Journal of Parallel and Distributed Computing
On an on-line scheduling problem for parallel jobs
Information Processing Letters
On-Line Load Balancing in a Hierarchical Server Topology
SIAM Journal on Computing
Evaluation of Job-Scheduling Strategies for Grid Computing
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
The ANL/IBM SP Scheduling System
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
A decoupled scheduling approach for the GrADS program development environment
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Comparison of Scheduling Heuristics for Grid Resource Broker
ENC '04 Proceedings of the Fifth Mexican International Conference in Computer Science
An Adaptive Generalized Scheduler for Grid Applications
HPCS '05 Proceedings of the 19th International Symposium on High Performance Computing Systems and Applications
An Adaptive Task Scheduling System for Grid Computing
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Workflows for e-Science: Scientific Workflows for Grids
Workflows for e-Science: Scientific Workflows for Grids
Backfilling Using System-Generated Predictions Rather than User Runtime Estimates
IEEE Transactions on Parallel and Distributed Systems
Resource Allocation Strategies in a 2-Level Hierarchical Grid System
ANSS-41 '08 Proceedings of the 41st Annual Simulation Symposium (anss-41 2008)
A novel multi-objective optimization scheme for grid resource allocation
Proceedings of the 6th international workshop on Middleware for grid computing
Model-based simulation and performance evaluation of grid scheduling strategies
Future Generation Computer Systems
Cooperation in multi-organization scheduling
Concurrency and Computation: Practice & Experience - Euro-Par 2007
Static strategy and dynamic adjustment: An effective method for Grid task scheduling
Future Generation Computer Systems
Grid broker selection strategies using aggregated resource information
Future Generation Computer Systems
On-line hierarchical job scheduling on grids with admissible allocation
Journal of Scheduling
A fast 5/2-approximation algorithm for hierarchical scheduling
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
Improving job scheduling algorithms in a grid environment
Future Generation Computer Systems
A taxonomy and survey on autonomic management of applications in grid computing environments
Concurrency and Computation: Practice & Experience
Two level job-scheduling strategies for a computational grid
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Towards transparent and distributed workload management for large scale web servers
Future Generation Computer Systems
A (2+ε)-approximation for scheduling parallel jobs in platforms
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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We evaluate job scheduling algorithms that integrate both tasks of Grid scheduling: job allocation to Grid sites and local scheduling at the sites. We propose and analyze an adaptive job allocation scheme named admissible allocation. The main idea of this scheme is to set job allocation constraints, and dynamically adapt them to cope with different workloads and Grid properties. We present 3-approximation and 5-competitive algorithms named MLB"a+PS and MCT"a+PS for the case that all jobs fit to the smallest machine, while we derive an approximation factor of 9 and a competitive factor of 11 for the general case. To show practical applicability of our methods, we perform a comprehensive study of the practical performance of the proposed strategies and their derivatives using simulation. To this end, we use real workload traces and corresponding Grid configurations. We analyze nine scheduling strategies that require a different amount of information on three Grid scenarios. We demonstrate that our strategies perform well across ten metrics that reflect both user- and system-specific goals.