Popularity-Based Hierarchical Caching for Next Generation Content Delivery Networks

Nima Najaflou*, Selin Sezer, Zeynep Gürkaş Aydın, Berk Canberk

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

More than half of the content over the Internet is carried by content delivery networks (CDNs). CDNs cache popular and most requested contents on the edges of the network. Thus helping to increase Quality of Experience (QoE), e.g., by decreasing time to first byte (TTFB) for different contents. In the present paper, we focus on developing a hierarchical caching structure for CDNs to improve their QoE. We focus on unpopular content here, since it accounts for a big portion of content over the Internet. Our novel data-driven method forms caching clusters or hierarchies to deal with unpopular contents. In order to form our clusters and assign edge servers into these clusters, we consider the pattern in which contents have been requested including the total number of requests, similar objects between two edge servers, and requests for those objects. Using tf- idf method, which is widely used in information retrieval, we find the similarities between requests landed on each of our edge servers and use these similarities to form clusters using the Markov Clustering algorithm. We evaluate our approach using different hierarchical models, and with real-world requests from a large-scale global CDN. We demonstrate that our hierarchical caching approach improves cache hit ratio by 9.05 %. Additionally, a 7.39 % decrease in TTFB is observed.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIndustrial Networks and Intelligent Systems - 7th EAI International Conference, INISCOM 2021, Proceedings
EditörlerNguyen-Son Vo, Van-Phuc Hoang, Quoc-Tuan Vien
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar73-87
Sayfa sayısı15
ISBN (Basılı)9783030774233
DOI'lar
Yayın durumuYayınlandı - 2021
Etkinlik7th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2021 - Hanoi, Viet Nam
Süre: 22 Nis 202123 Nis 2021

Yayın serisi

AdıLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Hacim379
ISSN (Basılı)1867-8211
ISSN (Elektronik)1867-822X

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???event.eventtypes.event.conference???7th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2021
Ülke/BölgeViet Nam
ŞehirHanoi
Periyot22/04/2123/04/21

Bibliyografik not

Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

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