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+
+% 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.
+
+
personal git repositories of Harald Welte. Your mileage may vary