M. Wooldridge, An Introduction to Multiagent Systems (Wiley, 2002).
S. Franklin and A. Graesser, “Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents,” in Proceedings of 3rd International Workshop on Agent Theories. Architectures, and Languages (Springer-Verlag, 1996).
F. Bellifemine, A. Poggi, and G. Rimassa, “Developing Multi Agent Systems with a FIPA-Compliant Agent Framework,” Software Practice Experience 31, 103–128 (2001).
D. M. Chess, Itinerant Agent for Mobile Computing, Technical Report, IBM Corporation (New York, 1995).
N. J. E. Wijngaards, “Supporting Internet-Scale Multi-Agent Systems,” Data Knowledge Engineering 41(2–3), 229–245 (2002).
A4 Project. http://www.ccrl-nece.de/~cao/A4/.
C. Sungjin, “Mobile Agent Based Adaptive Scheduling Mechanism in Peer to Peer Grid Computing,” in Proceedings of International Conference on Computational Science and Its Applications, ICCSA’2005, 2005, LNCS 3483, May 2005, pp. 936–947.
S. S. Manvi and M. N. Birje, “An Agent-Based Resource Allocation Model for Grid Computing,” in Proceedings of IEEE International Conference on Services Computing (SCC’05), Orlando, Florida, USA, 2005.
S. Choi, “Adaptive Group Scheduling Mechanism Using Mobile Agents in Peer-to-Peer Grid Computing Environment,” Applied Intelligence, Special Issue on Agent-based Grid Computing 25(2), 199–221 (2006).
R. Buyya, D. Abramson, and J. Giddy, “Nimrod-G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid,” in Proceedings of International Conference and Exhibition on High Performance Computing in Asia-Pacific Region (HPC Asia 2000), Bejing, China, 2000.
R. Buyya and M. Murshed, “GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing,” J. Concurrency and Computation: Practice and Experience 14 (2002).
R. S. Chang, J. S. Chang, and P. S. Lin, “An Ant Algorithm for Balanced Job Scheduling in Grids,” J. Future Generation Computer Systems 25, 20–27 (2009).
Author information
Authors and Affiliations
Corresponding author
Additional information
The article is published in the original.
Rights and permissions
About this article
Cite this article
Altameem, T., Amoon, M. An agent-based approach for dynamic adjustment of scheduled jobs in computational grids. J. Comput. Syst. Sci. Int. 49, 765–772 (2010). https://doi.org/10.1134/S1064230710050114
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1064230710050114