On-line scheduling

Sgall, Jiřį́

doi:10.1007/bfb0029570

Cited by 202 publications

(119 citation statements)

References 68 publications

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“…Each cluster measures the sum of flow times F i (the difference between the job's completion time C i,j and its release date, or arrival time r i,j ) of cluster's local jobs: F i = j (C i,j − r i,j ). We consider on-line [32], clairvoyant scheduling [7]. A job J i,j is unknown to the scheduler before its arrival time r i,j .…”

Section: Descriptionmentioning

confidence: 99%

Promoting cooperation in selfish computational grids

Rządca¹,

Trystram²

2009

European Journal of Operational Research

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In distributed computing the recent paradigm shift from centrallyowned clusters to organizationally distributed computational grids introduces a number of new challenges in resource management and scheduling. In this work, we study the problem of Selfish Load Balancing which extends the well-known Load Balancing (LB) problem to scenarios in which each processor is concerned only with the performance of its local jobs. We propose a simple mathematical model for such systems and a novel function for computing the cost of the execution of foreign jobs. Then, we use the game-theoretic framework to analyze the model in order to compute the expected result of LB performed in a grid formed by two clusters. We show that, firstly, LB is a socially-optimal strategy, and secondly, for similarly loaded clusters, it is sufficient to collaborate during longer time periods in order to make LB the dominant strategy for each cluster. However, we show that if we allow clusters to make decisions depending on their current queue length, LB will never be performed. Then, we propose a LB algorithm which balances the load more equitably, even in the presence of overloaded clusters. Our algorithms do not use any external forms of compensation (such as money). The load is balanced 1 only by considering the parameters of execution of jobs. This analysis is assessed experimentally by simulation, involving scenarios with multiple clusters and heterogeneous load.

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Section: Descriptionmentioning

confidence: 99%

Promoting cooperation in selfish computational grids

Rządca¹,

Trystram²

2009

European Journal of Operational Research

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“…It can be useful to compare these results with those in on-line scheduling, since quite a lot of effort has gone into the analysis of multiple machine scheduling problems [39]. In the one-by-one model competitive ratios increase with increasing number of machines.…”

Section: Theorem 15 ([14]mentioning

confidence: 99%

On-Line Algorithms, Real Time, the Virtue of Laziness, and the Power of Clairvoyance

Ausiello

Allulli

Bonifaci

et al. 2006

Lecture Notes in Computer Science

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“…In addition to these remarks it is worthwhile to comment on the difference between offline and online scheduling [64]. Offline scheduling as mostly discussed in this article, in the ideal case, assumes that all data of a problem are given, i.e., full knowledge of the future (of course, this is also an approximation since our knowledge of future demand or orders is uncertain), and is close to planning except for the length of the time horizon and the resolution of time.…”

Section: Some Comments On Planning and Scheduling In The Process Indumentioning

confidence: 99%

Planning and scheduling in the process industry

Kallrath¹

2002

OR Spectrum

308

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Since there has been tremendous progress in planning and scheduling in the process industry during the last 20 years, it might be worthwhile to give an overview of the current state-of-the-art of planning and scheduling problems in the chemical process industry. This is the purpose of the current review which has the following structure: we start with some conceptional thoughts and some comments on special features of planning and scheduling problems in the process industry. In Section 2 the focus is on planning problems while in Section 3 different types of scheduling problems are discussed. Section 4 presents some solution approaches especially those applied to a benchmark problem which has received considerable interest during the last years. Section 5 allows a short view into the future of planning and scheduling. In the appendix we describe the WestenbergerKallrath problem which has already been used extensively as a benchmark problem for planning and scheduling in the process industry.

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On-line scheduling

Cited by 202 publications

References 68 publications

Promoting cooperation in selfish computational grids

Promoting cooperation in selfish computational grids

On-Line Algorithms, Real Time, the Virtue of Laziness, and the Power of Clairvoyance

Planning and scheduling in the process industry

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