Market‐Oriented Resource Management and Scheduling: A Taxonomy and Survey

Garg, Saurabh; Buyya, Rajkumar

doi:10.1002/9781119973584.ch14

Cited by 11 publications

(14 citation statements)

References 55 publications

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“…Several economic models can be applied to the Grid and Cloud environments [4], [5], [6], [7]. The most important ones in our scenario are the Commodity market model and the Posted price models.…”

Section: Related Workmentioning

confidence: 99%

“…The request is sent to a brokering tool that transparently manages the allocation of the VM corresponding to the SLA specification in a hybrid Cloud composed by the resources of a Public Cloud provider (as the Amazon Elastic Cloud Computing EC2) 5 and the private ones. The purpose is to maximize both the number of satisfied users and the PP's profit.…”

Section: The Scheduling Strategiesmentioning

confidence: 99%

See 1 more Smart Citation

Delivering Cloud Services with QoS Requirements: An Opportunity for ICT SMEs

Quarati

D’Agostino

Galizia

et al. 2012

Economics of Grids, Clouds, Systems, and Services

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Abstract.The acknowledged success and diffusion of Cloud computing is due to its great potential in terms of improving companies' business model. Notwithstanding this opportunity, two main issues arise: the need of brokers supporting users in the selection of the most suitable offers, and the provisioning of dedicated services with higher levels of quality different from mere availability. This paper discusses the expected performance in a real-case scenario of a Cloud brokering tool delivering two services: e-Learning courses in virtual classroom and Risk Assessment evaluation, each with a specific set of nonfunctional requirements. The broker relies on the resources supplied by a hybrid Cloud infrastructure, allocated following different scheduling strategies, which dynamically select the proposals better satisfying the QoS requested by users. The objective is the execution of the highest amount of user requests along with the maximization of the profit of the private Cloud provider, in a context of posted price economic model.

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Section: Related Workmentioning

confidence: 99%

Section: The Scheduling Strategiesmentioning

confidence: 99%

Delivering Cloud Services with QoS Requirements: An Opportunity for ICT SMEs

Quarati

D’Agostino

Galizia

et al. 2012

Economics of Grids, Clouds, Systems, and Services

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“…In a research conducted by Buyya et al [14], different types of economic based scheduling methods used in economic grid and grid environments are categorized according to Fig 1. Heuristic models for task-execution scheduling mainly include static and dynamic methods. Static methods are used when the set of tasks to be scheduled is predetermined and dynamic methods are used when tasks enter as real time [6].…”

Section: System-levelmentioning

confidence: 99%

Efficient Nash equilibrium resource allocation based on game theory mechanism in cloud computing by using auction

Nezarat

Dastghaibifard

2015

2015 1st International Conference on Next Generation Computing Technologies (NGCT)

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One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer's utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.

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“…Buyya et al [10] proposed a market-oriented RA scheme by integrating both the customer-driven service management and provider-driven risk management to promote SLA-based RA. Nevertheless, [10] it requires a market maker and a market registry to bring the consumer and providers together and to publish the cloud services and discover their providers.…”

Section: A Sla-based Dynamic Ra Modelsmentioning

confidence: 99%

“…Nevertheless, [10] it requires a market maker and a market registry to bring the consumer and providers together and to publish the cloud services and discover their providers.…”

Section: A Sla-based Dynamic Ra Modelsmentioning

confidence: 99%