TY - GEN
T1 - A prediction-based real-time scheduling advisor
AU - Dinda, Peter A
N1 - Funding Information:
Effort sponsored by the National Science Foundation under Grants ANI-0093221, ACI-0112891, and EIA-0130869.
Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - The real-time scheduling advisor (RTSA) is an entirely user-level system that an application running on a typical shared, unreserved distributed computing environment can turn to for advice on how to schedule its compute-bound soft real-time tasks. Given a list of hosts, a description of the CPU demands of the task, the deadline, and a confidence level, the RTSA will recommend one of the hosts and predict, as a confidence interval, the running time of the task on that host. The RTSA is based on a scalable and extensible shared resource prediction system based on statistical time series analysis. The author first describes how the RTSA builds on this underlying system to provide its service, and then he evaluates its performance using a randomized methodology based on real background workloads, determining the effect of different factors. He also compares it with a random approach and a measurement-based approach.
AB - The real-time scheduling advisor (RTSA) is an entirely user-level system that an application running on a typical shared, unreserved distributed computing environment can turn to for advice on how to schedule its compute-bound soft real-time tasks. Given a list of hosts, a description of the CPU demands of the task, the deadline, and a confidence level, the RTSA will recommend one of the hosts and predict, as a confidence interval, the running time of the task on that host. The RTSA is based on a scalable and extensible shared resource prediction system based on statistical time series analysis. The author first describes how the RTSA builds on this underlying system to provide its service, and then he evaluates its performance using a randomized methodology based on real background workloads, determining the effect of different factors. He also compares it with a random approach and a measurement-based approach.
UR - http://www.scopus.com/inward/record.url?scp=84966586023&partnerID=8YFLogxK
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U2 - 10.1109/IPDPS.2002.1015480
DO - 10.1109/IPDPS.2002.1015480
M3 - Conference contribution
AN - SCOPUS:84966586023
T3 - Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002
SP - 88
EP - 95
BT - Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Parallel and Distributed Processing Symposium, IPDPS 2002
Y2 - 15 April 2002 through 19 April 2002
ER -