期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 70, 期 1, 页码 1013-1018出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3044073
关键词
Task analysis; Servers; Protocols; Uplink; Downlink; Energy consumption; Time-frequency analysis; Mobile edge computing; task offloading; energy efficient; resource allocation; convex optimization
资金
- National Research Foundation (NRF) through the Ministry of Science, ICT, and Future Planning (MSIP), Korea Government [2017R1A2B3012316]
- NRF through the Ministry of Science, ICT (MSIT), Korea Government [2019R1F1A1060648]
- National Research Foundation of Korea [2019R1F1A1060648] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This paper investigates an asynchronous offloading protocol for mobile edge computing systems, addressing a joint optimization problem of transmit power, offloading size, and time-frequency resources to minimize the energy consumption of the system. By applying convex optimization techniques, the optimal solution for the asynchronous MEC offloading problem can be obtained. Numerical results demonstrate the effectiveness of the proposed asynchronous protocol over traditional synchronous approaches.
This paper investigates an asynchronous offloading protocol for mobile edge computing (MEC) systems where the computational tasks of mobile users are partially offloaded to a MEC server at a base station (BS). In the proposed asynchronous approach, upload, computation, and download of the tasks are performed in an asymmetric and non-orthogonal manner. A joint optimization problem of the transmit power, the offloading size, and the time-frequency resources is addressed to minimize the energy consumption of the overall system. By applying convex optimization techniques, the optimal solution for the asynchronous MEC offloading problem can be obtained. Numerical results demonstrate the effectiveness of the proposed asynchronous protocol over the conventional synchronous approach.
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