In the cloud service paradigm, service providers aim to cost-efficiently serve Internet of Things (IoT) devices' applications that often request computation-intensive services. In this study, we focus on the cloud...
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In the cloud service paradigm, service providers aim to cost-efficiently serve Internet of Things (IoT) devices' applications that often request computation-intensive services. In this study, we focus on the cloud resource sharing problem in the distributed mobile cloud computing (DMCC) platform. By considering different IoT applications and distributed cloud infrastructure, we design a novel DMCC resource sharing scheme for data offloading services. Based on the cooperative game theory, five different valuesolutions are adopted, and they are implemented for each case cooperative process to provide the fair-efficient solution. According to the service characteristics, our proposed scheme explores the mutual benefits of local and global MCC providers' interactions, and effectively shares the distributed cloud resources. To dynamically adapt the current DMCC system conditions, our approach can provide an appropriate guidance to improve the efficiency of cloud resource usage while enhancing the service quality. The main novelty of our proposed scheme is the ability to leverage a reciprocal consensus between different control viewpoints. Therefore, we can ensure a relevant tradeoff between efficiency and fairness among multiple service providers.
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