Cloud Federations: Economics, Games and Benefits
Cloud Federations: Economics, Games and Benefits
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云联盟：经济学、博弈和效益
DOI：
10.1109/tnet.2019.2943810
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
G. Stamoulis
中科院分区：
文献类型：
--
作者：
George Darzanos;I. Koutsopoulos;G. Stamoulis
共享经济是一种改变游戏规则的商业模式，目前正在渗透到多个工业领域。本文旨在构建云服务提供商（CSP）计算能力资源共享经济的基础理论。 CSP 旨在以经济高效的方式为地理位置分散的客户提供服务，这些客户通常需要计算资源需求较高的服务。 CSP 联盟的形成是管理这些多样化且随时间变化的服务请求的有效手段。在本文中，我们介绍了创新的联盟模型和盈利联盟的政策，这些联盟也为其客户实现了足够的服务质量。考虑到灵活的云计算服务模型，我们将每个CSP的虚拟化基础设施抽象为M/M/1排队系统，制定了CSP收入和成本函数，并研究了基于任务转发（TF）和基于容量共享（CS）的联邦方法。在 TF 下，每个 CSP 可以将其部分工作负载转发给其他联合 CSP，而在 CS 下，每个 CSP 可以与其他 CSP 共享其部分计算基础设施。对于这两种方法，我们提出了两种不同程度的CSP合作的运营模式：$(i)$联合商业模式，其中CSP充分合作：他们共同决定联邦政策，使联邦总利润最大化，并在他们之间公平分享； $(ii)$ 奖励驱动模式，自私的 CSP 参与游戏：他们调整对联邦政策的反应，旨在最大化其个人利润。结果表明，我们的政策可以形成有效的联盟，这对 CSP 和客户都有利。
Sharing economy is a game-changing business paradigm that is currently permeating several industrial sectors. This paper aims to build a fundamental theory of the sharing economy of the computational capacity resource of Cloud Service Providers (CSPs). CSPs aim to cost-efficient serve geographically dispersed customers that often request computational resource-demanding services. The formation of CSP federations arises as an effective means to manage these diverse and time-varying service requests. In this paper, we introduce innovative federation models and policies for profitable federations that also achieve adequate QoS for their customers. Taking in account the flexible cloud computing service model, we abstract the virtualized infrastructure of each CSP to an M/M/1 queueing system, we formulate the CSP revenue and cost functions, and we study the task forwarding-based (TF) and the capacity sharing-based (CS) federation approaches. Under TF, each CSP may forward part of its workload to other federated CSPs, while under CS each CSP may share parts of its computational infrastructure with others. For both approaches, we propose two operation modes with different degree of CSPs’ cooperation: $(i)$ the joint business mode, where the CSPs fully cooperate: they jointly decide on the federation policies that maximize the total federation profit which is shared fairly among them; $(ii)$ the reward-driven mode, where self-interested CSPs participate in a game: they adjust their responses to federation policies aiming to maximize their individual profits. The results reveal that our policies lead to effective federations, which are beneficial both for CSPs and for customers.