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Dynamic Fog Computing: Practical Processing at Mobile Edge Devices

Dynamic Fog Computing: Practical Processing at Mobile Edge Devices

SANDER SOO, Chii Chang, Seng W. Loke, Satish Narayana Srirama
Copyright: © 2019 |Pages: 24
ISBN13: 9781522556930|ISBN10: 1522556931|EISBN13: 9781522556947
DOI: 10.4018/978-1-5225-5693-0.ch002
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MLA

SOO, SANDER, et al. "Dynamic Fog Computing: Practical Processing at Mobile Edge Devices." Algorithms, Methods, and Applications in Mobile Computing and Communications, edited by Agustinus Borgy Waluyo, IGI Global, 2019, pp. 24-47. https://doi.org/10.4018/978-1-5225-5693-0.ch002

APA

SOO, S., Chang, C., Loke, S. W., & Srirama, S. N. (2019). Dynamic Fog Computing: Practical Processing at Mobile Edge Devices. In A. Borgy Waluyo (Ed.), Algorithms, Methods, and Applications in Mobile Computing and Communications (pp. 24-47). IGI Global. https://doi.org/10.4018/978-1-5225-5693-0.ch002

Chicago

SOO, SANDER, et al. "Dynamic Fog Computing: Practical Processing at Mobile Edge Devices." In Algorithms, Methods, and Applications in Mobile Computing and Communications, edited by Agustinus Borgy Waluyo, 24-47. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-5693-0.ch002

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Abstract

The emerging Internet of Things (IoT) systems enhance various mobile ubiquitous applications such as augmented reality, environmental analytics, etc. However, the common cloud-centric IoT systems face limitations on the agility needed for real-time applications. This motivates the Fog computing architecture, where IoT systems distribute their processes to the computational resources at the edge networks near data sources and end-users. Although fog computing is a promising solution, it also raises a challenge in mobility support for mobile ubiquitous applications. Lack of proper mobility support will increase the latency due to various factors such as package drop, re-assigning tasks to fog servers, etc. To address the challenge, this chapter proposes a dynamic and proactive fog computing approach, which improves the task distribution process in fog-assisted mobile ubiquitous applications and optimizes the task allocation based on runtime context information. The authors have implemented and validated a proof-of-concept prototype and the chapter discusses the findings.

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