On-line bin-stretching

Azar, Yossi; Regev, Oded

doi:10.1016/s0304-3975(00)00258-9

Cited by 67 publications

(51 citation statements)

References 13 publications

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“…This application has first appeared in [3]. In this setting, an older server (or a server cluster) is streaming a large number of files to the newer server without any guarantee on file order.…”

Section: Motivation We Give Two Of Applications Of Online Bin Stretcmentioning

confidence: 99%

Better Algorithms for Online Bin Stretching

Böhm

Sgall

Stee

et al. 2015

Approximation and Online Algorithms

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Online Bin Stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as the optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin.We give an algorithm for Online Bin Stretching with a stretching factor of 1.5 for any number of bins. We also show a specialized algorithm for three bins with a stretching factor of 11/8 = 1.375.

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Section: Motivation We Give Two Of Applications Of Online Bin Stretcmentioning

confidence: 99%

Better Algorithms for Online Bin Stretching

Böhm

Sgall

Stee

et al. 2015

Approximation and Online Algorithms

View full text Add to dashboard Cite

show abstract

“…Various other models of semi-online scheduling problems on identical machines have been studied extensively in recent years [11,16,10,13,2,6,15,3,12]. These variants differ in which partial information about future job is known in advance.…”

Section: Previous Workmentioning

confidence: 99%

“…Several models assume some information is known in advance, this can be the total processing time of jobs [11,1], the optimal makespan [2,4] or the largest processing time [10]. A model where all job processing times are bounded between two known values, with a ratio of at most ρ for some given ρ > 1 between these two values, was studied in [10].…”

Section: Previous Workmentioning

confidence: 99%

Semi-online scheduling with “end of sequence” information

Epstein

2007

J Comb Optim

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We study a variant of classical scheduling, which is called scheduling with "end of sequence" information. It is known in advance that the last job has the longest processing time. Moreover, the last job is marked, and thus it is known for every new job whether it is the final job of the sequence. We explore this model on two uniformly related machines, that is, two machines with possibly different speeds. Two objectives are considered, maximizing the minimum completion time and minimizing the maximum completion time (makespan). Let s be the speed ratio between the two machines, we consider the competitive ratios which are possible to achieve for the two problems as functions of s. We present algorithms for different values of s and lower bounds on the competitive ratio. The proposed algorithms are best possible for a wide range of values of s. For the overall competitive ratio, we show tight bounds of φ + 1 ≈ 2.618 for the first problem, and upper and lower bounds of 1.5 and 1.46557 for the second problem.

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“…The variable bin packing algorithm as proposed in [32][33][34] is handling different bin sizes, but the size is fixed after the selection of the bin. The extensible bin-packing algorithm, which allows a stretching of the bin [35,36] is not applicable as the maximum number of bins is fixed. Another difference to standard bin-packing approaches is the necessity to preempt message classes as the capacity of a single host is often too small.…”

Section: Configuration Of a Distributed Systemmentioning

confidence: 99%

Configuration of distributed message converter systems

Risse

Aberer

Wombacher

et al. 2004

Performance Evaluation

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Finding a configuration of a distributed system satisfying performance goals is a complex search problem that involves many design parameters, like hardware selection, job distribution and process configuration. Performance models are a powerful tool to analyze potential system configurations, however, their evaluation is expensive, such that only a limited number of possible configurations can be evaluated. In this paper we present a systematic method to find a satisfactory configuration with feasible effort, based on a two-step approach. First, performing a queuing network analysis a hardware configuration is determined and then a software configuration is incrementally optimized by simulating Layered Queuing Network models. We applied this method to the design of performant EDI converter systems in the financial domain, where increasing message volumes need to be handled due to the growing importance of B2B interaction.

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On-line bin-stretching

Cited by 67 publications

References 13 publications

Better Algorithms for Online Bin Stretching

Better Algorithms for Online Bin Stretching

Semi-online scheduling with “end of sequence” information

Configuration of distributed message converter systems

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