Scheduling Independent Tasks with QoS Requirements in Grid Computing with Time-Varying Resource Prices

As cloud-based services become more numerous and dynamic, resource provisioning becomes more and more challenging. A QoS constrained resource allocation problem is considered in this paper, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation. Game theory is used to solve the problem of resource allocation. A practical approximated solution with the following two steps is proposed. First, each participant solves its optimal problem independently, without consideration of the multiplexing of resource assignments. A Binary Integer Programming method is proposed to solve the independent optimization. Second, an evolutionary mechanism is designed, which changes multiplexed strategies of the initial optimal solutions of different participants with minimizing their efficiency losses. The algorithms in the evolutionary mechanism take both optimization and fairness into account. It is demonstrated that Nash equilibrium always exists if the resource allocation game has feasible solutions.A game-theoretic method of fair resource allocation for cloud 253

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“…Various resource management methods with different policies and principles were published in some papers [1,2,6,9,14,17,19,24,28,30,32].…”

Section: Related Workmentioning

confidence: 99%

“…Many techniques are available to achieve this [9,14]. (2) Subtasks are dependent, and communicate with each other.…”

Section: Assumptionsmentioning

confidence: 99%

A game-theoretic method of fair resource allocation for cloud computing services

et al. 2009

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“…In [3], two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming. Doǧan and Ozguner [4] consider the problem of scheduling a set of independent tasks with multiple QoS requirements, which may include timeliness, reliability, security, version and priority in a Grid computing system in which resource prices can vary with time during scheduling time intervals. Golconda et al [5] compare five QoS-based scheduling heuristics from the literature in terms of three performance parameters, namely the number of satisfied users, makespan and total utility of the meta-task.…”

Section: Related Workmentioning

confidence: 99%

An optimization approach for decentralized QoS‐based scheduling based on utility and pricing in Grid computing

Li¹

2006

Concurrency and Computation

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SUMMARYThis paper presents an optimization approach for decentralized Quality of Service (QoS)-based scheduling based on utility and pricing in Grid computing. The paper assumes that the quality dimensions can be easily formulated as utility functions to express quality preferences for each task agent. The utility values are calculated by the user-supplied utility function that can be formulated with the task parameters. The QoS constraint Grid resource scheduling problem is formulated into a utility optimization problem. The QoS-based Grid resource scheduling optimization is decomposed into two subproblems by applying the Lagrangian method. In the Grid, a Grid task agent acts as a consumer paying for the Grid resource and the resource providers receive profits from task agents. A pricing-based QoS scheduling algorithm is used to perform optimally decentralized QoS-based resource scheduling. The experiments investigate the effect of the QoS metrics on the global utility and compare the performance of the proposed algorithm with other economical Grid resource scheduling algorithms.

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“…In fact, in service operations management, it is a common phenomenon that different time slots have varying costs. For example, in grid computing, service providers charge the customers based on the time when the task is scheduled [9]. When a television network schedules advertiser's campaign [4,5], the values of different time slots are significantly different.…”

Section: Introductionmentioning

confidence: 99%

Scheduling with variable time slot costs

Wan

2010

Naval Research Logistics

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Abstract:In this article, we study a class of new scheduling models where time slot costs have to be taken into consideration. In such models, processing a job will incur certain cost which is determined by the time slots occupied by the job in a schedule. The models apply when operational costs vary over time. The objective of the scheduling models is to minimize the total time slot costs plus a traditional scheduling performance measure. We consider the following performance measures: total completion time, maximum lateness/tardiness, total weighted number of tardy jobs, and total tardiness. We prove the intractability of the models under general parameters and provide polynomial-time algorithms for special cases with non-increasing time slot costs.

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Scheduling Independent Tasks with QoS Requirements in Grid Computing with Time-Varying Resource Prices

Cited by 37 publications

References 14 publications

A game-theoretic method of fair resource allocation for cloud computing services

A game-theoretic method of fair resource allocation for cloud computing services

An optimization approach for decentralized QoS‐based scheduling based on utility and pricing in Grid computing

Scheduling with variable time slot costs

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