The contract net protocol: high-level communication and control in a distributed problem solver
Distributed Artificial Intelligence
Parallel Computers Two: Architecture, Programming and Algorithms
Parallel Computers Two: Architecture, Programming and Algorithms
A Performance Study of Monitoring and Information Services for Distributed Systems
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Scalability Analysis of the Contract Net Protocol
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
A framework for adaptive execution in grids
Software—Practice & Experience
Benchmarking of high throughput computing applications on Grids
Parallel Computing
Tycoon: An implementation of a distributed, market-based resource allocation system
Multiagent and Grid Systems
Decentralised Resource Discovery Service for Large Scale Federated Grids
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
A Performance Model for Federated Grid Infrastructures
PDP '08 Proceedings of the 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008)
Job submission to grid computing environments
Concurrency and Computation: Practice & Experience - UK e-Science All Hands Meeting 2006
Model-based simulation and performance evaluation of grid scheduling strategies
Future Generation Computer Systems
A decentralized model for scheduling independent tasks in Federated Grids
Future Generation Computer Systems
Performance-based scheduling strategies for HTC applications in complex federated grids
Concurrency and Computation: Practice & Experience - Grid Computing, High Performance and Distributed Application
EGC'05 Proceedings of the 2005 European conference on Advances in Grid Computing
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The majority of non-coordinated decentralized meta-schedulers in a Federated Grid perform scheduling strategies without taking into account resources' current load or specific resource owners' internal demands, leading to suboptimal schedules. Clearly, these policies increase the number of job migrations, the number of messages generated per re-scheduled job, and also the application makespan. The main purpose of the present study is to analyze the effect of applying self-adjusting resource sharing policies to previously proposed performance based scheduling strategies. For example, when a resource is near saturation or has an internal peak demand, it can decide not to accept new external jobs. On the other hand, when a job owner receives the previous action, it can decide not to submit temporally more jobs to that resource. In this way, the proposed self-adjusting resource sharing policies save time and communication bandwidth by reducing the number of jobs migrations, and thus, avoiding the generation of the corresponding messages per re-scheduled job. At the same time, the new resource sharing strategies improve application makespan and resource performance objective functions while maintaining infrastructure owners complete autonomy.