Dynamics of service selection and provider pricing game in heterogeneous cloud market

Cuong, Thi; Tran, Nguyen H.; Huh, Eui‐Nam; Hong, Choong Seon; Niyato, Dusit; Han, Zhu

doi:10.1016/j.jnca.2016.04.012

Cited by 40 publications

(33 citation statements)

References 39 publications

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“…The most employed approaches include multicriteria decision analysis-based service selection [7,[12][13][14], reputation-aware service selection [15], adaptive learning mechanism-based service selection [8,16], economic theoretical model-based service selection [17,18], service level agreement-based service ranking [6], visualization framework for service selection [19], and trust evaluation middleware for cloud service selection [20]. Though these approaches can efficiently measure service quality, the implementation of some approaches is time-consuming and costly.…”

Section: Related Workmentioning

confidence: 99%

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Context‐Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

2018

Wireless Communications and Mobile Computing

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Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select trustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on the trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service selection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest. In addition, the relational degree among services is calculated based on PropFlow algorithm and we utilize it to improve the accuracy of ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user's trust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared with other two traditional approaches. The experimental results show the effectiveness of SSRM.

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Section: Related Workmentioning

confidence: 99%

“…Do et al [17] propose a dynamic service selection method which provides a price game in heterogeneous cloud market. The paper studies price competition in a heterogeneous cloud market, where users can identify benefit and cost of cloud service application and choose the best one through analyzing market-relevant factors.…”

Section: Related Workmentioning

confidence: 99%

Context‐Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

2018

Wireless Communications and Mobile Computing

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“…The user's tasks are assigned to a hybrid cloud server and device. It builds an extra computation for private clouds that allows users to perform workloads, that is, how to offload workloads from users to both public and private clouds [5]. Based on the concerns of public cloud service reliability and security, a hybrid cloud solution is proposed, which can make full use of public cloud resources to supplement the local private cloud resources [6].…”

Section: Related Workmentioning

confidence: 99%

Public Cloud Cost Analysis Based on Game Theory

Chen¹

2018

Proceedings of the 2018 International Conference on Sports, Arts, Education and Management Engineering (SAEME 2018)

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Abstract. In a hybrid cloud computing environment, how to divide workload reasonably is a problem that every rational user needs to consider. The game model of hybrid cloud computing is constructed. The cost is also taken into consideration when the user usually considers the response time. The function which takes the response time and the cost as the variable is the utility function. By solving the Nash equilibrium method, the user's strategy behavior is analyzed, and the optimal strategy of the user is determined. Through the simulation, the influence of different response time and expense ratio on the user equilibrium strategy is given and compared.

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“…Do et al studied price competition in a heterogeneous cloud computing systems, in which the service providers that provide cloud services or cloud broker are all called cloud service providers (CSPs). Do CT adopt a two‐stage noncooperative game model to express the price competition among CSPs . In stage I, CSPs set their service prices to maximize their profits.…”

Section: Related Workmentioning

confidence: 99%

Key parameters decision for cloud computing: Insights from a multiple game model

Wang

Liu

Zhang

2017

Concurrency and Computation

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Summary In service‐oriented cloud computing systems (CCSs), the aim of cloud service organizers (CSOs) is to achieve maximum profit by collecting metadata with low cost from big data reporters (BDRs) and to provide advanced services to customers at a high price. In these systems, BDRs receive payoffs by reporting metadata to CSOs and exchanging metadata with other BDRs, and customers expect to get high‐quality services at a low price. However, because the missing of a critical parameters decision model in such service‐oriented CCSs, it is difficult to measure key parameters in CCSs such as price and quality of services in the competitive market. In this paper, we propose a multiple game (MG) model to formulate the critical parameters decision process. In the MG model, there are multiple games: games among BDRs and games among CSOs under the rule of “survival of the fittest,” games between BDRs and CSOs under the rule of “the highest payoff first,” and games between customers and CSOs under the rule of “the lowest price and the highest quality of service (QoS) first.” With the proposed multiple game (MG) model, the optimal key parameters can be obtained and the Pareto‐optimal equilibrium point can be achieved. Extensive simulation results demonstrate the effectiveness and efficiency of the proposed MG model in dynamically deciding key parameters in CCSs.

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Dynamics of service selection and provider pricing game in heterogeneous cloud market

Cited by 40 publications

References 39 publications

Context‐Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

Context‐Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

Public Cloud Cost Analysis Based on Game Theory

Key parameters decision for cloud computing: Insights from a multiple game model

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