Hardware Model-Aware Joint Offloading and Resources Allocation Optimization

doi:10.13190/j.jbupt.2021-143

Journal of Beijing University of Posts and Telecommunications ›› 2022, Vol. 45 ›› Issue (2): 22-28.doi: 10.13190/j.jbupt.2021-143

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Hardware Model-Aware Joint Offloading and Resources Allocation Optimization

ZHI Jialin, WANG Nan, MAN Yi, TENG Yinglei

School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2021-07-13 Published:2021-12-16

Abstract

Abstract: The traditional researches on edge computing offloading do not involve the details of computer hardware implementation. In addition, their computing model is rough, and the optimization scheme has low accuracy. To solve these problems, a hardware-based scheme that jointly optimizes computing offloading and resource allocation for multi-user multi-edge server is proposed. In particular, the details of hardware implementation in the calculation process are considered. From the perspective of the granularity of computer instruction execution, the input/output bottleneck and the energy consumption of memory functional modules are calculated first. Then, the joint optimization model is re-established. Finally, the system energy consumption is minimized on the premise of meeting the delay requirement of offloading tasks. To solve the high-dimensional problem of action space, a hybrid online two-part matching kuhn-munkras algorithm based on deep deterministic policy gradient is adopted. The simulation results show that the memory energy consumption cannot be ignored. Besides, the proposed optimization algorithm can effectively learn the optimal strategy and has a significant effect on reducing the system energy consumption.

Key words: mobile edge computing, computer pipelining, online bipartite matching, deep reinforcement learning

CLC Number:

TN911.22

ZHI Jialin, WANG Nan, MAN Yi, TENG Yinglei. Hardware Model-Aware Joint Offloading and Resources Allocation Optimization[J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(2): 22-28.

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Hardware Model-Aware Joint Offloading and Resources Allocation Optimization

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