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


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Abstract


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 greencentric, 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 userÔ??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

KeyWords
Elasticity debt analytics game theory green cloud computing hidden Markov model mobile cloud computing utility computing



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