Caching and Update Strategy Based on Content Popularity and Information Freshness for Fog Radio Access Networks

JIANG Fan; LIANG Xiao; SUN Changyin; WANG Junxuan

doi:10.11999/JEIT220373

Volume 44 Issue 9

Sep. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(9): 3108-3116

JIANG Fan, LIANG Xiao, SUN Changyin, WANG Junxuan. Caching and Update Strategy Based on Content Popularity and Information Freshness for Fog Radio Access Networks[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3108-3116. doi: 10.11999/JEIT220373

Citation:

JIANG Fan, LIANG Xiao, SUN Changyin, WANG Junxuan. Caching and Update Strategy Based on Content Popularity and Information Freshness for Fog Radio Access Networks[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3108-3116. doi: 10.11999/JEIT220373

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Caching and Update Strategy Based on Content Popularity and Information Freshness for Fog Radio Access Networks

doi: 10.11999/JEIT220373 cstr: 32379.14.JEIT220373

1.
School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
2.
Shaanxi Key Laboratory of Information Communication Network and Security, Xi’an 710121, China

Funds: The National Natural Science Foundation of China (62071377, 62101442), Shaanxi Province Key Industry Innovation Chain (Group) (2019ZDLGY07-06), The Graduate Student Innovation Foundation Project of Xi’an University of Posts and Telecommunications (CXJJYL2021063)

Received Date: 2022-03-31
Accepted Date: 2022-08-05
Rev Recd Date: 2022-08-04

Available Online: 2022-08-09

Publish Date: 2022-09-19

Abstract

Abstract

Introducing edge caching into fog radio access networks can effectively reduce the redundancy of content transmission. However, the existing content caching strategies consider rarely the dynamic nature of already cached content. A caching update algorithm based on content popularity and information freshness is proposed. The proposed algorithm considers fully the mobility of users and the temporal and spatial dynamics of content popularity. Furthermore, the Age of Information (AoI) is introduced to achieve a dynamic content update procedure. More specifically, the proposed algorithm adopts initially a Bidirectional Long Short-Term Memory network (Bi-LSTM) to predict the user's location in the next period according to the user's historical location information. Secondly, according to the acquired user location, combined with the user's preference model, the content popularity of each location area is obtained accordingly, and the most popular content will be cached at the Fog Access Points(F-APs). Finally, concerning AoI requirements of the already cached content, the caching update window can be dynamically adjusted to achieve a high-efficient and low-latency caching process. Simulation results demonstrate that the proposed algorithm improves effectively the content cache hit rate, and also minimizes the average delay of content transmission while ensuring the timeliness of the information.
- Fog radio networks,
- Edge caching,
- Age of Information (AoI),
- Content popularity prediction

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References(18)

References

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