JOMP—an OpenMP-like interface for Java
Proceedings of the ACM 2000 conference on Java Grande
A framework for adaptive execution in grids
Software—Practice & Experience
A multi-layer resource reconfiguration framework for grid computing
Proceedings of the 4th international workshop on Middleware for grid computing
A Multi-agent Framework for Resource Brokering of Multiple Concurrent Jobs in Grid Environment
ISPDC '06 Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing
Self-adaptive applications on the grid
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Adaptive performance control for distributed scientific coupled models
Proceedings of the 21st annual international conference on Supercomputing
Implementation of a Resource Broker for Efficient Resource Management in Grid Environment
ADCOM '07 Proceedings of the 15th International Conference on Advanced Computing and Communications
Optimizing resource allocation for multiple concurrent jobs in grid environment
ICPADS '07 Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 02
Feedback-Guided Analysis for Resource Requirements in Large Distributed System
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Future Generation Computer Systems
Resource requirement prediction using clone detection technique
Future Generation Computer Systems
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In a computational grid, jobs must adapt to the dynamically changing heterogeneous environment with an objective of maintaining the quality of service. In order to enable adaptive execution of multiple jobs running concurrently in a computational grid, we propose an integrated performance-based resource management framework that is supported by a multi-agent system (MAS). The multi-agent system initially allocates the jobs onto different resource providers based on a resource selection algorithm. Later, during runtime, if performance of any job degrades or quality of service cannot be maintained for some reason (resource failure or overloading), the multi-agent system assists the job to adapt to the system. This paper focuses on a part of our framework in which adaptive execution facility is supported. Adaptive execution facility is availed by reallocation and local tuning of jobs. Mobile, as well as static agents are employed for this purpose. The paper provides a summary of the design and implementation and demonstrates the efficiency of the framework by conducting experiments on a local grid test bed.