Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks

Hyun Soung You; Ji Hong Kim; Won Yong Shin; Sang Wook Kim

doi:10.1109/PerComWorkshops51409.2021.9431023

Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks

Hyun Soung You, Ji Hong Kim, Won Yong Shin, Sang Wook Kim

Department of Computational Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	336-339
Number of pages	4
ISBN (Electronic)	9781665404242
DOIs	https://doi.org/10.1109/PerComWorkshops51409.2021.9431023
Publication status	Published - 2021 Mar 22
Event	2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021 - Kassel, Germany Duration: 2021 Mar 22 → 2021 Mar 26

Publication series

Name	2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021

Conference

Conference	2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021
Country/Territory	Germany
City	Kassel
Period	21/3/22 → 21/3/26

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the NRF grant funded by the Korea government (MSIT) (No. NRF-2020R1A2B5B03001960) and the IITP grant funded by the Korea government (MSIT) (No. 2020-0-01373, Artificial Intelligence Graduate School Program (Hanyang University)). This work was also supported in part by the Yonsei University Research Fund of 2020 (2020-22-0101).

Publisher Copyright:
© 2021 IEEE.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Hardware and Architecture
Software

Access to Document

10.1109/PerComWorkshops51409.2021.9431023

Cite this

You, H. S., Kim, J. H., Shin, W. Y., & Kim, S. W. (2021). Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks. In 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021 (pp. 336-339). [9431023] (2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PerComWorkshops51409.2021.9431023

You, Hyun Soung ; Kim, Ji Hong ; Shin, Won Yong et al. / Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks. 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 336-339 (2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021).

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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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note = "Funding Information: ACKNOWLEDGMENT This work was supported by the NRF grant funded by the Korea government (MSIT) (No. NRF-2020R1A2B5B03001960) and the IITP grant funded by the Korea government (MSIT) (No. 2020-0-01373, Artificial Intelligence Graduate School Program (Hanyang University)). This work was also supported in part by the Yonsei University Research Fund of 2020 (2020-22-0101). Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021 ; Conference date: 22-03-2021 Through 26-03-2021",

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You, HS, Kim, JH, Shin, WY & Kim, SW 2021, Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks. in 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021., 9431023, 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Institute of Electrical and Electronics Engineers Inc., pp. 336-339, 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Kassel, Germany, 21/3/22. https://doi.org/10.1109/PerComWorkshops51409.2021.9431023

Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks. / You, Hyun Soung; Kim, Ji Hong; Shin, Won Yong et al.
2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 336-339 9431023 (2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: ACKNOWLEDGMENT This work was supported by the NRF grant funded by the Korea government (MSIT) (No. NRF-2020R1A2B5B03001960) and the IITP grant funded by the Korea government (MSIT) (No. 2020-0-01373, Artificial Intelligence Graduate School Program (Hanyang University)). This work was also supported in part by the Yonsei University Research Fund of 2020 (2020-22-0101). Publisher Copyright: © 2021 IEEE.

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AB - 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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You HS, Kim JH, Shin WY, Kim SW. Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks. In 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 336-339. 9431023. (2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021). doi: 10.1109/PerComWorkshops51409.2021.9431023

Location-Aware Caching via Predicting Heterogeneous File Preferences in Mobile Networks

Abstract

Publication series

Conference

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

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