Digital Twin Network Geometric Modeling for Edge Resource Optimization

The patent segments the digital twin representation into multiple resolution levels (coarse and fine geometric models). The system maintains a coarse representation by default and only generates detailed fine representations when needed, based on contextual variables and operational requirements. This segmentation allows the system to reduce computational resource consumption while maintaining the capability to process information on-demand when required.

The patent implements dynamic adjustment of digital twin representations based on contextual variables such as node operational status, communication conditions, and processing requirements. The system dynamically switches between different levels of detail and updates representations only when necessary, rather than maintaining constant high-fidelity models. This dynamic approach optimizes the balance between information processing capability and resource consumption.

The patent applies local quality by creating digital twin representations with varying levels of detail tailored to specific contextual requirements. Instead of uniformly high-fidelity representations across the entire network, the system generates detailed representations only for nodes and regions where they are actually needed for effective orchestration and monitoring, thereby reducing overall computing resource demands on near-edge nodes.

The patent changes key parameters of the digital twin representation such as geometric detail level, update frequency, and data granularity based on contextual variables. By adjusting these parameters dynamically according to operational needs and resource availability, the system maintains effective orchestration capability while adapting computing resource consumption to match actual requirements.

The patent applies partial action by transmitting only the necessary level of detail in digital twin data based on current operational requirements. The system sends coarse representations during normal conditions and only transmits detailed fine representations when specific contextual variables indicate they are needed, thereby reducing communication bandwidth consumption while maintaining information accuracy when required.

The patent implements preliminary action by pre-establishing coarse digital twin representations and indexing structures before detailed data transmission is needed. This allows the system to quickly generate detailed representations only when required, rather than continuously transmitting high-fidelity data, thus reducing overall communication bandwidth requirements while maintaining the ability to provide accurate information on-demand.