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diff --git a/2005/flow-accounting-ols2005/OLS2005/seelam/seelam-abstract.tex b/2005/flow-accounting-ols2005/OLS2005/seelam/seelam-abstract.tex new file mode 100644 index 0000000..26070b0 --- /dev/null +++ b/2005/flow-accounting-ols2005/OLS2005/seelam/seelam-abstract.tex @@ -0,0 +1,56 @@ + +% Registration Enhancements to Linux I/O Scheduling +% [2]Register/Submit Proposal Seetharami R Seelam (seelam@cs.utep.edu) + +The Linux 2.6 release provides four I/O +schedulers: deadline, anticipatory, noop, and +completely fair queuing (CFQ), along with an +option to select one of these four at boot +time. The selection is based on \textit{a priori} +knowledge of the workload, hardware +configuration of the system, and the file +system, among other factors. The anticipatory +scheduler (AS) is the default. Although the AS +performs well under many situations, we have +identified cases, under certain combinations +of workloads, where the AS leads to starvation +of processes. To mitigate this problem, we +implemented an extension to the AS (called +Cooperative AS or CAS) and compared its +performance with the other four schedulers. +This paper briefly describes the AS and the +related deadline scheduler, highlighting their +shortcomings; in addition, it gives a detailed +description of the CAS. We report performance +of all five schedulers on a set of workloads, +which represent a wide range of I/O behavior. +The study shows that (1) the CAS has an order +of magnitude improvement in performance in +cases where the AS leads to starvation and (2) +in several cases the CAS has performance +comparable to that of the other schedulers. +But, as the literature and this study reports, +no one scheduler can provide the best possible +performance for all workloads; accordingly, +Linux provides four from which to select. Even +when dealing with just four I/O schedulers, in +systems that service concurrent workloads with +different I/O behaviors, \textit{a priori} selection of +the scheduler with the best possible +performance can be an intricate task. Dynamic +selection based on workload needs, system +configuration, and other parameters can +address this challenge. Accordingly, we are +developing metrics and heuristics that can be +used for this purpose. The paper concludes +with a description of our efforts in this +direction, in particular, we present a +characterization function based on metrics +related to system behavior and I/O requests +that can be used to measure and compare +scheduling algorithm performance. This +characterization function can be used to +dynamically select an appropriate scheduler +based on observed system behavior. + + |