TY - GEN
T1 - Privacy-preserving distributed edge caching for mobile data offloading in 5G networks
AU - Zeng, Yiming
AU - Huang, Yaodong
AU - Liu, Ji
AU - Yang, Yuanyuan
N1 - Publisher Copyright:
©2020 IEEE
PY - 2020/11
Y1 - 2020/11
N2 - —Distributed edge caching has drawn great attention with the fast development of smart edge devices. Caching popular contents in the edge can reduce latency and improve the quality of service of edge mobile users. Meanwhile, the data privacy in the edge is critical to preserve the privacy of individual users and devices. How to jointly determine the caching and routing policy in the edge network in a distributed manner and simultaneously design the proper privacy preserving mechanism are challenging. We tackle these challenges in two progressive steps. First, we design a distributed algorithm which can achieve the global optimum. Second, we propose a privacy-preserving mechanism based on differential privacy and prove the privacy guarantee. We conduct extensive numerical simulations based on real-world requests to evaluate the performance of the proposed distributed algorithm and the privacy mechanism. Results highlight a significant improvement of the proposed distributed algorithm while only up to 10.1% of the total serving cost increased by the privacy mechanism.
AB - —Distributed edge caching has drawn great attention with the fast development of smart edge devices. Caching popular contents in the edge can reduce latency and improve the quality of service of edge mobile users. Meanwhile, the data privacy in the edge is critical to preserve the privacy of individual users and devices. How to jointly determine the caching and routing policy in the edge network in a distributed manner and simultaneously design the proper privacy preserving mechanism are challenging. We tackle these challenges in two progressive steps. First, we design a distributed algorithm which can achieve the global optimum. Second, we propose a privacy-preserving mechanism based on differential privacy and prove the privacy guarantee. We conduct extensive numerical simulations based on real-world requests to evaluate the performance of the proposed distributed algorithm and the privacy mechanism. Results highlight a significant improvement of the proposed distributed algorithm while only up to 10.1% of the total serving cost increased by the privacy mechanism.
KW - 5G networks
KW - Differential privacy
KW - Distributed algorithm
KW - —Edge caching
UR - https://www.scopus.com/pages/publications/85102000553
U2 - 10.1109/ICDCS47774.2020.00106
DO - 10.1109/ICDCS47774.2020.00106
M3 - Conference contribution
AN - SCOPUS:85102000553
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 541
EP - 551
BT - Proceedings - 2020 IEEE 40th International Conference on Distributed Computing Systems, ICDCS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 40th IEEE International Conference on Distributed Computing Systems, ICDCS 2020
Y2 - 29 November 2020 through 1 December 2020
ER -