Security-Driven Heuristics and A Fast Genetic Algorithm for Trusted Grid Job Scheduling
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Risk-Resilient Heuristics and Genetic Algorithms for Security-Assured Grid Job Scheduling
IEEE Transactions on Computers
Selfish Grids: Game-Theoretic Modeling and NAS/PSA Benchmark Evaluation
IEEE Transactions on Parallel and Distributed Systems
WaveGrid: a scalable fast-turnaround heterogeneous peer-based desktop grid system
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Wave scheduler: scheduling for faster turnaround time in peer-based desktop grid systems
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Pitfalls in parallel job scheduling evaluation
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Cluster computing on the fly: P2P scheduling of idle cycles in the internet
IPTPS'04 Proceedings of the Third international conference on Peer-to-Peer Systems
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Current job scheduling systems for massively parallel machines and Beowulf-class compute clusters support batch scheduling involving two classes of queues: prime time vs. non-prime time. Jobs running in these queue classes must satisfy different criteria with respect to job-size, runtime, or other resource needs. These constraints are designed to delay big jobs to non-prime time in order to provide better quality service during the prime time work-day hours.This paper surveys existing prime time/non-prime time scheduling policies and investigates the sensitivity of scheduling performance to changes in the jobsize and run-time limits allowed during prime time vs. non-prime time. Our simulation study, using real workload traces from theNASA NAS IBM SP/2 cluster, gives strong evidence for the use of specific prime time limits and sheds light on the per-formance trade-offs regarding response times, utilization, short term scheduling algorithm (FCFS vs. EASY backfilling), and success and overflow rates.