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Elasticity Debt Analytics Exploitation for Green Mobile Cloud Computing: An Equilibrium Model

机译:绿色移动云计算的弹性债务分析开发:均衡模型

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Mobile cloud computing is the model to ubiquitously access a shared pool of cloud computing resources, data, and services on-demand. This paper introduces the elasticity debt analytics paradigm as a solution concept for the resource provisioning problem in mobile cloud computing environments, guaranteeing the quality of service requirements. A novel green-centric, game theoretic approach to minimizing the elasticity debt on mobile cloud-based service level is proposed, investigating the mobile cloud offloading case. The decision to offload a mobile device user's task on cloud affects the level of elasticity debt minimization for the provided services. The modeling for the computation of the processing time, energy, and overhead in mobile opportunistic offloading is presented. A utility-driven elasticity debt and profit quantification approach is also examined for maximization of resource utilization, exploiting the hidden Markov model. The problem is formulated as an elasticity debt quantification game, elaborating on an incentive mechanism to predict elasticity debt, mitigate the risk of service over-utilization, achieve scalability, and optimize cloud resource provisioning. The experimental results prove the effectiveness of the equilibrium model, which allocates the mobile device user requests to high elasticity debt-level services and facilitates the elasticity debt minimization for green mobile cloud computing environments.
机译:移动云计算是一种可按需普遍访问云计算资源,数据和服务的共享池的模型。本文介绍了弹性债务分析范式,作为移动云计算环境中资源供应问题的解决方案概念,可确保服务质量要求。提出了一种新颖的以绿色为中心的博弈论方法,以最小化基于移动云的服务水平上的弹性债务,从而研究了移动云卸载的情况。在云上卸载移动设备用户任务的决定会影响所提供服务的最小化弹性债务级别。提出了用于计算移动机会卸载中的处理时间,能量和开销的模型。利用隐马尔可夫模型,还研究了由公用事业驱动的弹性债务和利润量化方法,以最大程度地利用资源。该问题被表述为弹性债务量化游戏,阐述了一种激励机制来预测弹性债务,减轻服务过度使用的风险,实现可扩展性以及优化云资源供应。实验结果证明了该均衡模型的有效性,该均衡模型将移动设备用户请求分配给高弹性债务级别的服务,并有助于绿色移动云计算环境的弹性债务最小化。

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