P
Pengbo Si
Researcher at Beijing University of Technology
Publications - 102
Citations - 1715
Pengbo Si is an academic researcher from Beijing University of Technology. The author has contributed to research in topics: Cognitive radio & Quality of service. The author has an hindex of 16, co-authored 88 publications receiving 1040 citations. Previous affiliations of Pengbo Si include University of Florida & Beijing University of Posts and Telecommunications.
Papers
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Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues and Challenges
TL;DR: This survey investigates some of the work that has been done to enable the integrated blockchain and edge computing system and discusses the research challenges, identifying several vital aspects of the integration of blockchain andEdge computing: motivations, frameworks, enabling functionalities, and challenges.
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Virtualization for Distributed Ledger Technology (vDLT)
TL;DR: In the proposed virtualization for DLT (vDLT), the underlying resources are abstracted and by providing a logical view of resources, vDLT can significantly improve the performance, facilitate system evolution, and simplify DLT management and configuration.
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Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks With Mobile Edge Computing in Smart City
Meng Li,Pengbo Si,Yanhua Zhang +2 more
TL;DR: A novel vehicle network architecture in the smart city scenario, mitigating the network congestion with the joint optimization of networking, caching, and computing resources is proposed and formulated as a partially observable Markov decision process to minimize the system cost.
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Optimal Cooperative Internetwork Spectrum Sharing for Cognitive Radio Systems With Spectrum Pooling
TL;DR: This paper presents a cooperative scheme for internetwork spectrum sharing among multiple secondary systems, which takes into account the price and spectrum efficiency as the design criteria.
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Resource Optimization for Delay-Tolerant Data in Blockchain-Enabled IoT With Edge Computing: A Deep Reinforcement Learning Approach
TL;DR: This article introduces some promising technologies, such as edge computing and blockchain, and proposes a joint optimization framework about caching, computation, and security for delay-tolerant data in M2M communications networks based on dueling deep $Q$ -network (DQN).