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Cache Partitioning and Caching Strategies for Device-to-Device Caching Systems

Authors
Rim, MinjoongKang, Chung G.
Issue Date
2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Device-to-device communication; Base stations; Performance evaluation; Wireless networks; High frequency; Explosions; Broadband communication; D2D caching; wireless caching; mobile caching; content preference; cache partitioning; data offloading
Citation
IEEE ACCESS, v.9, pp.8192 - 8211
Indexed
SCIE
SCOPUS
Journal Title
IEEE ACCESS
Volume
9
Start Page
8192
End Page
8211
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/130018
DOI
10.1109/ACCESS.2021.3049442
ISSN
2169-3536
Abstract
The amount of traffic in wireless networks is increasing exponentially, and this problem can be mitigated using device-to-device (D2D) caching technology, which installs a cache on a mobile end device. Devices can reduce the cell load through self-offloading via content in their own cache and D2D offloading using content in others' caches. However, especially in the early stage of D2D caching systems, a limited number of devices with a small storage might be used, and it is required to develop a caching scheme with excellent performance despite the small cache size. Regarding content popularity, which is common to most users, the preference probability values are not concentrated on some pieces of content, making it difficult to achieve satisfactory performance using a small cache. On the other hand, when considering individual users, content preferences may contain large values for specific content based on individual characteristics. In addition, the performance can be improved by considering short-term content preferences that reflect changes in content preferences over time or newly created content during peak hours. In this article, the hit ratio is divided into six parts considering self- and D2D offloading, common and individual user preferences, and little and large temporal changes in content preferences during peak hours. We also conceptually divide the cache of a helper into six areas in relation to the six parts of the hit ratio, and discuss cache partitioning and proactive caching strategies according to the environment.
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