Computationally feasible bounds for partially observed Markov decision processes
Operations Research
The mathematics of product form queuing networks
ACM Computing Surveys (CSUR)
Modeling video sources for real-time scheduling
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Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
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Journal of the ACM (JACM)
Fairness and efficiency in web server protocols
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Classifying scheduling policies with respect to unfairness in an M/GI/1
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Scheduling Correlated Broadcast Data Considering Access Frequencies with Temporal Variations
NCA '03 Proceedings of the Second IEEE International Symposium on Network Computing and Applications
The impact of the service discipline on delay asymptotics
Performance Evaluation - Modelling techniques and tools for computer performance evaluation
Energy-Aware Modeling and Scheduling of Real-Time Tasks for Dynamic Voltage Scaling
RTSS '05 Proceedings of the 26th IEEE International Real-Time Systems Symposium
A new average case analysis for completion time scheduling
Journal of the ACM (JACM)
Long-Range Dependence at the Disk Drive Level
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
PBS: a unified priority-based scheduler
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Adaptive and scalable comparison scheduling
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Scheduling despite inexact job-size information
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A Markovian approach for modeling packet traffic with long-range dependence
IEEE Journal on Selected Areas in Communications
A similarity measure for time, frequency, and dependencies in large-scale workloads
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
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We define CWS, a non-preemptive scheduling policy for workloads with correlated job sizes. CWS tackles the scheduling problem by inferring the expected sizes of upcoming jobs based on the structure of correlations and on the outcome of past scheduling decisions. Size prediction is achieved using a class of Hidden Markov Models (HMM) with continuous observation densities that describe job sizes. We show how the forward-backward algorithm of HMMs applies effectively in scheduling applications and how it can be used to derive closed-form expressions for size prediction. This is particularly simple to implement in the case of observation densities that are phase-type (PH-type) distributed, where existing fitting methods for Markovian point processes may also simplify the parameterization of the HMM workload model. Based on the job size predictions, CWS emulates size-based policies which favor short jobs, with accuracy depending mainly on the HMM used to parametrize the scheduling algorithm. Extensive simulation and analysis illustrate that CWS is competitive with policies that assume exact information about the workload.