| Series On Data Driven Intelligence, Sustainability, And Systems |
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| Blockchain-enabled fog resource access and granting |
Gang Liu( ),Jinsong Wu(),Ting Wang*() |
Nokia Shanghai Bell Co., Ltd., Shanghai 201206, China
School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541004, China
Shanghai Key Laboratory of Trustworthy Computing and the School of Software Engineering, East China Normal University, Shanghai 200062, China |
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Abstract Fog computing is a new computing paradigm for meeting ubiquitous massive access and latency-critical applications by moving the processing capability closer to end users. The geographical distribution/floating features with potential autonomy requirements introduce new challenges to the traditional methodology of network access control. In this paper, a blockchain-enabled fog resource access and granting solution is proposed to tackle the unique requirements brought by fog computing. The smart contract concept is introduced to enable dynamic, and automatic credential generation and delivery for an independent offer of fog resources. A per-transaction negotiation mechanism supports the fog resource provider to dynamically publish an offer and facilitates the choice of the preferred resource by the end user. Decentralized authentication and authorization relieve the processing pressure brought by massive access and single-point failure. Our solution can be extended and used in multi-access and especially multi-carrier scenarios in which centralized authorities are absent.
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Received: 22 December 2020
Online: 19 August 2021
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Corresponding Authors:
Ting Wang
E-mail: gang.i.liu@nokia-sbell.com;wujs@ieee.org;twang@sei.ecnu.edu.cn
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| About author: Gang Liu received the BEng and PhD degrees in computer science from Northwestern Polytechnical University, China in 2002 and 2008, respectively. Currently, he works as a research scientist in Nokia Shanghai Bell Co., Ltd. His research interests include fixed and mobile converged network, SDN/NFV, edge/cloud computing, and AI-assisted cellular network.|Jinsong Wu received the PhD degree from Queen’s University, Canada in 2006. He is now a professor at School of Artificial Intelligence, Guilin University of Electronic Technology. He was the founder (2011) and founding chair (2011-2017) of IEEE Technical Committee on Green Communications and Computing (TCGCC). He is also the co-founder (2014) and founding vice-chair (2015-present) of IEEE Technical Committee on Big Data (TCBD). He received both 2017 and 2019 IEEE System Journal Best Paper Awards. His co-authored paper won 2018 IEEE TCGCC Best Magazine Paper Award. He received IEEE Green Communications and Computing Technical Committee 2017 Excellent Services Award for Excellent Technical Leadership and Services in the Green Communications and Computing Community. He is the leading editor and co-author of the comprehensive book, entitled Green Communications: Theoretical Fundamentals, Algorithms, and Applications, published by CRC Press in September 2012. He has been an IEEE senior member since 2011. His research interests include green communication and computer network, big data, machine learning, IoT, and edge computing.|Ting Wang received the BS degree from University of Science and Technology Beijing, China in 2008, the MEng degree from Warsaw University of Technology, Poland in 2011, and the PhD degree in computer science and engineering from Hong Kong University of Science and Technology, China in 2015. He is currently an associate professor at Shanghai Key Laboratory of Trustworthy Computing and School of Software Engineering, East China Normal University (ECNU). Prior to joining ECNU in 2020, he worked at the Bell Labs as a research scientist from 2015 to 2016, and at Huawei as a senior engineer from 2016 to 2020. He is currently an associate editor of IEEE Access, the editor-in-chief of IITCIB, and a technical committee member of Computer Communications, Elsevier. His research interests include software defined networking, data center networking, AI-driven intelligent networking, cloud computing, edge computing, and network function virtualization. |
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