Operating systems (3rd ed.): internals and design principles
Operating systems (3rd ed.): internals and design principles
Modern Operating Systems
G-commerce: Market Formulations Controlling Resource Allocation on the Computational Grid
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Design and Evaluation of a Resource Selection Framework for Grid Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Market-based Proportional Resource Sharing for Clusters
Market-based Proportional Resource Sharing for Clusters
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
A distributed backup agent based on grid computing architecture
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
A dynamic supervising model based on grid environment
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Authentication algorithm based on grid environment
ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
A Process Scheduling Analysis Model Based on Grid Environment
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
Processing certificate of authorization with watermark based on grid environment
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part II
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Grid computing architecture was defined to be a complete physical layer. The functions of information systems based on grid architecture are resources sharing, collaborative processing, etc. Resources are used by processes. System performance is calculated from resources usages. Process scheduling is more important when jobs are not uniformly distributed in all grid nodes. In this paper, we proposed a process schedule analyzing model based on grid computing architecture. This model can make all grid nodes be loading-balance. When the load of the node is heavy, it can select the other grid nodes to execute its job by the verification of supervisor grid node and then the job is transferred. Via implementing this model, we can have the best system performance.