Load Sharing in Distributed Real-Time Systems with State-Change Broadcasts
IEEE Transactions on Computers
Job scheduling in the presence of multiple resource requirements
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
SETI@HOME—massively distributed computing for SETI
Computing in Science and Engineering
IEEE Transactions on Parallel and Distributed Systems
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Improving Performance via Computational Replication on a Large-Scale Computational Grid
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Heuristics for Scheduling Parameter Sweep Applications in Grid Environments
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A Heuristic Algorithm for Mapping Communicating Tasks on Heterogeneous Resources
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Distributed Job Scheduling on Computational Grids Using Multiple Simultaneous Requests
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Integrating Trust into Grid Resource Management Systems
ICPP '02 Proceedings of the 2002 International Conference on Parallel Processing
On Advantages of Grid Computing for Parallel Job Scheduling
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
A Study of Deadline Scheduling for Client-Server Systems on the Computational Grid
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Software—Practice & Experience
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CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
User group-based workload analysis and modelling
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Exploiting replication and data reuse to efficiently schedule data-intensive applications on grids
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Pro-active failure handling mechanisms for scheduling in grid computing environments
Journal of Parallel and Distributed Computing
A novel resource-driven job allocation scheme for desktop grid environments
TGC'10 Proceedings of the 5th international conference on Trustworthly global computing
Information Sciences: an International Journal
Enhanced Dynamic Hierarchical Replication and Weighted Scheduling Strategy in Data Grid
Journal of Parallel and Distributed Computing
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In this paper, we propose a novel distributed resource-scheduling algorithm capable of handling multiple resource requirements for jobs that arrive in a Grid computing environment. In our proposed algorithm, referred to as multiple resource scheduling (MRS) algorithm, we take into account both the site capabilities and the resource requirements of jobs. The main objective of the algorithm is to obtain a minimal execution schedule through efficient management of available Grid resources. We first propose a model in which the job and site resource characteristics can be captured together and used in the scheduling algorithm. To do so, we introduce the concept of a n-dimensional virtual map and resource potential. Based on the proposed model, we conduct rigorous simulation experiments with real-life workload traces reported in the literature to quantify the performance. We compare our strategy with most of the commonly used algorithms in place on performance metrics such as job wait times, queue completion times, and average resource utilization. Our combined consideration of job and resource characteristics is shown to render high-performance with respect to above-mentioned metrics in the environment. Our study also reveals the fact that MRS scheme has a capability to adapt to both serial and parallel job requirements, especially when job fragmentation occurs. Our experimental results clearly show that MRS outperforms other strategies and we highlight the impact and importance of our strategy.