Competitive non-migratory scheduling for flow time and energy
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
How to schedule when you have to buy your energy
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
Online algorithms for advance resource reservations
Journal of Parallel and Distributed Computing
Improved multi-processor scheduling for flow time and energy
Journal of Scheduling
| Hi-index | 0.00 |
In this paper we consider multiprocessor scheduling with hard deadlines and investigate the cost of eliminating migration in the online setting. Let I be any set of jobs that can be completed by some migratory offline schedule on m processors. We show that I can also be completed by a nonmigratory online schedule using m speed-5.828 processors (i.e., processors 5.828 times faster). This result supplements the previous results that I can also be completed by a nonmigratory offline schedule using 6m unit-speed processors [B. Kalyanasundaram and K. R. Pruhs, J. Algorithms, 38 (2001), pp. 2--24] or a migratory online schedule using m speed-2 processors [C. A. Phillips et al., Algorithmica, 32 (2002), pp. 163--200]. Our result is based on a simple conservative scheduling algorithm called PARK, which commits a processor to a job only when the processor has zero commitment before its deadline. A careful analysis of PARK further shows that the processor speed can be reduced arbitrarily close to 1 by exploiting more processors (say, using 16m speed-1.8 processors). PARK also finds application in overloaded systems; it gives the first online nonmigratory algorithm that can exploit moderately faster processors to match the performance of any migratory offline algorithm.