Energy-efficiency fog computing resource allocation in cyber physical internet of things systems

Energy-efficiency fog computing resource allocation in cyber physical internet of things systems

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Cyber physical internet of things systems (CPIoTs), taking advantages of cyber physical systems, have been considered as a promising technology to provide better interaction and interoperability among various machines. However, the development of CPIoTs suffers severely from big data. In this context, fog computing is proposed to handle the big data bottleneck of CPIoTs. In this study, the authors focus on the joint optimisation of the communication resources and computation resources in fog computing-based CPIoTs to maximise the overall system energy efficiency, in which multiple fog nodes and end users are taken into consideration. Moreover, since the channel estimation error will become serious with the expanding scale, the imperfect channel state information is considered in this study. The formulated optimisation problem is a mixed integer non-linear problem which is indeed non-deterministic polynomial hard, hence a probability distribution method is proposed to reformulate the problem into a non-probability form, and the resource allocation algorithm based on Dinkelbach algorithm and Lagrange duality approach is adopted to tackle the problem efficiently. The simulation results confirm the effectiveness of the proposed scheme, especially when the scales are enormous.


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