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An Adaptive Edge–Cloud-Based Integrated Framework for Real-Time XR Collaboration

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2026, 12(4), 17
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : July 13, 2026
  • Accepted : August 24, 2026
  • Published : August 31, 2026

Jung Soo Han 1

1백석대학교

Accredited

ABSTRACT

Extended Reality (XR) technologies have recently expanded into various fields, including smart manufacturing, digital twins, remote education, and healthcare. However, real-time XR collaboration still faces challenges such as network latency, input synchronization errors, global state inconsistency, and limitations of static feedback. To address these issues, this study proposes an adaptive Edge– Cloud-based XR collaboration framework. The proposed framework classifies input data into State and Event information for synchronization and distributes processing tasks between Edge and Cloud according to latency sensitivity, global state consistency requirements, and processing complexity. It also integrates AI-based context prediction and adaptive feedback into a unified process from input processing to user feedback. Through a comparative analysis with conventional XR collaboration architectures, the proposed framework was examined in terms of input processing, real-time responsiveness, data consistency, and feedback. This study presents an integrated mechanism that jointly determines synchronization methods and processing locations according to input characteristics and processing requirements.

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