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Optimal multilevel media stream caching in cloud-edge environment

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Abstract

Due to the problem of high link load of edge cache and small storage space of edge server, a caching architecture by the collaborative of edge nodes and the cloud server is proposed. The content cache location is designed and optimized, which can be the content provider, cloud server (CS), and edge node (EN). In the proposed system, cloud servers collaborate with edge servers and the performance of content caching can be improved by coordinating caching on the cloud server or caching on the edge server. In this paper, a cloud-edge collaborative caching model based on the greedy algorithm is proposed, which includes the content caching model and collaborative caching model. Network architecture, file popularity estimation, link capacity, and other factors are considered in the model. Correspondingly, a cloud-edge collaborative cache algorithm based on a greedy algorithm is proposed. The related optimization problem is decomposed into the knapsack problem of cache layout in each layer, and then the greedy algorithm is used to solve the knapsack problem of cache placement and cooperative cache proposed in this paper. The affiliation between CS cache and EN caches in the layered architecture is improved and recognized. In the experimental results, the link load is reduced, the cache hit rate is improved by using the proposed method of edge caching, and it also has obvious advantages in the average end-to-end service delay.

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References

  1. CISCO, Inc. Cisco visual networking index: global mobile data traffic forecast[R/OL. (2017–02). [2018–10–20].https:∥www cisco com/c/en/us/soltions/collateral /serviceprovider/visual-networking-index-vni /mobile-white-paperc11–520862.html.

  2. Bi SZ, Zhang R, Ding Z et al (2015) Wireless communications in the era of big data. IEEE Commun Mag 153(10):190–199

    Article  Google Scholar 

  3. Maddah M, Niesen U (2014) Fundamental limits of caching. IEEE Trans Inf Theory 60(5):2856–2867

    Article  MathSciNet  Google Scholar 

  4. Li X, Wang X, Zhu C, et al (2015) Caching-as-a-service: virtual caching framework in the cloud-based mobile networks. Computer Communications Workshops, pp. 372–377, IEEE

  5. Jiang Y, Ma M, Bennis M et al (2019) User preference learning-based edge caching for fog radio access network. IEEE Trans Wirel Commun 67(2):1268–1283

    Article  Google Scholar 

  6. Jiang Y, Huang W, Bennis M et al (2019) Decentralized asynchronous coded caching design and performance analysis in fog radio access networks. IEEE Trans Mobile Comput 1:1–12

    Article  Google Scholar 

  7. Cui X, Jiang Y, Chen X (2018) Graph-based cooperative caching in Fog-RAN. IEEE ICNC Workshops, pp. 1-6, IEEE

  8. Paschos GS, Iosifidis G, Tao M, Towsley D, Caire G (2018) The role of caching in future communication systems and networks. IEEE J Sel Areas Commun 36(6):1111–1125

    Article  Google Scholar 

  9. Müller S, Atan O, van der Schaar M et al (2017) Context-aware proactive content caching with service differentiation in wireless networks. IEEE Trans Wirel Commun 16(2):1024–1036

    Article  Google Scholar 

  10. Jie Hu, Lieliang Yang, Hanzo L (2017) Energy- efficient cross-layer design of wireless mesh networks for content sharing in online social networks. IEEE Trans Veh Technol 66(9):8495–8509

    Article  Google Scholar 

  11. Tandon R, Simeone O (2016) Cloud-aided wireless networks with edge caching: fundamental latency trade-offs in fog radio access networks. In: 2016 IEEE International Symposium on Information Theory (ISIT), pp. 2157-8117, IEEE

  12. Bastug E, Bennis M, Debbah M (2014) Living on the edge: the role of proactive caching in 5g wireless networks. IEEE Commun Mag 52(8):82–89

    Article  Google Scholar 

  13. Ahlehagh H, Dey S (2014) Video-aware scheduling and caching in the radio access network. IEEE/ACM Trans Netw 22(5):1444–1462

    Article  Google Scholar 

  14. Jiang W, Feng G, Qin S (2017) Optimal cooperative content caching and delivery policy for heterogeneous cellular networks. IEEE Trans Mob Comput 16(5):1382–1393

    Article  Google Scholar 

  15. Kwak J, Kim Y, Le LB, Chong S (2018) Hybrid content caching in 5G wireless networks: cloud versus edge caching. IEEE Trans Wirel Commun 17(5):3030–3045

    Article  Google Scholar 

  16. Li B, Rui L L, Qiu X, et al. (2019) Content caching strategy for edge and cloud cooperation computing. In: 2019 15th International Wireless Communications and Mobile Computing Conference (IWCMC).

  17. Ndikumana A, Ullah S, Leah T, et al. (2017) Collaborative cache allocation and computation offloading in mobile edge computing. In: 2017 19th Asia-Pacific Network Operations and Management Symposium (APNOMS).

  18. Tran TX, Le DV, Yue G, Pompili D (2018) Cooperative hierarchical caching and request scheduling in a cloud radio access network. IEEE Trans Mob Comput 17(12):2729–2743

    Article  Google Scholar 

  19. Tang J, Zhou Z, Xue X et al (2020) Using collaborative edge-cloud cache for search in the internet of things. IEEE Internet Things J 7(2):922–936

    Article  Google Scholar 

  20. Baccour E, Erbad A, Bilal K, et al. (2020) FacebookVideoLive18: A live video streaming dataset for streams metadata and online viewers locations. In: 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT), IEEE.

  21. Trzciński T, Rokita P (2017) Predicting the popularity of online videos using support vector regression. IEEE Transac Multim 19(11):2561–2570

    Article  Google Scholar 

  22. One in 5 Facebook videos is live. [Online]. Available:https://smallbiztrends.com/2018/04/facebook-live-stats.html.

  23. Bastug E, Bennis M, Debbah M (2014) Living on the edge:the role of proactive caching in 5G wireless networks. IEEE Commun Magaz 52(8):82–89

    Article  Google Scholar 

  24. Hou T, Feng G, Qin S et al. (2018) Proactive content caching by exploiting transfer learning for mobile edge computing. In: Globecom IEEE Global Communications Conference, IEEE.

  25. Li C, Song M, Chongchong Yu, Luo YL (2021) Mobility and marginal gain based content caching and placement for cooperative edge-cloud computing. Inf Sci 548(16):153–176

    Article  Google Scholar 

  26. Li C, Song M, Zhang M, Luo Y (2020) Effective replica management for improving reliability and availability in edge-cloud computing environment. J Parallel Distrib Comput 143:107–128

    Article  Google Scholar 

  27. Li C, Bai J, Yi C, Luo Y (2020) Resource and replica management strategy for optimizing financial cost and user experience in edge cloud computing system. Inf Sci 516:33–55

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The work was supported by Key Research and Development Plan of Hubei Province (No.2020BAB102), Beijing Intelligent Logistics System Collaborative Innovation Center Open Project (No.BILSCIC-2019KF-02). Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

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Authors and Affiliations

  1. School of Information, Beijing Wuzi University, Beijing, 101149, China

    Hengliang Tang & Chunlin Li

  2. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Chunlin Li, Yihan Zhang & Youlong Luo

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  1. Hengliang Tang
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  2. Chunlin Li
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Correspondence to Youlong Luo.

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Tang, H., Li, C., Zhang, Y. et al. Optimal multilevel media stream caching in cloud-edge environment. J Supercomput 77, 10357–10376 (2021). https://doi.org/10.1007/s11227-021-03683-x

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