STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Trade-offs between speed and processor in hard-deadline scheduling
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Non-clairvoyant scheduling to minimize the average flow time on single and parallel machines
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Improved algorithms for stretch scheduling
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Non-clairvoyant Scheduling for Minimizing Mean Slowdown
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Online Weighted Flow Time and Deadline Scheduling
APPROX '01/RANDOM '01 Proceedings of the 4th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems and 5th International Workshop on Randomization and Approximation Techniques in Computer Science: Approximation, Randomization and Combinatorial Optimization
Server scheduling in the Lp norm: a rising tide lifts all boat
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Approximation Algorithms for Average Stretch Scheduling
Journal of Scheduling
Dynamic TCP acknowledgment in the LogP model
Journal of Algorithms
Nonclairvoyant scheduling to minimize the total flow time on single and parallel machines
Journal of the ACM (JACM)
Theoretical Computer Science - Special issue: Online algorithms in memoriam, Steve Seiden
| Hi-index | 0.00 |
We consider the problem of scheduling a collection of dynamically arriving jobs with unknown execution times so as to minimize the average response/flow time. This is the classic CPU scheduling problem faced by time sharing operating systems. In the standard 3-field scheduling notation this is the nonclairvoyant version of 1|pmtn, r/sub j/|/spl Sigma/F/sub j/. Its easy to see that every algorithm that doesn't unnecessarily idle the processor is at worst n-competitive, where n is the number of jobs. Yet there is no known nonclairvoyant algorithm, deterministic or randomized, with a competitive ratio provably o(n). We present a randomized nonclairvoyant algorithm, RMLF, that has competitive ratio /spl theta/(lognloglogn) against an adaptive adversary. RMLF is a slight variation of the multi level feedback (MLF) algorithm used by the Unix operating system, further justifying the adoption of this algorithm. R. Motwani et al. (1994) showed that every randomized nonclairvoyant algorithm is /spl Omega/2(log n)competitive, and that every deterministic nonclairvoyant algorithm is /spl Omega/2(n/sup 1/3/)-competitive.