We consider the problem of preemptively scheduling jobs to minimize mean response time of an M/G/1 queue. When the scheduler knows each job's size, the shortest remaining processing time (SRPT) policy is optimal. Unfortunately, in many settings we do not have access to each job's size. Instead, we know only the job size distribution. In this setting, the Gittins policy is known to minimize mean response time, but its complex priority structure can be computationally intractable. A much simpler alternative to Gittins is the shortest expected remaining processing time (SERPT) policy. While SERPT is a natural extension of SRPT to unknown job sizes, it is unknown how close SERPT is to optimal.
We present a new variant of SERPT called monotonic SERPT (M-SERPT) which is as simple as SERPT but has provably near-optimal mean response time at all loads for any job size distribution. Specifically, we prove the mean response time ratio between M-SERPT and Gittins is at most 3 for load ρ ≤ 8/9 and at most 5 for any load. This makes M-SERPT the only scheduling policy known to be a constant-factor approximation of Gittins.
The Information Systems Laboratory Colloquium (ISLC)
is typically held in Packard 101 every Thursday at 4:30 pm during the academic year. Coffee and refreshments are served at 4pm in the second floor kitchen of Packard Bldg.
The Colloquium is organized by graduate students Joachim Neu, Tavor Baharav and Kabir Chandrasekher. To suggest speakers, please contact any of the students.
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