TY - GEN
T1 - Edge Caching with Real-Time Guarantees
AU - Yang, Le
AU - Zheng, Fu Chun
AU - Jin, Shi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In recent years, optimization of the successful transmission probability (STP) in wireless cache-enabled networks has been studied extensively. However, few works have examined the real-time performance of the cache-enabled networks. In this paper, we investigate the performance of the cache-enabled networks with real-time guarantees by adopting age of information (AoI) as the metric to characterize the timeliness of the delivered information. We establish a spatial-temporal model by utilizing stochastic geometry and queueing theory which captures both the temporal traffic dynamics and the interferers' geographic distribution. Under the random caching framework, we achieve the closed-form expression of AoI by adopting the maximum average received power criterion for the user association. Finally, we formulate a convex optimization problem for the minimization of the Peak AoI(PAoI) and obtain the optimal caching probabilities by utilizing the Karush-Kuhn-Tucker (KKT) conditions. Numerical results demonstrate that the random caching strategy is a better choice than both the most popular caching (MPC) and uniform caching (UC) strategies when it comes to improving the real-time performance for the cached files as well as maintaining the file diversity.
AB - In recent years, optimization of the successful transmission probability (STP) in wireless cache-enabled networks has been studied extensively. However, few works have examined the real-time performance of the cache-enabled networks. In this paper, we investigate the performance of the cache-enabled networks with real-time guarantees by adopting age of information (AoI) as the metric to characterize the timeliness of the delivered information. We establish a spatial-temporal model by utilizing stochastic geometry and queueing theory which captures both the temporal traffic dynamics and the interferers' geographic distribution. Under the random caching framework, we achieve the closed-form expression of AoI by adopting the maximum average received power criterion for the user association. Finally, we formulate a convex optimization problem for the minimization of the Peak AoI(PAoI) and obtain the optimal caching probabilities by utilizing the Karush-Kuhn-Tucker (KKT) conditions. Numerical results demonstrate that the random caching strategy is a better choice than both the most popular caching (MPC) and uniform caching (UC) strategies when it comes to improving the real-time performance for the cached files as well as maintaining the file diversity.
KW - Age of information (AoI)
KW - cache-enabled networks
KW - caching strategy
KW - stochastic geometry
UR - https://www.scopus.com/pages/publications/85147034757
U2 - 10.1109/VTC2022-Fall57202.2022.10013080
DO - 10.1109/VTC2022-Fall57202.2022.10013080
M3 - 会议稿件
AN - SCOPUS:85147034757
T3 - IEEE Vehicular Technology Conference
BT - 2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022
Y2 - 26 September 2022 through 29 September 2022
ER -