ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads.
File(s)
Accepted version
Author(s)
Mi, N
Casale, G
Smirni, E
Type
Journal Article
Abstract
Temporal dependence in workloads creates peak congestion that can make service unavailable and reduce system performance. To improve system performability under conditions of temporal dependence, a server should quickly process bursts of requests that may need large service demands. In this paper, we propose and evaluateASIdE, an Autocorrelation-based SIze Estimation, that selectively delays requests which contribute to the workload temporal dependence. ASIdE implicitly approximates the shortest job first (SJF) scheduling policy but without any prior knowledge of job service times. Extensive experiments show that (1) ASIdE achieves good service time estimates from the temporal dependence structure of the workload to implicitly approximate the behavior of SJF; and (2) ASIdE successfully counteracts peak congestion in the workload and improves system performability under a wide variety of settings. Specifically, we show that system capacity under ASIdE is largely increased compared to the first-come first-served (FCFS) scheduling policy and is highly-competitive with SJF. © 2012 IEEE.
Date Issued
2012-05-08
ISSN
1932-4537
Start Page
198
End Page
212
Journal / Book Title
IEEE Transactions on Network and Service Management
Volume
9
Issue
2
Copyright Statement
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Description
2/12/14 meb. Accepted version, OK to add.
Identifier
2