Seven good reasons for mobile agents
Communications of the ACM
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Profile Driven Scheduling for a Heterogeneous Server Cluster
ICPPW '05 Proceedings of the 2005 International Conference on Parallel Processing Workshops
Scheduling of scientific workflows in the ASKALON grid environment
ACM SIGMOD Record
Journal of Parallel and Distributed Computing
Dynamic Grid tasks composition and distribution through agents: Research Articles
Concurrency and Computation: Practice & Experience - First International Workshop on Emerging Technologies for Next-generation GRID (ETNGRID 2004)
Relative Performance of Scheduling Algorithms in Grid Environments
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Scheduling strategies for mapping application workflows onto the grid
HPDC '05 Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium
An adaptive scheduling method for grid computing
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
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
Multi-Criteria Job Scheduling in Grid Using an Accelerated Genetic Algorithm
Journal of Grid Computing
Security Driven Scheduling Model for Computational Grid Using NSGA-II
Journal of Grid Computing
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Computational Grids (CGs) have become an appealing research area. They suggest a suitable environment for developing large scale parallel applications. CGs integrate a huge mount of distributed heterogeneous resources for constituting a powerful virtual supercomputer. Scheduling is the most important issue for enhancing the performance of CGs. Various strategies have been introduced, including static and dynamic behaviors. The former maps tasks to resources at submission time, while the latter operates at run time. While static scheduling is unsuitable for the dynamic Grid environment, scheduling in CGs is still more complex than the proposed dynamic solutions. This paper introduces a decentralized Adaptive Grid Scheduler (AGS) based on a novel rescheduling mechanism. AGS has several salient properties as it is; hybrid, adaptive, decentralized, and efficient. Also, AGS is a robust mechanism as it has the ability to; (i) detect resource failures, (ii) continue its functionality in spite of the failure existence, then (iii) recover back. Moreover, it integrates both static and dynamic scheduling behaviors. An initial static scheduling map is proposed for an input Direct Acyclic Graph (DAG). However, DAG tasks may be rescheduled if the performance of the allocated resources changes in away that may affect the tasks' response time. AGS overcomes drawbacks of traditional schedulers by utilizing the mobile agent unique features to enhance the resource discovery and monitoring processes. Experimental results have shown that AGS outperforms traditional Grid schedulers as it introduces a better scheduling efficiency.