AoI-Delay Tradeoff in Mobile Edge Caching: A Lyapunov Optimization-Based Method

Mobile edge caching (MEC) is a promising technique to improve the quality of service (QoS) for mobile users (MU) by bringing data to the network edge. However, optimizing the crucial QoS aspects of message freshness and service promptness, measured by age of information (AoI) and service delay, respectively, entails a tradeoff due to their competition for shared edge resources. This article investigates this tradeoff by formulating their weighted sum minimization as a sequential decision-making problem, incorporating high-dimensional, discrete-valued, and linearly constrained design variables. First, to assess the feasibility of the considered problem, we characterize the corresponding achievable region by deriving its superset with the rate stability theorem and its subset with a novel stochastic policy, and develop a sufficient condition for the existence of solutions. Next, to efficiently solve this problem, we propose a mixed-order drift-plus-penalty algorithm by jointly considering the linear and quadratic Lyapunov drifts and then optimizing them with dynamic programming (DP). Finally, by leveraging the Lyapunov optimization technique, we demonstrate that the proposed algorithm achieves an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(1/V)$ </tex-math></inline-formula> versus <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(V)$ </tex-math></inline-formula> tradeoff for the average AoI and average service delay.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-02-13
DOI
https://doi.org/10.1109/jiot.2025.3531415
Citations
3
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
4.46
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article

AoI-Delay Tradeoff in Mobile Edge Caching: A Lyapunov Optimization-Based Method

Dong Yang, Lei Yang, Ran Li, Xiaoqi Qin et al.
3 citations
IEEE Internet of Things Journal
Caching and Content Delivery
4.46
article

AoI-Delay Tradeoff in Mobile Edge Caching: A Lyapunov Optimization-Based Method

Dong Yang, Lei Yang, Ran Li, Xiaoqi Qin, Chuan Huang, Zhen-Xin Fu
article en
3 citations

Abstract

Mobile edge caching (MEC) is a promising technique to improve the quality of service (QoS) for mobile users (MU) by bringing data to the network edge. However, optimizing the crucial QoS aspects of message freshness and service promptness, measured by age of information (AoI) and service delay, respectively, entails a tradeoff due to their competition for shared edge resources. This article investigates this tradeoff by formulating their weighted sum minimization as a sequential decision-making problem, incorporating high-dimensional, discrete-valued, and linearly constrained design variables. First, to assess the feasibility of the considered problem, we characterize the corresponding achievable region by deriving its superset with the rate stability theorem and its subset with a novel stochastic policy, and develop a sufficient condition for the existence of solutions. Next, to efficiently solve this problem, we propose a mixed-order drift-plus-penalty algorithm by jointly considering the linear and quadratic Lyapunov drifts and then optimizing them with dynamic programming (DP). Finally, by leveraging the Lyapunov optimization technique, we demonstrate that the proposed algorithm achieves an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(1/V)$ </tex-math></inline-formula> versus <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(V)$ </tex-math></inline-formula> tradeoff for the average AoI and average service delay.

IEEE Internet of Things JournalVol. 12(11)
University of Nevada, Reno (US), Beijing University of Posts and Telecommunications (CN), Beijing Jiaotong University (CN), Chinese University of Hong Kong, Shenzhen (CN), Shenzhen Technology University (CN)
Openalex Percentile: Top 6%
Caching and Content Delivery
4.46
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