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Online data caching in edge-cloud collaborative system with the data center

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Abstract

In edge computing, the edge node can provide certain accessible storage and computing resources for the surrounding users. Caching data on the edge node can quickly retrieve the required data and complete the user’s requests with low delay. However, the resources of edge servers are limited and sometimes have to gain the data by transfering from other servers or buying from data centers at the cloud. Traditionally, data center is just regard as a place of purchasing data, and the data is always available for the buyer after purchase. However, we believe that these data have a validity period. After the buyer purchases the data, it only provides limited calls for free. Based on this assumption, in this paper, we study the data caching problem in the edge-cloud collaborative system to minimize the total cost. Without knowing the information of users’ future request flow, we propose an online algorithm. What’s more, the asymptotic competition ratio of the algorithm in the worst case is 3.

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Acknowledgements

This work is supported by Third Xinjiang Scientific Expedition Program (Grant No. 2021xjkk1300), NSFC 12071460 and Fundamental Research Project of Shenzhen City (No. JCYJ20210324102012033).

Funding

Funding was provided by Third Xinjiang Scientific Expedition Program (Grant Number 2021xjkk1300), NSFC (Grant Number 12071460), Shenzhen Fundamental Research Program (Grant Number JCYJ20210324102012033).

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Authors and Affiliations

  1. School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen, China

    Xinxin Han

  2. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Sijia Dai, Guichen Gao, Yang Wang & Yong Zhang

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  1. Xinxin Han
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  2. Sijia Dai
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  3. Guichen Gao
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  4. Yang Wang
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  5. Yong Zhang
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Correspondence to Yong Zhang.

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A preliminary version of this paper was in AAIM 2021 Han et al. (2021)

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Han, X., Dai, S., Gao, G. et al. Online data caching in edge-cloud collaborative system with the data center. J Comb Optim 44, 3351–3363 (2022). https://doi.org/10.1007/s10878-022-00892-9

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