Abstract
Among the existing Content Center Networking (CCN) caching schemes, the most important category is popularity-based schemes which perform better than non-popularity-based in terms of cache-hits. However, these existing popularity-based caching schemes assumed that they provide services for a single type of applications and assumed that content requests (interest) conform to Zipf-like distribution. Although Zipf-like request distribution was validated in many network applications, this distribution may not exist at the node level in CCN when there exist multiple types of upper-level applications in the network. Once the traffic feature of Zipf-like distribution becomes less obvious, the existing popularity-based caching schemes could not work well. Therefore, how to predict the content request (interest) for each node becomes a key problem of caching design.
In this paper, we use the application-level relevance of interest to assist the caching design, rather than just relying on names. We propose a scheme (named as ICDCS) based on interest/content tag analyzing in which multiple types of upper-level applications produced contents/interests and tags is added as a part of name, then a measuring mechanism is designed to count and predict the trend of interest. Our scheme can be well combined with existed approaches and improve their caching performance. Simulations over various system parameters are done to validate the effectiveness and efficiency of ICDCS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jacobson, V., Smetters, D.K., Thornton, J.D., Plass, M.F., Briggs, N.H., Braynard, R.L.: Networking named content. In: International Conference on Emerging Networking Experiments and Technologies, pp. 117–124 (2009)
Zhang, G., Liu, J., Chang, X., Chen, Z.: Combining popularity and locality to enhance in-network caching performance and mitigate pollution attacks in content-centric networking. IEEE Access 5, 19012–19022 (2017)
Ioannou, A., Weber, S.: A survey of caching policies and forwarding mechanisms in information-centric networking. IEEE Commun. Surv. Tutorials 18, 2847–2886 (2016)
Fricker, C., Robert, P., Roberts, J., Sbihi, N.: Impact of traffic mix on caching performance in a content-centric network. In: 2012 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 310–315. IEEE (2012)
Quan, W., Xu, C., Guan, J., Zhang, H.: Scalable name lookup with adaptive prefix bloom filter for named data networking. IEEE Commun. Lett. 18, 102–105 (2014)
Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. (TOIS) 22, 5–53 (2004)
Din, I.U., Hassan, S., Khan, M.K., Guizani, M., Ghazali, O., Habbal, A.: Caching in information-centric networking: strategies, challenges, and future research directions. IEEE Commun. Surv. Tutorials 20, 1443–1474 (2018)
Wang, Y., Li, Z., Tyson, G., Uhlig, S.: Design and evaluation of the optimal cache allocation for content-centric networking. IEEE Trans. Comput. 65, 95–107 (2016)
Pacifici, V., Dán, G.: Coordinated selfish distributed caching for peering content-centric networks. IEEE/ACM Trans. Netw. 24, 1–12 (2016)
Duan, J., Wang, X., Xu, S.Z., Liu, Y.N., Xu, C., Zhao, G.F.: Cache scheme based on pre-fetch operation in ICN. Plos One 11, e0158260 (2016)
Wang, S., Bi, J., Wu, J., Vasilakos, A.V.: CPHR: in-network caching for information-centric networking with partitioning and hash-routing. IEEE/ACM Trans. Netw. 24, 1 (2015)
Breslau, L., Cao, P., Fan, L., Phillips, G., Shenker, S.: Web caching and Zipf-like distributions: evidence and implications. Proc. IEEE INFOCOM 1, 126–134 (1999)
Gu, Y., Chen, L., Tang, K.M.: A load balancing method under zipf-like requests distribution in DHT-based P2P network systems. In: 2009 International Conference on Web Information Systems and Mining, WISM 2009, pp. 656–660 (2009)
Mangili, M., Martignon, F., Capone, A.: Performance analysis of content-centric and content-delivery networks with evolving object popularity. Comput. Netw. 94, 80–98 (2015)
Afanasyev, A., Moiseenko, I., Zhang, L.: ndnSIM: NDN simulator for NS-3. University of California, Los Angeles, Technical report 4 (2012)
networking Index, C.V.: Forecast and methodology, 2016–2021, White Paper. San Jose, CA, USA 1 (2016)
Acknowledgements
This work was supported in part by the Natural Science Foundation of China under Grants 61672092 and 61572066, and in part by the Fundamental Research Funds for the Central Universities of China under Grants 2018JBZ103.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, G., Liu, J., Chang, X., Yang, Y. (2018). Interest Relevance-Based Caching Design in Content-Centric Networking. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_50
Download citation
DOI: https://doi.org/10.1007/978-3-030-05057-3_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05056-6
Online ISBN: 978-3-030-05057-3
eBook Packages: Computer ScienceComputer Science (R0)