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Semi-Edge From Edge Caching to Hierarchical Caching in Network Fog.pdf (979.45 kB)

Semi-edge: From edge caching to hierarchical caching in network fog

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conference contribution
posted on 2018-07-02, 10:28 authored by Yining Hua, Lin GuanLin Guan, Kostas KyriakopoulosKostas Kyriakopoulos
In recent content delivery mechanisms, popular contents tend to be placed closer to the users for better delivery performance and lower network resource occupation. Caching mechanisms in Content Delivery Networks (CDN), Mobile Edge Clouds (MECs) and fog computing have implemented edge caching paradigm for different application scenarios. However, state-of-the-art caching mechanisms in literature are mostly bounded by application scenarios. With the rapid development of heterogeneous networks, the lack of uniform caching management has become an issue. Therefore, a novel caching mechanism, Semi-Edge caching (SE), is proposed in this paper. SE caching mechanism is based on in-network caching technique and it could be generically applied into various types of network fog. Furthermore, two content allocation strategies, SE-U (unicast) and SE-B (broadcast), are proposed within SE mechanism. The performance of SE-U and SE-B are evaluated in three typical topologies with various scenario contexts. Compared to edge caching, SE can reduce latency by 7% and increase cache hit ratio by 45%.

History

School

  • Science

Department

  • Physics

Published in

EdgeSys 2018 - SIGMOBILE

Citation

HUA, Y., GUAN, L. and KYRIAKOPOULOS, K.G., 2018. Semi-edge: From edge caching to hierarchical caching in network fog. IN: Proceedings of the 1st International Workshop on Edge Systems, Analytics and Networking (EdgeSys'18 ), Munich, June 10- 15th.

Publisher

© Association for Computing Machinery (ACM)

Version

  • AM (Accepted Manuscript)

Publication date

2018

Notes

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 1st International Workshop on Edge Systems, Analytics and Networking (EdgeSys'18 ), https://doi.org/10.1145/3213344.3213352

ISBN

9781450358378

Language

  • en

Location

Munich

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