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Shangguang Wang
Researcher at Beijing University of Posts and Telecommunications
Publications - 238
Citations - 6864
Shangguang Wang is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Cloud computing & Quality of service. The author has an hindex of 35, co-authored 207 publications receiving 4221 citations. Previous affiliations of Shangguang Wang include Beihang University & Peking University.
Papers
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Journal ArticleDOI
An overview of Internet of Vehicles
TL;DR: An abstract network model of the IoV is proposed, the technologies required to create the IoVs are discussed, different applications based on certain currently existing technologies are presented, and essential future research is described in the area of IoV.
Journal ArticleDOI
Edge server placement in mobile edge computing
TL;DR: This paper forms the edge server placement problem in mobile edge computing environments for smart cities as a multi-objective constraint optimization problem that places edge servers in some strategic locations with the objective to make balance the workloads of edge servers and minimize the access delay between the mobile user and edge server.
Journal ArticleDOI
A Survey on Service Migration in Mobile Edge Computing
TL;DR: The cutting-edge research efforts on service migration in MEC are reviewed, a devisal of taxonomy based on various research directions for efficient service migration is presented, and a summary of three technologies for hosting services on edge servers, i.e., virtual machine, container, and agent are provided.
Journal ArticleDOI
Delay-Aware Microservice Coordination in Mobile Edge Computing: A Reinforcement Learning Approach
TL;DR: This article reformulates the microservice coordination problem using Markov decision process framework and then proposes a reinforcement learning-based online micro service coordination algorithm to learn the optimal strategy, which proves that the offline algorithm can find the optimal solution while the online algorithm can achieve near-optimal performance.
Proceedings ArticleDOI
An Energy-Aware Edge Server Placement Algorithm in Mobile Edge Computing
Yuanzhe Li,Shangguang Wang +1 more
TL;DR: This paper designs a particle swarm optimization based energy-aware edge server placement algorithm that can reduce more than 10% energy consumption with over 15% improvement in computing resource utilization, compared to other algorithms.