IEEE/ACM Transactions on Networking (TON)
Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Waiting Time Distributions for Processor-Sharing Systems
Journal of the ACM (JACM)
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Sharing a Processor Among Many Job Classes
Journal of the ACM (JACM)
Applied operating system concepts
Applied operating system concepts
A unifying approach to scheduling
Communications of the ACM
Size-based scheduling to improve web performance
ACM Transactions on Computer Systems (TOCS)
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
Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Two-level processor-sharing scheduling disciplines: mean delay analysis
Proceedings of the joint international conference on Measurement and modeling of computer systems
Performance analysis of LAS-based scheduling disciplines in a packet switched network
Proceedings of the joint international conference on Measurement and modeling of computer systems
A resource-allocation queueing fairness measure
Proceedings of the joint international conference on Measurement and modeling of computer systems
Nearly insensitive bounds on SMART scheduling
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Sojourn times in (discrete) time shared systems and their continuous time limits
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Tail equivalence for some time-shared systems
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Limits and approximations for the M/G/1 LIFO waiting-time distribution
Operations Research Letters
ACM SIGMETRICS Performance Evaluation Review
The Foreground-Background queue: A survey
Performance Evaluation
Sojourn times in (discrete) time shared systems and their continuous time limits
Queueing Systems: Theory and Applications
CWS: a model-driven scheduling policy for correlated workloads
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Design, implementation, and performance of a load balancer for SIP server clusters
IEEE/ACM Transactions on Networking (TON)
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Blind scheduling policies schedule tasks without knowledge of the tasks' remaining processing times. Existing blind policies, such as FCFS, PS, and LAS, have proven useful in network and operating system applications, but each policy has a separate, vastly differing description, leading to separate and distinct implementations. This paper presents the design and implementation of a configurable blind scheduler that contains a continuous, tunable parameter. By merely changing the value of this parameter, the scheduler's policy exactly emulates or closely approximates several existing standard policies. Other settings enable policies whose behavior is a hybrid of these standards. We demonstrate the practical benefits of such a configurable scheduler by implementing it into the Linux operating system. We show that we can emulate the behavior of Linux's existing, more complex scheduler with a single (hybrid) setting of the parameter. We also show, using synthetic workloads, that the best value for the tunable parameter is not unique, but depends on distribution of the size of tasks arriving to the system. Finally, we use our formulation of the configurable scheduler to contrast the behavior of various blind schedulers by exploring how various properties of the scheduler change as we vary our scheduler's tunable parameter.