An online algorithm optimally self-tuning to congestion for power management problems

Authors:
Wolfgang Bein;Naoki Hatta;Nelson Hernandez-Cons;Hiro Ito;Shoji Kasahara;Jun Kawahara
Affiliations:
Center for Information Technology and Algorithms, School of Computer Science, University of Nevada, Las Vegas;Department of Communications and Computer Engineering, Graduate School of Informatics, Kyoto University, Japan;Department of Systems Science, Graduate School of Informatics, Kyoto University, Japan;Department of Communications and Computer Engineering, Graduate School of Informatics, Kyoto University, Japan;Department of Systems Science, Graduate School of Informatics, Kyoto University, Japan;JST ERATO MINATO Project, Japan
Venue:
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
Year:
2011

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Abstract

We consider the classical power management problem: There is a device which has two states ON and OFF and one has to develop a control algorithm for changing between these states as to minimize (energy) cost when given a sequence of service requests. Although an optimal 2-competitive algorithm exists, that algorithm does not have good performance in many practical situations, especially in case the device is not used frequently. To take the frequency of device usage into account, we construct an algorithm based on the concept of "slackness degree." Then by relaxing the worst case competitive ratio of our online algorithm to 2+ε, where ε is an arbitrary small constant, we make the algorithm flexible to slackness. The algorithm thus automatically tunes itself to slackness degree and gives better performance than the optimal 2-competitive algorithm for real world inputs. In addition to worst case competitive ratio analysis, a queueing model analysis is given and computer simulations are reported, confirming that the performance of the algorithm is high.