Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks
- Authors
- You, Hyun-Soung; Kim, Ji-Hong; Shin, Won-Yong; Kim, Sang-Wook
- Issue Date
- May-2021
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Caching; collaborative filtering; content-centric network; data imputation; location awareness
- Citation
- 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, pp.336 - 339
- Indexed
- SCOPUS
- Journal Title
- 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021
- Start Page
- 336
- End Page
- 339
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/141919
- DOI
- 10.1109/PerComWorkshops51409.2021.9431023
- ISSN
- 0000-0000
- Abstract
- We present a new caching method in content-centric networks (CCNs) where each mobile user is equipped with finite-size cache and device-to-device content delivery is employed. In this study, we exploit the heterogeneity in file preferences among users who are moving around different locations (e.g., points-of-interest) in caching. Moreover, to infer our model parameter more accurately, we apply data imputation, which is a technique to replace unknown data with estimated values, based on collaborative filtering (CF). Our experimental results with real-world datasets demonstrate the superiority of our method over benchmark caching methods utilizing no location information in terms of both average hit ratio and runtime complexity.
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