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
conference contribution
posted on 2018-07-02, 10:28 authored by Yining Hua, Lin GuanLin Guan, Kostas KyriakopoulosKostas KyriakopoulosIn 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 - SIGMOBILECitation
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
2018Notes
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/10.1145/3213344.3213352ISBN
9781450358378Publisher version
Language
- en