A DAG-based Secure Cooperative Task Offloading Scheme in Vehicular Networks
Yao Xie, Fan Wu, Ke Zhang, Supeng Leng · 2021 IEEE 21st International Conference on Communication Technology (ICCT) · 2021
Cooperative task offloading is a promising solution to improve computation efficiency and reduce task delay in vehicular networks. However, trust risk among vehicles leads to security and privacy issues in the cooperative offloading process. In this article, we propose a Direct Acyclic Graph (DAG)-based secure cooperative task offloading framework, which provides secure and efficient computation services for the vehicular networks. The DAG-based blockchain is extended with a priority and reliability-biased random walk (PR-BRW) consensus algorithm to ensure the latency requirements of tasks in different emergency degrees. Moreover, to prevent the potential malicious behaviors of vehicles involved in offloading, we develop a vehicle credit assessment mechanism that can adaptively adjust the consensus opportunities according to vehicle credit values. Next, we formulate the cooperative task offloading problems to minimize the overall offloading delay by jointly optimizing offloading decision, data segment size, and DAG confirmation threshold. Furthermore, we analyze the PR-BRW consensus process to obtain the DAG confirmation time, and develop a Particle Swarm Optimization (PSO)-based delay-optimal cooperative offloading (PDCO) scheme to achieve the optimal solution. Simulation results demonstrate the feasibility of the proposed secure cooperative task offloading scheme.