On Reducing IoT Service Delay via Fog Offloading

By Ashkan Yousefpour, Genya Ishigaki, Riti Gour, Jason P. Jue. IEEE Internet of Things Journal, 2018

319 citations recorded by the source corpus.

With the Internet of Things (IoT) becoming a major component of our daily life, understanding how to improve the quality of service for IoT applications through fog computing is becoming an important problem. In this paper, we introduce a general framework for IoT-fog-cloud applications, and propose a delay-minimizing collaboration and offloading policy for fog-capable devices that aims to reduce the service delay for IoT applications. We then develop an analytical model to evaluate our policy and show how the proposed framework helps to reduce IoT service delay.

Subfields: Computer Networks and Communications, Computer Science Applications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ea7139d55978c63a18eaee24cbb1b0f91035de9d

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Citations in the corpus

Collaborative Cloud and Edge Computing for Latency Minimization (2019, background): “A cooperative task offloading policy was proposed to deliver low latency performance for a multiuser MEC system by load sharing [19].”
Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing (2018, methodology): “For the IoT, fog computing is adopted to improve the quality of service [21].”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “A three-layer general logical architecture for fog computing is introduced in [88] and [89].”