articleIEEE Transactions on Mobile ComputingJan 19, 2024Closed access

Diffusion-Based Reinforcement Learning for Edge-Enabled AI-Generated Content Services

Nanyang Technological University · University of Electronic Science and Technology of China · +4 more institutions

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Abstract

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which deploys AIGC models in wireless edge networks to ensure broad AIGC services accessibility for Metaverse users. Nonetheless, an important aspect of providing personalized user experiences requires carefully selecting AIGC Service Providers (ASPs) capable of effectively executing user tasks, which is complicated by environmental uncertainty and variability. Addressing…

Citation impact

153
total citations
FWCI
47.95
Percentile
100%
References
55
Citations per year

Authors

7

Topics & keywords

Keywords
  • Computer science
  • Reinforcement learning
  • Service discovery
  • Wireless
  • Service (business)
  • Enhanced Data Rates for GSM Evolution
  • Key (lock)
  • Artificial intelligence
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