A Comparative Study on Game Theoretic Approaches for Resource Allocation in Cloud Computing Architectures

Jebalia, Maha; Letaïfa, Asma Ben; Hamdi, Mohamed; Tabbane, Sami

doi:10.1109/wetice.2013.11

Cited by 15 publications

(7 citation statements)

References 12 publications

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“…Different types of equilibria and games have been considered, according to the problem addressed. A detailed survey of several resource allocation strategies in Clouds is given in [64], whereas a recent comparative study can be found in [40].…”

Section: Related Workmentioning

confidence: 99%

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Ardagna

Ciavotta

Passacantando

2017

IEEE Trans. Serv. Comput.

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Abstract-The adoption of Cloud technologies is steadily increasing. In such systems, applications can benefit from nearly infinite virtual resources on a pay-per-use basis. However, being the Cloud massively multi-tenant and characterized by highly variable workloads the development of more and more effective provisioning policies assumes paramount importance. Boosted by the success of the Cloud, the application of Game Theory models and methodologies has also become popular, since they have been demonstrated to suit perfectly to Cloud social, economic, and strategic structures. This paper aims to study, model and efficiently solve the cost minimization problem associated with the service provisioning of SaaS virtual machines in multiple IaaSs. We propose a game-theoretic approach for the runtime management of resources from multiple IaaS providers to be allocated to multiple competing SaaSs, along with a cost model including revenues and penalties for requests execution failures. A distributed algorithm for identifying Generalized Nash Equilibria has been developed and analysed in detail. The effectiveness of our approach has been assessed by performing a wide set of analyses under multiple workload conditions. Results show that our algorithm is scalable and provides significant cost savings with respect to alternative methods (80% on average). Furthermore, increasing the number of IaaS providers SaaSs can achieve 9-15% cost savings from the workload distribution on multiple IaaSs.

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Section: Related Workmentioning

confidence: 99%

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Ardagna

Ciavotta

Passacantando

2017

IEEE Trans. Serv. Comput.

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“…• VM migration and placement: is a procedure of transferring a running VM among various PMs in data centers without any interruption and disconnecting the cloud users. Processing, networking and storage connectivity is required during the VM migration from source to destination PMs [25,31,98,149,150]. • Workload balancing: is the procedure of allocating workloads and resources in a cloud computing systems.…”

Section: Future Workmentioning

confidence: 99%

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

et al. 2016

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There are two actors in cloud computing environment cloud providers and cloud users. On one hand cloud providers hold enormous computing resources in the cloud large data centers that rent the resources out to the cloud users on a pay-per-use basis to maximize the profit by achieving high resource utilization. On the other hand cloud users who have applications with loads variation and lease the resources from the providers they run their applications within minimum expenses. One of the most critical issues of cloud computing is resource management in infrastructure as a service (IaaS). Resource management related problems include resource allocation, resource adaptation, resource brokering, resource discovery, resource mapping, resource modeling, resource provisioning and resource scheduling. In this review we investigated resource allocation schemes and algorithms used by different researchers and categorized these approaches according to the problems addressed schemes and the parameters used in evaluating different approaches. Based on different studies considered, it is observed that different schemes did not consider some important parameters and enhancement is required to improve the performance of the existing schemes. This review contributes to the existing body of research and will help the researchers to gain more insight into resource allocation techniques for IaaS in cloud computing in the future.

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“…The highest bidder will be allocated the set of auctioned resources. To deal with such complexities of the resource allocation problem in a dynamic and evolutionary environment, a number of researchers have focused on a study of game theoretical approaches [15]. Game theory-based resource allocation mechanisms have received a considerable amount of attention in cloud computing to solve the optimization problem of resource allocation.…”

Section: Resource Allocation In a Cloud Computing Environmentmentioning

confidence: 99%

Towards an autonomic performance management approach for a cloud broker environment using a decomposition–coordination based methodology

Mehrotra

Srivastava

Banicescu

et al. 2016

Future Generation Computer Systems

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Efficient resource allocation of computational resources to services is one of the predominant challenges in a cloud computing environment. Furthermore, the advent of cloud brokerage and federated cloud computing systems increases the complexity of cloud resource management. Cloud brokers are considered third party organizations that work as intermediaries between the service providers and the cloud providers. Cloud brokers rent different types of cloud resources from a number of cloud providers and sublet these resources to the requesting service providers. In this paper, an autonomic performance management approach is introduced that provides dynamic resource allocation capabilities for deploying a set of services over a federated cloud computing infrastructure by considering the availability as well as the demand of the cloud computing resources. A distributed control based approach is used for providing autonomic computing features to the proposed framework via a feedback-based control loop. This distributed control based approach is developed using one of the decomposition-coordination methodology, named interaction balance, for interactive bidding of cloud computing resources. The primary goals of the proposed approach are to maintain the service level agreements, maximize the profit, and minimize the operating cost for the service providers and the cloud broker. The application of interaction balance methodology and prioritization of profit maximization for the cloud broker and the service providers during resource allocation are novel contributions of the proposed approach.

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A Comparative Study on Game Theoretic Approaches for Resource Allocation in Cloud Computing Architectures

Cited by 15 publications

References 12 publications

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

Towards an autonomic performance management approach for a cloud broker environment using a decomposition–coordination based methodology

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