Cooperation in Multi-organization Scheduling

Pascual, Fanny; Rządca, Krzysztof; Trystram, Denis

doi:10.1007/978-3-540-74466-5_25

Cited by 21 publications

(33 citation statements)

References 8 publications

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“…The Multi-Organization Scheduling problem (MOSP) was introduced by Pascual et al [6], [7]. The goal was to study how to efficiently schedule parallel jobs in new computing platforms, while respecting users' own selfish objectives.…”

Section: B Related Workmentioning

confidence: 99%

“…Ooshita et al [9] also studied the notion of cooperation between organizations, following [6] but with a different perspective. Instead of studying the strict lack of willingness to cooperate, they studied how much one can improve the global makespan if all organizations allow some degradation of their own local objectives by a constant factor -called degree of cooperativeness (denoted by the parameter α).…”

Section: B Related Workmentioning

confidence: 99%

“…MOSP -as first studied by Pascual et al [6], [7] introduces local constraints to guarantee that all organizations will always have incentive to cooperate. In the global schedule, no organization will have its makespan increased when compared to the makespan that the organization could have by scheduling its jobs alone in its own set of processors (C (k) local max ).…”

Section: A Relaxed Local Constraintsmentioning

confidence: 99%

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Tight Analysis of Relaxed Multi-organization Scheduling Algorithms

Cordeiro

Dutot

Mounié

et al. 2011

2011 IEEE International Parallel &Amp; Distributed Processing Symposium

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Abstract-The goal of this paper is to study how limited cooperation can impact the quality of the schedule obtained by multiple independent organizations in a typical grid computing platform. This relaxed version of the problem known as the Multi-Organization Scheduling Problem (MOSP) models an environment where organizations providing both resources and jobs tolerate a bounded degradation on the makespan of their own jobs in order to minimize the makespan over the entire platform.More precisely, the technical contributions are the following. First, we improve the existing inapproximation bounds for this problem proving that what was previously though as not polynomially approximable (unless P = N P ) is actually not approximable at all. We achieve this using two families of instances whose Pareto optimal solutions are on par with the previous inaproximability bounds.Then, we present two algorithms that solve the problem with approximation ratios of (2; 3/2) and (3; 4/3) respectively. This means that when using the first (second) algorithm, if an organization tolerates that the completion time of its last job cannot exceed twice (three times) the time it would have obtained by itself, then the algorithm provides a solution that is a 3/2-approximation (4/3-approximation) for the optimal global makespan. Both algorithms are efficient since their performance ratio correspond to the Pareto optimal solutions of the previously defined instances.

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Section: B Related Workmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

Section: A Relaxed Local Constraintsmentioning

confidence: 99%

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Tight Analysis of Relaxed Multi-organization Scheduling Algorithms

Cordeiro

Dutot

Mounié

et al. 2011

2011 IEEE International Parallel &Amp; Distributed Processing Symposium

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“…Drozdowski [5] gave a detailed review on the problems of scheduling multiprocessor tasks in a single machine environment for optimizing various objective functions. Pascual et al [6] and Rzadca [7] studied the problem of scheduling multiprocessor tasks in a multi-machine environment for minimizing makespan where all the machines have the same number of processors. Pascual et al [6] proposed a 4-approximation algorithm and Rzadca [7] proposed a 3-approximation algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Pascual et al [6] and Rzadca [7] studied the problem of scheduling multiprocessor tasks in a multi-machine environment for minimizing makespan where all the machines have the same number of processors. Pascual et al [6] proposed a 4-approximation algorithm and Rzadca [7] proposed a 3-approximation algorithm. Later, the problem of scheduling multiprocessor tasks in a multi-machine environment for minimizing makespan was studied in [8][9][10], and three 3-approximation algorithms were obtained.…”

Section: Introductionmentioning

confidence: 99%

A Polynomially Solvable Case of Scheduling Multiprocessor Tasks in a Multi-Machine Environment

Xiao¹,

Mou²,

Mu³

2017

Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

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Abstract. The problem of scheduling multiprocessor tasks in a multi-machine environment is considered. Each machine contains a number of identical processors. Each task requires a number of processors on a single machine for its processing. The objective is to minimize the overall task completion time, i.e. the makespan. The general problem has been known to be strongly NP-hard. A linear time optimal algorithm is presented for a special case of the problem where all the tasks have unit processing times and each task requires one or k (k is part of the input) processors. The small computational effort of the algorithm is valuable in some practical applications.

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Multi‐organization scheduling approximation algorithms

Cohen¹,

Cordeiro²,

Trystram³

et al. 2011

Concurrency and Computation

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SUMMARYIn this paper we consider the problem of scheduling on computing platforms composed of several independent organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization provides both resources and jobs and follows its own objectives. We are interested in the best way to minimize the makespan on the entire platform when the organizations behave in a selfish way. We study the complexity of the MOSP problem with two different local objectives-makespan and average completion time-and show that MOSP is strongly NP-Hard in both cases. We formally define a selfishness notion, by means of restrictions on the schedules. We prove that selfish behavior imposes a lower bound of 2 on the approximation ratio for the global makespan. We present various approximation algorithms of ratio 2 which validate selfishness restrictions. These algorithms are experimentally evaluated through simulation, exhibiting good average performances and presenting good fairness to organizations' local objectives.

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Cooperation in Multi-organization Scheduling

Cited by 21 publications

References 8 publications

Tight Analysis of Relaxed Multi-organization Scheduling Algorithms

Tight Analysis of Relaxed Multi-organization Scheduling Algorithms

A Polynomially Solvable Case of Scheduling Multiprocessor Tasks in a Multi-Machine Environment

Multi‐organization scheduling approximation algorithms

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