Approximation Algorithms for the Multiorganization Scheduling Problem

Dutot, P-F; Pascual, Fanny; Rządca, Krzysztof; Trystram, Denis

doi:10.1109/tpds.2011.47

Cited by 18 publications

(22 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For parallel rigid jobs (i.e., that requires a fixed number of processors

q_{i}^{(k)}

), Pascual et al . have showed a new algorithm with constant approximation ratio (a 3‐approximation) regarding the optimal global makespan. They also show that this bound is asymptotically tight (when the number of organizations is large).…”

Section: The Multiorganization Scheduling Problemmentioning

confidence: 99%

“…For this more general scenario, we can show that Theorem The price of anarchy in MOSP games with priority to organizations and parallel workloads is unbounded. Proof We will prove this theorem constructing an instance of the MOSP game with priorities to organizations that has a pure Nash equilibrium with cost arbitrarily far from the schedule with optimal cost. Like in Section 7, the construction of the pure Nash equilibrium is inspired by the ILBA algorithm. Let

x MathClass-rel\in double-struckN

the ratio of the cost of this equilibrium to the ratio of the optimal cost and

n MathClass-rel= \frac{3}{2} x (x MathClass-bin- 1) MathClass-bin+ 2

.…”

Section: Game With Priority To Organizationsmentioning

confidence: 99%

See 1 more Smart Citation

Coordination mechanisms for decentralized parallel systems

Cohen

Cordeiro

Trystram

2014

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

International audienceOn resource sharing platforms, the execution of the jobs submitted by users is usually controlled by a centralized global scheduler. It determines efficient schedules regarding some common objective function that all organizations agree with (for instance, maximizing the utilization of the entire platform). However, in practice, each organization is mostly interested in the performance obtained for its own jobs. We study the price that the collectivity must pay in order to allow independence to selfish, self-governing organizations, so they can choose the best schedules for their own jobs. In other words, we are interested in analyzing the costs on the global performance inflicted by the decentralization of scheduling policies. We present a game-theoretic model for the problem and the associated coordination mechanisms developed to reduce the cost of the decentralization of the decision-making process. The main contribution is to show (in theory and practice) how to devise pure Nash equilibria configurations for every instance of the problem and to prove that the price paid by the collectivity depends on the local scheduling policy and on the characteristics of the workload executed on such platform

show abstract

“…For parallel rigid jobs (i.e., that requires a fixed number of processors

q_{i}^{(k)}

Section: The Multiorganization Scheduling Problemmentioning

confidence: 99%

x MathClass-rel\in double-struckN

the ratio of the cost of this equilibrium to the ratio of the optimal cost and

n MathClass-rel= \frac{3}{2} x (x MathClass-bin- 1) MathClass-bin+ 2

.…”

Section: Game With Priority To Organizationsmentioning

confidence: 99%

Coordination mechanisms for decentralized parallel systems

Cohen

Cordeiro

Trystram

2014

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, the organizations may have a different number of processors. The rigid job scheduling problem on multi-organizations has been extended in [11] for the case where the jobs are submitted to local queues on each cluster with the extra constraint that the initial local schedules must not be worsened. The authors provide a 3-approximation.…”

Section: Problem Statementmentioning

confidence: 99%

Approximating the Non-contiguous Multiple Organization Packing Problem

Bougeret¹,

Dutot²,

Jansen

et al. 2010

IFIP Advances in Information and Communication Technology

Self Cite

View full text Add to dashboard Cite

“…[6] the jobs are scheduled to minimize the global performance metric (the makespan) with an additional requirement -the utility of each player cannot be worse than if the player would act alone. Such approach ensures the stability of the system against actions of any single user (it is not profitable for the user to leave the system and to act alone) but not to the formation of sub-coalitions.…”

Section: Introductionmentioning

confidence: 99%

Non-monetary fair scheduling

Skowron

Rządca

2013

Proceedings of the Twenty-Fifth Annual ACM Symposium on Parallelism in Algorithms and Architectures

Self Cite

View full text Add to dashboard Cite

We consider a multi-organizational system in which each organization contributes processors to the global pool but also jobs to be processed on the common resources. The fairness of the scheduling algorithm is essential for the stability and even for the existence of such systems (as organizations may refuse to join an unfair system).We consider on-line, non-clairvoyant scheduling of sequential jobs. The started jobs cannot be stopped, canceled, preempted, or moved to other processors. We consider identical processors, but most of our results can be extended to related or unrelated processors.We model the fair scheduling problem as a cooperative game and we use the Shapley value to determine the ideal fair schedule. In contrast to the current literature, we do not use money to assess the relative utilities of jobs. Instead, to calculate the contribution of an organization, we determine how the presence of this organization influences the performance of other organizations. Our approach can be used with arbitrary utility function (e.g., flow time, tardiness, resource utilization), but we argue that the utility function should be strategy resilient. The organizations should be discouraged from splitting, merging or delaying their jobs. We present the unique (to within a multiplicative and additive constants) strategy resilient utility function.We show that the problem of fair scheduling is NP-hard and hard to approximate. However, for unit-size jobs, we present a fully polynomial-time randomized approximation scheme (FPRAS). We also show that the problem parametrized with the number of organizations is fixed parameter tractable (FPT). In cooperative game theory, the Shapley value is considered in many contexts as "the" fair solution. Our results show that, although the problem for the large number of organizations is computationally hard, this solution concept can be used in scheduling (for instance, as a benchmark for measuring fairness of heuristic algorithms).

show abstract

Approximation Algorithms for the Multiorganization Scheduling Problem

Cited by 18 publications

References 16 publications

Coordination mechanisms for decentralized parallel systems

Coordination mechanisms for decentralized parallel systems

Approximating the Non-contiguous Multiple Organization Packing Problem

Non-monetary fair scheduling

Contact Info

Product

Resources

About