Resource allocation in combined fog-cloud scenarios by using artificial intelligence

Abedi, Masoud GND; Pourkiani, Mohammadreza

Although both cloud and fog computing technologies provide great on-demand services for the users, but none of them could singly guarantee the Quality of Service for the Internet of Things (IoT) based delay-sensitive applications. Therefore, cooperation between fog and cloud servers is of great importance. In this paper, we discuss about an artificial intelligence (AI) based task distribution algorithm (AITDA), which aims to reduce the response time and the Internet traffic by distribution of the tasks between fog and cloud servers. Our case study is a delay-sensitive application that runs in a situation where the computing capability of fog servers is restricted, and the internet connection is unstable (like vessels on the oceans). The primary trial of the AITDA shows that this method noticeably reduces the response time and internet traffic in comparison to the cloud-based and foz-based approaches.

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Abedi, Masoud / Pourkiani, Mohammadreza: Resource allocation in combined fog-cloud scenarios by using artificial intelligence. 2020.

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