Edge Computing and Digital Twins for Autonomous Systems

The field of autonomous systems is moving towards a tighter integration of communication, sensing, and computation, with a focus on edge computing and digital twins. This integration is expected to enable more efficient, scalable, and resilient systems, with applications in areas such as intelligent transportation and smart cities. Researchers are exploring novel architectures and algorithms to support the deployment of digital twins at the edge, leveraging technologies such as mobile edge computing and UAV-assisted edge computing. These advancements have the potential to significantly improve the performance and adaptability of autonomous systems, and to enable new use cases and applications. Noteworthy papers in this area include:

  • A paper that introduces a distributed computing architecture for integrating digital twins and mobile edge computing, which achieves significant reductions in synchronization errors and improvements in resource utilization.
  • A paper that proposes a nature-inspired architectural framework for building next-generation communication networks, leveraging digital twin technology and multi-population integration to enable dynamic coordination and evolutionary capabilities.

Sources

Intelligent Edge Resource Provisioning for Scalable Digital Twins of Autonomous Vehicles

[Social] Allostasis: Or, How I Learned To Stop Worrying and Love The Noise

Multi-Tier UAV Edge Computing for Low Altitude Networks Towards Long-Term Energy Stability

Toward Autonomous Digital Populations for Communication-Sensing-Computation Ecosystem

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