Task placement and resource allocation for computing power network: validation on video stream processing system

Linjiang Shen; Shuqing Qiu; Chao Cui; Zhaobin Li; Jundong Xu; Yan Xu

doi:10.1117/12.3011529

7 December 2023 Task placement and resource allocation for computing power network: validation on video stream processing system

Linjiang Shen, Shuqing Qiu, Chao Cui, Zhaobin Li, Jundong Xu, Yan Xu

Author Affiliations +

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129411V (2023) https://doi.org/10.1117/12.3011529
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Computing power network is an emerging paradigm to meet the increasing computation demands and improve the system performance. Video stream processing is one of the important scenarios of computing power network, which puts strict demands on the limited edge computing and network resources. In this paper, a decision-making agent is constructed by a deep reinforcement learning algorithm, and the offloading location and resource allocation of video processing tasks are dynamically decided based on the system load, task status and service quality. A unique advantage is that the algorithm is model-free and does not rely on numerous system assumptions. By constructing the test-bed system, it is verified that the proposed method can achieve the optimization of task delay and energy consumption in real AI video stream processing scenarios. Future research directions are discussed in terms of the theory and system design.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Linjiang Shen, Shuqing Qiu, Chao Cui, Zhaobin Li, Jundong Xu, and Yan Xu "Task placement and resource allocation for computing power network: validation on video stream processing system", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129411V (7 December 2023); https://doi.org/10.1117/12.3011529

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