Abstract
With the development of computer networks, the amount of network information continues to grow. To facilitate the transfer of the increasing information, a content distribution network (CDN) is developed by adding an intermediate layer on the existing network. Technically, Caching strategy of CDN is the most important mechanism, which heavily impacts the CDN performance. On the other hand, considering the cost of operating CDN, some strategies have been proposed, aiming to save the CDN cost in terms of, e.g., power energy. This paper makes a brief review on the recent developments of CDN in terms of its caching strategy and operation cost, and discusses some potential development directions of CDN.
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Stocker, V., Smaragdakis, G., Lehr, W., Bauer, S.: The growing complexity of content delivery networks: challenges and implications for the internet ecosystem. Telecommun. Policy 41(2), 1003–1016 (2017)
Sahoo, J., et al.: A survey on replica server placement algorithms for content delivery networks. IEEE Commun. Surv. Tutorials 19(2), 1002–1026 (2016)
Shuai, Q., Wang, K., Miao, F., Jin, L.: A cost-based distributed algorithm for load balancing in content delivery network. In: 2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Hangzhou, China, pp. 11–15. IEEE (2017)
Kyryk, M., Pleskanka, N., Pleskanka, M.: The analysis of the optimal data distribution method at the content delivery network. In: 2019 IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), Polyana, Ukraine, pp. 1–4. IEEE (2019)
Xu, K., Li, X., Bose, S.K., Shen, G.: Joint replica server placement, content caching, and request load assignment in content delivery networks. IEEE Access 6(2), 17968–17981 (2018)
Zhang, G., Li, Y., Lin, T.: Caching in information centric networking: a survey. Comput. Netw. 57(16), 3128–3141 (2013)
Lal, K.N., Kumar, A.: A centrality-measures based caching scheme for content-centric networking (CCN). Multimedia Tools Appl. 77(14), 17625–17642 (2018)
Tang, S.Y., Alnoman, A., Anpalagan, A., Woungang, I.: A user‐centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks. Trans. Emerg. Telecommun. Technol. 29(8), e3461 (2018)
Sun, S.S., Jiang, W., Feng, G., Qin, S., Yuan, Y.: Cooperative caching with content popularity prediction for mobile edge caching. Tehnicki Vjesnik-Technical Gazette 26(2), 503–509 (2019)
Yao, L., Chen, A.L., Deng, J., Wang, J.B., Wu, G.W.: A cooperative caching scheme based on mobility prediction in vehicular content centric networks. IEEE Trans. Veh. Technol. 67(6), 5435–5444 (2018)
Su, Z., Hui, Y.L., Xu, Q.C., Yang, T.T., Liu, J.Y., Jia, Y.J.: An edge caching scheme to distribute content in vehicular networks. IEEE Trans. Veh. Technol. 67(6), 5346–5356 (2018)
He, H.J., Zhao, Y., Wu, J.F., Tian, Y.: Cost-aware capacity provisioning for internet video streaming CDNs. Comput. J. 58(12), 3255–3270 (2015)
Simulation-transactions of the society for modeling and simulation international. http://sage.cnpereading.com/paragraph/article/10.1177/0037549719862023. Accessed 30 Sept 2019
Lin, M.H., Wierman, A., Andrew, L.L.H., Thereska, E.: Dynamic right-sizing for power-proportional data centers. IEEE/ACM Trans. Networking 21(5), 1378–1391 (2013)
Mathew, V., Sitaraman, R.K., Shenoy, P.: Energy-aware load balancing in content delivery networks. In: IEEE INFOCOM, vol. 12, pp. 954–962. IEEE Press, Orlando (2012)
Tchernykh, A., Cortes-Mendoza, J.M., Pecero, J.E., Bouvry, P., Kliazovich, D.: Adaptive energy efficient distributed VoIP load balancing in federated cloud infrastructure. In: 3rd IEEE International Conference on Cloud Networking, pp. 1–6. IEEE Press, Luxembourg (2014)
Liao, D., Sun, G., Yang, G.H., Chang, V.: Energy-efficient virtual content distribution network provisioning in cloud-based data centers. Future Gener. Comput. Syst. Int. J. Sci. 83, 347–357 (2018)
Bar-Yehuda, R., Kantor, E., Kutten, S., Rawitz, D.: Growing half-balls: minimizing storage and communication costs in content delivery networks. SIAM J. Discrete Math. 32(3), 1903–1921 (2018)
Ahmed, F., Shafiq, M.Z., Khakpour, A.R., Liu, A.X.: Optimizing internet transit routing for content delivery networks. IEEE-ACM Trans. Netw. 26(1), 76–89 (2018)
Fatin, H.Z., Jamali, S., Fatin, G.Z.: Data replication in large scale content delivery networks: a genetic algorithm approach. J. Circ. Syst. Comput. 27(12), 1850189 (2018)
Tseng, L., DeAntonis, J., Higuchi, T., Altintas, O.: Peer-assisted content delivery network by vehicular micro clouds. In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet), Tokyo, Japan, pp. 1–3. IEEE (2018)
Salahuddin, M.A., Sahoo, J., Glitho, R., Elbiaze, H., Ajib, W.: A survey on content placement algorithms for cloud-based content delivery networks. IEEE Access 6(8), 91–114 (2018)
Mahesh, G., Maheswara Rao, V.V.R., Shankar, R.S., Sirisha, G.V.G.: Primal-dual parallel algorithm for optimal content delivery in cloud CDNs. In: 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore, India, pp. 1–6. IEEE (2017)
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Zhao, J., Liang, P., Liufu, W., Fan, Z. (2020). Recent Developments in Content Delivery Network: A Survey. In: Shen, H., Sang, Y. (eds) Parallel Architectures, Algorithms and Programming. PAAP 2019. Communications in Computer and Information Science, vol 1163. Springer, Singapore. https://doi.org/10.1007/978-981-15-2767-8_9
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DOI: https://doi.org/10.1007/978-981-15-2767-8_9
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