Fine-grained resource adjustment of edge server in cloud-edge collaborative environment

Author:

Peng Yu,Hao JiaORCID,Chen Yang,Gan Jianhou

Funder

Youth Project of Applied Basic Research Program of Yunnan Province

National Natural Science Foundation of China

Key Project of Applied Basic Research Program of Yunnan Province

Publisher

Springer Science and Business Media LLC

Reference37 articles.

1. Zhou, Z., Chen, X., Li, E., et al.: Edge intelligence: paving the last mile of artificial intelligence with edge computing [J]. Proc. IEEE 107(8), 1738–1762 (2019)

2. China academy of information and communications technology, research report on key technologies situation of cloud-edge collaboration. [EB/OL]. http://ww w.caict.ac.cn/ 2023

3. Abaker, I., Badrul, N.: The rise of “Big Data” on cloud computing: review and open research issues [J]. Inf. Syst. 47, 98–115 (2015)

4. Keshavarzi, A., Haghighat, A., Bohlouli, M.: Enhanced time-aware QoS prediction in multi-cloud: a hybird k-medoids and lazy learning approach (QoPC) [J]. Computing 102(4), 923–949 (2020)

5. Youpeng, Tu., Haiming, C., Linjie, Y.: Edge computing offloading decision-making problem in Internet of Things systems: modeling, solution and classification [J]. Small Microcomput. Syst. 42(10), 2145–2152 (2021)

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