Scheduling for performance and availability in systems with temporal dependent workloads

Temporal locality in workloads creates conditions in which a server, in order to remain available, should quickly process bursts of requests with large service requirements. In this paper, we show how to counteract the resulting peak congestions and maintain high availability by delaying selected requests that contribute to the temporal locality. We propose and evaluate SWAP, a measurement-based scheduling policy that approximates the shortest job first (SJF) scheduling without requiring any knowledge of job service times. We show that good service time estimates can be obtained from the temporal dependence structure of the workload and allow to closely approximate the behavior of SJF. Experimental results indicate that SWAP significantly improves system performability. In particular, we show that system capacity under SWAP is largely increased compared to first-come first-served (FCFS) scheduling and is highly-competitive with SJF, but without requiring a priori information of job service times.

[1]  Alma Riska,et al.  Long-Range Dependence at the Disk Drive Level , 2006, Third International Conference on the Quantitative Evaluation of Systems - (QEST'06).

[2]  Virgílio A. F. Almeida,et al.  Capacity Planning for Web Performance: Metrics, Models, and Methods , 1998 .

[3]  Marcel F. Neuts,et al.  Structured Stochastic Matrices of M/G/1 Type and Their Applications , 1989 .

[4]  A. Erramilli,et al.  A connection admission control algorithm for self-similar traffic , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[5]  Martin F. Arlitt,et al.  Web server workload characterization: the search for invariants , 1996, SIGMETRICS '96.

[6]  Vishal Misra,et al.  PBS: a unified priority-based scheduler , 2007, SIGMETRICS '07.

[7]  Asser N. Tantawi,et al.  An analytical model for multi-tier internet services and its applications , 2005, SIGMETRICS '05.

[8]  Ness B. Shroff,et al.  Bursty data over CDMA: MAI self similarity, rate control and admission control , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[9]  Tao Yang,et al.  Bandwidth allocation for VBR video traffic in ATM networks , 1995, Proceedings of Fourth International Conference on Computer Communications and Networks - IC3N'95.

[10]  Bo Friis Nielsen,et al.  On the statistical implications of certain random permutations in Markovian arrival processes (MAPs) and second-order self-similar processes , 2000, Perform. Evaluation.

[11]  Peter J. Denning,et al.  The Operational Analysis of Queueing Network Models , 1978, CSUR.

[12]  Virgílio A. F. Almeida,et al.  Capacity planning for web performance: metrics , 1998 .

[13]  Lawrence M. Leemis,et al.  Discrete-Event Simulation: A First Course , 2006 .

[14]  B. Welford.  Note on a Method for Calculating Corrected Sums of Squares and Products , 1962 .

[15]  Qi Zhang,et al.  Performance impacts of autocorrelated flows in multi-tiered systems , 2007, Perform. Evaluation.

[16]  Ningfang Mi.  Performance impacts of autocorrelated flows in multi-tiered systems , 2007, PERV.

[17]  David Tse,et al.  A framework for robust measurement-based admission control , 1999, TNET.

[18]  Michael Muskulus,et al.  Analysis and modeling of job arrivals in a production grid , 2007, PERV.

[19]  Eric J. Friedman,et al.  Fairness and efficiency in web server protocols , 2003, SIGMETRICS '03.

[20]  Carey L. Williamson,et al.  Internet Web servers: workload characterization and performance implications , 1997, TNET.

[21]  Sem C. Borst,et al.  GPS scheduling: selection of optimal weights and comparison with strict priorities , 2006, SIGMETRICS '06/Performance '06.

[22]  Linus Schrage,et al.  Letter to the Editor - A Proof of the Optimality of the Shortest Remaining Processing Time Discipline , 1968, Oper. Res..