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UID:936@lincs.fr
DTSTART;TZID=Europe/Paris:20260212T140000
DTEND;TZID=Europe/Paris:20260212T150000
DTSTAMP:20260218T103543Z
URL:https://www.lincs.fr/events/metalore-learning-to-orchestrate-communica
 tion-and-computation-for-metaverse-synchronization/
SUMMARY:MetaLore: Learning to Orchestrate Communication and Computation for
 Metaverse Synchronization
DESCRIPTION:As augmented and virtual reality evolve\, achieving seamless
 synchronization between physical and digital realms remains a critical
 challenge\, especially for real-time applications where delays affect the
 user experience. This paper presents MetaLore\, a Deep Reinforcement
 Learning (DRL) based framework for joint communication and computational
 resource allocation in Metaverse or digital twin environments.\n\nMetaLore
 dynamically shares the communication bandwidth and computational resources
 among sensors and mobile devices to optimize synchronization\, while
 offering high throughput performance. Special treatment is given in
 satisfying end-to-end delay guarantees. A key contribution is the
 introduction of two novel Age of Information (AoI) metrics: Age of Request
 Information (AoRI) and Age of Sensor Information (AoSI) — integrated into
 the reward function to enhance synchronization quality.\n\nAn open source
 simulator has been extended to incorporate and evaluate the approach. The
 DRL solution is shown to achieve the performance of full-enumeration
 brute-force solutions by making use of a small\, task-oriented observation
 space of two queue lengths at the network side. This allows the DRL
 approach the flexibility to effectively and autonomously adapt to dynamic
 traffic conditions.
CATEGORIES:Seminars,Youtube
LOCATION:Amphi 7\, 19 Place Marguerite Perey\, Palaiseau\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=19 Place Marguerite Perey\,
 Palaiseau\, France;X-APPLE-RADIUS=100;X-TITLE=Amphi 7:geo:0,0
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TZID:Europe/Paris
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DTSTART:20251026T020000
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