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

Mobile cloud computing is being accepted as the model for mobile users to ubiquitously access a shared pool of cloud computing resources, data and services on-demand. In this context, elasticity debt analytics can be harnessed as a measure for efficient scheduling of cloud resources and guarantee of quality of service requirements. This paper proposes a novel green-driven, game theoretic approach to minimizing the elasticity debt on mobile cloud-based service level, investigating the case when a task is offloaded, scheduled and executed on a mobile cloud computing system. The decision to offload a mobile device user's task on cloud affects the level of elasticity debt minimization for the provided services. The research problem is formulated as an elasticity debt quantification game, elaborating on an incentive mechanism to: (a) predict elasticity debt and mitigate the risk of service overutilization, (b) achieve scalability as the number of mobile device user requests for cloud resources increases or decreases accordingly, and (c) optimize cloud resource provisioning, parameterizing the current pool of active users per service. The experimental results prove the effectiveness of the equilibrium model, which allocates the mobile device user requests to high elasticity debt-level services and facilitate elasticity debt minimization for greener mobile cloud computing environments.