Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Understanding intelligence
Developing multi-agent systems with a FIPA-compliant agent framework
Software—Practice & Experience
Introduction to Multiagent Systems
Introduction to Multiagent Systems
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Distributed computing research issues in grid computing
ACM SIGACT News
Supporting internet-scale multi-agent systems
Data & Knowledge Engineering - DKE 40
Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Remote Application Scheduling on Metacomputing Systems
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Resource Scheduling for Parallel Query Processing on Computational Grids
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
An Agent-based Resource Allocation Model for Grid Computing
SCC '05 Proceedings of the 2005 IEEE International Conference on Services Computing - Volume 01
ARMS: An agent-based resource management system for grid computing
Scientific Programming
An ant algorithm for balanced job scheduling in grids
Future Generation Computer Systems
Resource scheduling with conflicting objectives in grid environments: Model and evaluation
Journal of Network and Computer Applications
Static strategy and dynamic adjustment: An effective method for Grid task scheduling
Future Generation Computer Systems
Mobile agent based adaptive scheduling mechanism in peer to peer grid computing
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
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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.