Online Digital Twin-Empowered Content Resale Mechanism in Age of Information-Aware Edge Caching Networks
CoRR(2024)
Abstract
For users requesting popular contents from content providers, edge caching
can alleviate backhaul pressure and enhance the quality of experience of users.
Recently there is also a growing concern about content freshness that is
quantified by age of information (AoI). Therefore, AoI-aware online caching
algorithms are required, which is challenging because the content popularity is
usually unknown in advance and may vary over time. In this paper, we propose an
online digital twin (DT) empowered content resale mechanism in AoI-aware edge
caching networks. We aim to design an optimal two-timescale caching strategy to
maximize the utility of an edge network service provider (ENSP). The formulated
optimization problem is non-convex and NP-hard. To tackle this intractable
problem, we propose a DT-assisted Online Caching Algorithm (DT-OCA). In
specific, we first decompose our formulated problem into a series of
subproblems, each handling a cache period. For each cache period, we use a
DT-based prediction method to effectively capture future content popularity,
and develop online caching strategy. Competitive ratio analysis and extensive
experimental results demonstrate that our algorithm has promising performance,
and outperforms other benchmark algorithms. Insightful observations are also
found and discussed.
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