Towards energy and time efficient resource allocation in IoT-Fog-cloud environment

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Abstract

As the number of IoT devices with limited resources and the corresponding observed data grow exponentially, the method of offloading all tasks to a remote data center becomes expensive, even inefficient. How to optimize the energy consumption of application requests from IoT devices satisfying the deadline constraint is also a challenge. Fog computing is closer to users, featuring the lower service delay but less resource than the remote cloud. Fog does not mean to replace cloud. They are complementary to each other, and cooperation between them is worth studying. The main points of this paper are: (1) Proposing a general IoT-fog-cloud computing architecture that fully exploits the advantages of fog and cloud. (2) Formulating the energy efficient computation offloading and dynamic resource scheduling (eoDS) problem, then proposing an eoDS algorithm to solve the problem, reducing the energy consumption and completion time of application requests (3) Compared with cloud nodes, the mobility of fog nodes is higher. For this, we propose the fog functional areas reconstruction method to adaptively deal with the changing environment, improving the resource utilization of fog.

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Sun, H., Yu, H., & Fan, G. (2019). Towards energy and time efficient resource allocation in IoT-Fog-cloud environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11434 LNCS, pp. 387–393). Springer Verlag. https://doi.org/10.1007/978-3-030-17642-6_32

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