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Abstract ：
Mobile edge computing (MEC) enables mobile devices (MDs) to offload computation-intensive tasks to edge servers to support a variety of latency-sensitive emerging applications (such as the Internet of Vehicles, real-time video analytics, etc.). However, the time-varying communication link environment of signal occlusion and interference between MDs and edge servers often leads to disappointing offloading benefits. Reconfigurable intelligent surface (RIS) is recognized as a promising technology in sixth-generation communication networks, with great potential to intelligently adjust the phase shift and amplitude of reflective elements to enhance wireless network capabilities. This paper proposes a novel computation offloading algorithm for RIS empowered MEC networks. Specifically, we comprehensively consider the optimization problems of delay, energy consumption, and operator cost in the process of computation offloading, and model it as a Markov decision process. To overcome the continuous action space challenge, we propose a computation offloading algorithm based on Deep Deterministic Policy Gradient (DDPG) to jointly optimize the phase shift and amplitude of RIS, offloading decision, and MEC resource allocation strategy. Finally, compared with various other benchmark algorithms, our proposed algorithm has a significant performance improvement over non-RIS learning algorithms and other classical algorithms, and maintains the optimal performance. © 2022 Elsevier B.V.
Keyword ：
6G; Computation offloading; Deep Deterministic Policy Gradient; Mobile edge computing; Reconfigurable intelligent surface; Resource allocation
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| GB/T 7714 | Zhang, X. , Wu, W. , Liu, S. et al. An efficient computation offloading and resource allocation algorithm in RIS empowered MEC [J]. | Computer Communications , 2023 , 197 : 113-123 . |
| MLA | Zhang, X. et al. "An efficient computation offloading and resource allocation algorithm in RIS empowered MEC" . | Computer Communications 197 (2023) : 113-123 . |
| APA | Zhang, X. , Wu, W. , Liu, S. , Wang, J. . An efficient computation offloading and resource allocation algorithm in RIS empowered MEC . | Computer Communications , 2023 , 197 , 113-123 . |
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Abstract ：
Driven by advanced 5G cellular systems, mobile edge computing (MEC) has emerged as a promising technology that can meet the energy efficiency and latency requirements of IoT applications. Edge service migration in the MEC environment plays an important role in ensuring user service quality and enhancing terminal computing capabilities. Application services on the edge side should be migrated from different edge servers to edge nodes closer to users, so that services follow users and ensure high-quality services. In addition, during the migration process, edge services face security challenges in an edge network environment without centralized management. To tackle this challenge, this paper innovatively proposes a blockchain-based security edge service migration framework, Falcon, which uses mobile agents different from VM and container as edge service carriers, making migration more flexible. Furthermore, we considered the dependencies between agents and designed a service migration algorithm to maximize the migration benefits and obtain better service quality. In order to ensure the migration of edge services in a safe and reliable environment, Falcon maintains an immutable alliance chain among multiple edge clouds. Finally, the experimental results show that 'Falcon'has lower energy consumption and higher service quality. © 2020 Xiangjun Zhang et al.
Keyword ：
5G mobile communication systems Blockchain Energy efficiency Energy utilization Green computing Mobile agents Quality of service
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| GB/T 7714 | Zhang, Xiangjun , Wu, Weiguo , Yang, Shiyuan et al. Falcon: A Blockchain-Based Edge Service Migration Framework in MEC [J]. | Mobile Information Systems , 2020 , 2020 . |
| MLA | Zhang, Xiangjun et al. "Falcon: A Blockchain-Based Edge Service Migration Framework in MEC" . | Mobile Information Systems 2020 (2020) . |
| APA | Zhang, Xiangjun , Wu, Weiguo , Yang, Shiyuan , Wang, Xiong . Falcon: A Blockchain-Based Edge Service Migration Framework in MEC . | Mobile Information Systems , 2020 , 2020 . |
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