Abstract
This paper studies the computation offloading and resource allocation of Multi-access Edge Computing Networks (MEC) networks under stochastic task arrivals and imperfect channle state conditions (CSI). We aim to minimize the energy consumptions of all mobile users (MUs) while satisfying the stability of all MUs’ queues by optimizing the transmit power, computational frequency and offloading ratio. The problem is modeled as a a long-term average stochastic optimization problem which cannot be solved trivially. To address this, we firstly apply the Lyapunov framework to transform the long-term average optimization problem into a series of per-slot optimization subproblems, and then an iterative optimization method is proposed to decompose the perslot optimization subproblem into three toy problems. The simulation results demonstrate the convergence and performance of the proposed algorithm.
This work is supported by the National Natural Science Foundation of China under Grant 62171158 and the Research Fund Program of Guangdong Key Laboratory of Aerospace Communication and Networking Technology under Grant 2018B030322004.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Wang, M., Shi, S., Wang, X. (2023). Dynamic Computation Offloading and Resource Allocation for Multi-access Edge Computing Networks. In: Li, A., Shi, Y., **, L. (eds) 6GN for Future Wireless Networks. 6GN 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 504. Springer, Cham. https://doi.org/10.1007/978-3-031-36011-4_2
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DOI: https://doi.org/10.1007/978-3-031-36011-4_2
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