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Fog Computing Framework for the Internet of Things

Fog Computing Framework for the Internet of Things

Latest PhD Thesis on Fog Computing Framework for the Internet of Things

Research Area:  Fog Computing

Abstract:

   Smart systems (e.g., smart home, smart cities) rely heavily on the Internet of Things (IoT) with features of heterogeneity and resource constraints. It is widely recognized as the next generation of the Internet, connecting a myriad of devices to further enhance the collaboration between humans and machines,thus forming a variety of applications, including human-to-human, human-to-machine, and machine-to-machine networks. The cloud is naturally assumed to be the core in data processing and service provisioning in the current IoT architecture. As the IoT generates a huge amount of data, it may lead to severe congestion and latency issues. To address these concerns, fog computing is conceptually proposed as a complement to cloud while located within proximity of users and smart objects. However, fog is a concept that has not been fully investigated.
   As the role of fog computing is to expedite the IoT continuum between the cloud and things, an investigation of fog computing will help us to acquire insights into the internal components and their interactions. Hence, our work in this thesis starts from common IoT applications in smart living to explore the fog elements, namely, fog servers, fog edge nodes and fog lets. Then, we detail the interplay in a uniform fog architecture along the cloud-fog-things continuum.
   Finally, the latency issue is studied as it is the driving reason for fog adoption.We carefully investigate the latency components to disclose the reasons why and how to cut down the overall delays in fog. Due to the practical deployment and resource limitations of fog nodes, it could be hard to directly reduce the end-to-end delay in a fog system.

Name of the Researcher:  Jianhua Li

Name of the Supervisor(s):  Jiong Jin, Dong Yuan

Year of Completion:  2019

University:  Swinburne University of Technology

Thesis Link:   Home Page Url