Application of Real-Time Monitoring to Scheduling Tasks with Random Execution Times
IEEE Transactions on Software Engineering
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Advanced Fractal Programming in C - with Disk
Advanced Fractal Programming in C - with Disk
The Distributed Monitor System of TOPSYS
CONPAR 90/VAPP IV Proceedings of the Joint International Conference on Vector and Parallel Processing
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A Grid service broker for scheduling e-Science applications on global data Grids: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
Fair resource sharing in hierarchical virtual organizations for global grids
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
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In this paper, we developed a framework for efficient resource management within the grid service environment. For considering the grid service architecture and functions, the resource management is the most important to grid service; therefore, GridRMF (Grid Resource Management Framework) is modeled and developed in order to respond to such variable characteristics of resources as accordingly as possible. GridRMF uses the participation level of grid resource as a basis of its hierarchical management. This hierarchical management divides managing domains into two parts: VMS (Virtual Organization Management System) for virtual organization management and RMS (Resource Management System) for metadata management. VMS mediates resources according to optimal virtual organization selection mechanism, and responds to malfunctions of the virtual organization by LRM (Local Resource Manager) automatic recovery mechanism. RMS, on the other hand, responds to load balance and fault by applying resource status monitoring information into adaptive performance-based task allocation algorithm.