4.8 Article

A Blockchain-Based Containerized Edge Computing Platform for the Internet of Vehicles

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 4, Pages 2395-2408

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3027700

Keywords

Containers; Task analysis; Edge computing; Processor scheduling; Servers; Delays; Blockchain; container scheduling; edge computing; vehicle task offloading

Funding

  1. National Key Research and Development Plan of China [2018YFB1800302, 2018YFB1800805]
  2. National Natural Science Foundation of China [61772345, 61902258, 61672358, 61836005]
  3. Major Fundamental Research Project in the Science and Technology Plan of Shenzhen [JCYJ20190808142207420, GJHZ20190822095416463]
  4. Pearl River Young Scholars funding of Shenzhen University

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CUTE is a containerized edge computing platform designed to provide low-latency computation services for the Internet of Vehicles, integrated with blockchain for enhanced network security. By developing a heuristic container scheduling algorithm, CUTE optimizes the scheduling efficiency for vehicle-submitted tasks based on DAG structures.
Edge computing is promising to solve the latency issue in the Internet of Vehicles (IoV). However, due to decentralization, traditional edge computing suffers in management, deployment, and security. Containerization relaxes resource deployment and migration problems, but current container scheduling policies are inefficient to process complicated tasks based on directed acyclic graph or DAG structures. In this article, we design a containerized edge computing platform CUTE, which provides low-latency computation services for the Internet of Vehicles. The centralized controller is empowered with resource management and orchestration, and containers are scheduled to appropriate edge servers to optimize the computation delay. CUTE is also integrated with blockchain to improve network security. We formulate the vehicle task offloading and container scheduling problems and develop a heuristic container scheduling algorithm for DAG-based computation tasks submitted by vehicles remotely. We implement and deploy CUTE into the China Mobile Network, and conduct comprehensive experiments and a case study. The experiment results show that CUTE can provide low-latency computation services for vehicular applications and that the heuristic algorithm outperforms traditional container scheduling policies.

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