Feature-Aware D2D Content Caching Strategy

Jing YANG; Jinke LI

doi:10.11999/JEIT190691

Volume 42 Issue 9

Sep. 2020

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Jing YANG, Jinke LI. Feature-Aware D2D Content Caching Strategy[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2201-2207. doi: 10.11999/JEIT190691

Citation:

Jing YANG, Jinke LI. Feature-Aware D2D Content Caching Strategy[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2201-2207. doi: 10.11999/JEIT190691

Jing YANG, Jinke LI. Feature-Aware D2D Content Caching Strategy[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2201-2207. doi: 10.11999/JEIT190691

Citation:

Jing YANG, Jinke LI. Feature-Aware D2D Content Caching Strategy[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2201-2207. doi: 10.11999/JEIT190691

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Feature-Aware D2D Content Caching Strategy

doi: 10.11999/JEIT190691

Jing YANG,
Jinke LI^,

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Optical Communication and Networks Key Laboratory of Chongqing, Chongqing 400065, China
3.
Ubiquitous Sensing and Networking Key Laboratory of Chongqing, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61871062, 61771082), The Program for Innovation Team Building at Institutions of Higher Education in Chongqing (CXTDX201601020)

Received Date: 2019-09-05
Rev Recd Date: 2020-05-03

Available Online: 2020-05-17

Publish Date: 2020-09-27

Abstract

Abstract

Device to Device (D2D) communications can effectively offload base station traffic. In D2D networks, the popular content is not only needs to be shared, but also the individual content is needs to be cached. In this paper, the problem of cache content selection is researched. A Content Social Value Prediction(CSVP) method based on feature perception is proposed. Value prediction can not only reduce latency, but also reduce the number of cache replacements and reduce cache costs. Firstly, the current value of content is calculated by combining user features and content features, and then future value is calculated through user social relationships. The small base station provides the user with a personalized content caching service according to the value of the content, and the base station selects a content with a larger value in the individual cache content of each small base station as popular content. Simulation results show that the caching strategy based on the proposed method can alleviate the base station traffic effectively, and reduce the delay by about 20%～40%.
- Edge network,
- D2D communication,
- Content caching,
- Exploration - exploitation,
- Value prediction

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References(17)

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