The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
A data intensive distributed computing architecture for “grid” applications
Future Generation Computer Systems - Special issue on high performance computing and networking Europe 1999
The DEVS Environment for High-Performance Modeling and Simulation
IEEE Computational Science & Engineering
Architectural Models for Resource Management in the Grid
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
A Case for Economy Grid Architecture for Service-Oriented Grid Computing
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
User Demand Prediction-Based Resource Management Model in Grid Computing Environment
ICHIT '08 Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology
| Hi-index | 0.00 |
The intelligent agent works powerful jobs for handling system complexity and making systems more modular. Especially a reasoning agent is effective on organizing for decision-making process of systems. This paper introduces an Ontology-based Intelligent Agent for a Grid Resource Management System (OIAGRMS), which uses ontology reasoning to select a suitable resource supplier, is proposed. This paper focuses on effective grid resource management and the improvement of resource utilization through transaction management for the OIAGRMS. For performance evaluation with accuracy and reliability, the OIAGRMS is compared with the Prediction-based Agent for Grid Resource Management System(PAGRMS) and the Random-based Agent for Grid Resource Management System(RAGRMS). The OIAGRMS recorded over 90 percents trade success, but the PAGRMS and RAGRMS recorded less than a 90 percents trade success. In comparing of resource utilization rate, maximum deviation, standard deviation, the OIAGRMS were about 9.4 and 9.8 percents but the PAGRMS are about 22.9 and 16.3 percents, the RAGRMS were about 61.6 and 21.7 percents. The empirical results demonstrate the usefulness and improvement utilization with stable performances of the intelligent agent base on ontology reasoning in grid environment.