A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers

Samaan, Nancy

doi:10.1109/tpds.2013.23

Cited by 92 publications

(36 citation statements)

References 25 publications

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“…Furthermore, they consider scenarios when the profit is maximized from the perspective of the whole CF, and scenarios when each cloud maximizes its profit. Another approach is presented in [11], where the author applied game theory to analyze the selfish behavior of cloud owner selling unused resources depending on uncertain load conditions.…”

Section: Motivation and State Of The Artmentioning

confidence: 99%

Traffic Management for Cloud Federation

Burakowski

Bęben

Berg

et al. 2018

Lecture Notes in Computer Science

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Abstract. The chapter summarizes activities of COST IC1304 ACROSS European Project corresponding to traffic management for Cloud Federation (CF). In particular, we provide a survey of CF architectures and standardization activities. We present comprehensive multilevel model for traffic management in CF that consists of five levels: Level 5 -Strategies for building CF, Level 4 -Network for CF, Level 3 -Service specification and provision, Level 2 -Service composition and orchestration, and Level 1 -Task service in cloud resources. For each level we propose specific methods and algorithms. The effectiveness of these solutions were verified by simulation and analytical methods. Finally, we also describe specialized simulator for testing CF solution in IoT environment.

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Section: Motivation and State Of The Artmentioning

confidence: 99%

Traffic Management for Cloud Federation

Burakowski

Bęben

Berg

et al. 2018

Lecture Notes in Computer Science

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“…In (Zhao et al, 2012), authors present an online resource marketplace for open Clouds by adopting an eBay style transaction model based on auction theory. Here (Samaan, 2013) establishes a novel economic sharing model to regulate capacity sharing in a federation of hybrid Cloud providers. The idea of financial options is used by (Sharma et al, 2012) as a financial model for pricing Cloud compute commodities by using Moore's law on depreciation of asset values, to show the effect of depreciation of Cloud resource on QoS.…”

Section: Related Workmentioning

confidence: 99%

Cloud Asset Pricing Tree (CAPT) - Elastic Economic Model for Cloud Service Providers

Qanbari

Dustdar

et al. 2014

Proceedings of the 4th International Conference on Cloud Computing and Services Science

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Abstract:Cloud providers are incorporating novel techniques to cope with prospective aspects of trading like resource allocation over future demands and its pricing elasticity that was not foreseen before. To leverage the pricing elasticity of upcoming demand and supply, we employ financial option theory (future contracts) as a mechanism to alleviate the risk in resource allocation over future demands. This study introduces a novel Cloud Asset Pricing Tree (CAPT) model that finds the optimal premium price of the Cloud federation options efficiently. Providers will benefit by this model to make decisions when to buy options in advance and when to exercise them to achieve more economies of scale. The CAPT model adapts its structure to address the price elasticity concerns and makes the demand, price inelastic and the supply, price elastic. Our empirical evidences suggest that using the CAPT model, exploits the Cloud market potential as an opportunity for more resource utilization and future capacity planning.

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“…These works can be classified into two broad categories: (i) Cooperative resource pooling [6]- [8], where CSPs aggregate their resources aiming to maximize the total utility of federation and (ii) Resource trading [9], [10], where CSPs aim to maximize their individual profit by trading their unused resources. In our prelude work [11], we modeled each CSP as an M/M/1 queueing system and devised a mathematical model for the net profit of each CSP.…”

Section: Introductionmentioning

confidence: 99%

Economics models and policies for cloud federations

Darzanos

Koutsopoulos

Stamoulis

2016

2016 IFIP Networking Conference (IFIP Networking) and Workshops

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Cloud federation has emerged as an effective solution offering worldwide coverage, dynamic infrastructure scaling and improved QoS for the demanding cloud services. In this paper, we present a model for Cloud Service Providers (CSPs) federation and we investigate the economic benefits of CSPs under different federation modes. Each CSP is modeled as an M/M/1 queue with arrivals corresponding to computation tasks and service rate that captures the computational capabilities of the CSP. Each CSP earns revenue by charging its customers according to a QoS-dependent pricing function, and it undergoes a cost due to energy consumption of its infrastructure. We propose a model for the formation of cloud federations, according to which each CSP may forward part of the workload stemming from its customers to other CSPs. We define three federation modes with varying degrees of CSPs' interaction, namely the strong, weak and elastic federations. In strong federations, the CSPs jointly decide on their forwarding policies to maximize the total profit of the federation; then, they share these profits according to certain profit sharing policies. In weak federations, a game arises, in which each CSP follows a forwarding policy that aims to maximize its individual payoff, which however incorporates some fairness. In elastic federations, each CSP again aims to maximize its individual payoff, but it has the freedom to tune the degree of its selfishness through a pricing function. The numerical results validate and quantify the conjecture that federation can incur substantial monetary benefits and achieve a near to optimal QoS.

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A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers

Cited by 92 publications

References 25 publications

Traffic Management for Cloud Federation

Traffic Management for Cloud Federation

Cloud Asset Pricing Tree (CAPT) - Elastic Economic Model for Cloud Service Providers

Economics models and policies for cloud federations

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