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Qingqi Pei
Researcher at Xidian University
Publications - 245
Citations - 3757
Qingqi Pei is an academic researcher from Xidian University. The author has contributed to research in topics: Computer science & Cognitive radio. The author has an hindex of 20, co-authored 205 publications receiving 1745 citations. Previous affiliations of Qingqi Pei include Guilin University of Electronic Technology.
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Cooperative Computation Offloading and Resource Allocation for Blockchain-Enabled Mobile-Edge Computing: A Deep Reinforcement Learning Approach
TL;DR: This article develops an asynchronous advantage actor–critic-based cooperation computation offloading and resource allocation algorithm to solve the MDP problem and designs a multiobjective function to maximize the computation rate of MEC systems and the transaction throughput of blockchain systems.
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Vehicular Edge Computing and Networking: A Survey
TL;DR: A comprehensive survey of state-of-the-art research on VEC can be found in this paper, where the authors provide an overview of VEC, including the introduction, architecture, key enablers, advantages, challenges as well as several attractive application scenarios.
Posted Content
Vehicular Edge Computing and Networking: A Survey.
TL;DR: A comprehensive survey of state-of-art research on VEC, including the introduction, architecture, key enablers, advantages, challenges as well as several attractive application scenarios, is provided.
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An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System
TL;DR: A real-time vehicle tracking counter for vehicles that combines the vehicle detection and vehicle tracking algorithms to realize the detection of traffic flow is proposed.
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Blockchain-Enabled Secure Data Sharing Scheme in Mobile-Edge Computing: An Asynchronous Advantage Actor–Critic Learning Approach
TL;DR: In this article, a secure data sharing scheme in the blockchain-enabled mobile edge computing system using an asynchronous learning approach is presented, and an adaptive privacy-preserving mechanism according to available system resources and privacy demands of users is presented.