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Better bounds for online scheduling

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons43989

Albers,  Susanne
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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1997-1-009
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Albers, S.(1997). Better bounds for online scheduling (MPI-I-1997-1-009). Saarbrücken: Max-Planck-Institut für Informatik.

Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-9E1F-1
Abstract
We study a classical problem in online scheduling. A sequence of jobs must be scheduled on $m$ identical parallel machines. As each job arrives, its processing time is known. The goal is to minimize the makespan. Bartal, Fiat, Karloff and Vohra gave a deterministic online algorithm that is 1.986-competitive. Karger, Phillips and Torng generalized the algorithm and proved an upper bound of 1.945. The best lower bound currently known on the competitive ratio that can be achieved by deterministic online algorithms it equal to 1.837. In this paper we present an improved deterministic online scheduling algorithm that is 1.923-competitive, for all $m\geq 2$. The algorithm is based on a new scheduling strategy, i.e., it is not a generalization of the approach by Bartal {\it et al}. Also, the algorithm has a simple structure. Furthermore, we develop a better lower bound. We prove that, for general $m$, no deterministic online scheduling algorithm can be better than \mbox{1.852-competitive}.