A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Resource Management through Multilateral Matchmaking
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
A Heuristic Scheduling Strategy for Independent Tasks on Grid
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
Concurrency and Computation: Practice & Experience
Heuristic for resources allocation on utility computing infrastructures
Proceedings of the 6th international workshop on Middleware for grid computing
Comparison of Heuristics for Scheduling Independent Tasks on Heterogeneous Distributed Environments
CSO '09 Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization - Volume 01
Computational models and heuristic methods for Grid scheduling problems
Future Generation Computer Systems
Economic Grid Resource Scheduling Based on Utility Optimization
IITSI '10 Proceedings of the 2010 Third International Symposium on Intelligent Information Technology and Security Informatics
Improving job scheduling algorithms in a grid environment
Future Generation Computer Systems
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Grid systems have gained tremendous importance in past years since application requirements increased drastically. The heterogeneity and geographic dispersion of grid resources and applications place some difficult challenges such as job scheduling. A scheduling algorithm tries to find a resource for a job that fulfills the job's requirements while optimizing a given objective function. Utility is a measure of a user's satisfaction that can be seen as an objective function that a scheduler tries to maximize. Many utility functions have been proposed as an objective for scheduling algorithms. However, the proposed algorithms do not consider partial requirement satisfaction by awarding an utility based on the total fulfillment of the requirement. Most of them follow centralized or hierarchical approaches, suffering from scalability and fault tolerance problems. Our solution proposes a decentralized scheduling architecture with utility based scheduling algorithm that considers partial requirements satisfaction to overcome the shortcomings of actual solutions. Performance results show that user utility, submission and execution times are improved and a slightly more balanced system is achieved.