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Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicular Edge Computing

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Web Information Systems Engineering – WISE 2023 (WISE 2023)

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Abstract

Vehicular networking technology is advancing rapidly, and one promising area of research is blockchain-based vehicular edge computing to enhance resource allocation and data security. This paper aims to optimize resource allocation and data security in vehicular edge computing by leveraging blockchain technology, thereby improving the overall system efficiency and reliability. By integrating the computational, storage, and communication capabilities of vehicles with blockchain, efficient utilization of edge computing and fair resource allocation are achieved. Additionally, data encryption techniques are introduced to ensure data security and privacy protection. Experimental results demonstrate that the system can automatically identify and allocate the most suitable edge computing nodes, thereby enhancing the responsiveness and quality of computational tasks. The blockchain-based vehicular edge offloading system not only optimizes the performance of vehicular networking systems and enhances user experience but also strengthens data security and privacy protection, providing a novel solution for the development of the vehicular networking industry.

The work is supported in part by Key Research Projects of Universities in Guangdong Province under Grant 2022ZDZX1011. Guangdong Provincial Natural Science Fund Project under Grant 2023A1515011084 and Doctoral Program Construction Unit Research Capability Enhancement Project at Guangdong Polytechnic Normal University under Grant 22GPNUZDJS27.

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Authors and Affiliations

  1. School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou, 510635, China

    Maojie Wang, Shaodong Han & Guihong Chen

  2. Institute for Sustainable Industries and Liveable Cities, Victoria University, Melbourne, Australia

    Jiao Yin

  3. Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia

    Jinli Cao

Authors
  1. Maojie Wang
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  2. Shaodong Han
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  3. Guihong Chen
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  4. Jiao Yin
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  5. Jinli Cao
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Corresponding author

Correspondence to Guihong Chen .

Editor information

Editors and Affiliations

  1. Renmin University of China, Beijing, China

    Feng Zhang

  2. Victoria University, Footscray, VIC, Australia

    Hua Wang

  3. Qatar University, Doha, Qatar

    Mahmoud Barhamgi

  4. Swinburne University of Technology, Hawthorn, Australia

    Lu Chen

  5. Swinburne University of Technology, Hawthorn, Australia

    Rui Zhou

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, M., Han, S., Chen, G., Yin, J., Cao, J. (2023). Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicular Edge Computing. In: Zhang, F., Wang, H., Barhamgi, M., Chen, L., Zhou, R. (eds) Web Information Systems Engineering – WISE 2023. WISE 2023. Lecture Notes in Computer Science, vol 14306. Springer, Singapore. https://doi.org/10.1007/978-981-99-7254-8_16

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  • DOI: https://doi.org/10.1007/978-981-99-7254-8_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7253-1

  • Online ISBN: 978-981-99-7254-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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