Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Theoretical Computer Science - Selected papers in honor of Manuel Blum
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
ACM Transactions on Algorithms (TALG)
Scalably scheduling processes with arbitrary speedup curves
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Speed scaling of processes with arbitrary speedup curves on a multiprocessor
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Communications of the ACM
Non-clairvoyant speed scaling for weighted flow time
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Nonclairvoyant Speed Scaling for Flow and Energy
Algorithmica
Non-clairvoyant weighted flow time scheduling on different multi-processor models
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
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This paper initiates the study of online scheduling with rejection penalty in the non-clairvoyant setting, i.e., the size (processing time) of a job is not assumed to be known at its release time. In the rejection penalty model, jobs can be rejected with a penalty, and the user cost of a job is defined as the weighted flow time of the job plus the penalty if it is rejected before completion. Previous work on minimizing the total user cost focused on the clairvoyant single-processor setting [BBC+03,CLL11] and has produced O(1)-competitive online algorithm for jobs with arbitrary weights and penalties. This paper gives the first non-clairvoyant algorithms that are O(1)-competitive for minimizing the total user cost on a single processor and multi-processors, when using slightly faster (i.e., (1+ε)-speed for any ε 0) processors. Note that if no extra speed is allowed, no online algorithm can be O(1)-competitive even for minimizing (unweighted) flow time alone. The new user cost results can also be regarded as a generalization of previous non-clairvoyant results on minimizing weighted flow time alone (WSETF [BaD07] for a single processor; WLAPS [ZCL11] for multi-processors). The above results assume a processor running at a fixed speed. This paper shows more interesting results on extending the above study to the dynamic speed scaling model, where the processor can vary the speed dynamically and the rate of energy consumption is an arbitrary increasing function of speed. A scheduling algorithm has to decide job rejection and determine the order and speed of job execution. It is interesting to study the tradeoff between the above-mentioned user cost and energy. This paper gives two O(1)-competitive non-clairvoyant algorithms for minimizing the user cost plus energy on a single processor and multi-processors, respectively.