Network Topology Optimization for Metaverse Services
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Solution Overview
Problem
Existing telecommunications networks face challenges in managing network topology to efficiently provide metaverse services, balancing cost, user experience, and network capacity constraints.
Innovation Solution
A method and system that receive user metrics, network-associated requirements, and computing-system-associated requirements to generate a network-site implementation plan that minimizes cost functions, using integer programming to determine optimal network topology for metaverse service deployments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network topology is optimized for metaverse services, then service quality and user experience improve, but network complexity and deployment costs increase
Solution Approach 1:
The patent applies parameter changes by optimizing network topology through mathematical programming that adjusts network parameters (bandwidth, latency, node selection) to meet metaverse service requirements while managing complexity. The system changes network configuration parameters dynamically based on service demands and user metrics.
Solution Approach 2:
The patent implements preliminary action by pre-planning and optimizing network topology before metaverse service deployment. The system performs advance calculations using integer programming to determine optimal network configurations, avoiding complex ad-hoc adjustments during service operation.
2Productivity
If network capacity is increased to support metaverse services, then data rate and service performance improve, but infrastructure costs increase
Solution Approach 1:
The patent uses parameter changes to optimize the relationship between network capacity and cost. The mathematical programming model adjusts capacity allocation parameters to achieve required data rates for metaverse services while minimizing infrastructure investment by selecting optimal network paths and nodes.
Solution Approach 2:
The patent applies partial action by allocating network capacity selectively rather than uniformly across the entire network. The system provides excessive capacity only where and when needed for metaverse services, rather than upgrading the entire network infrastructure, thus reducing overall costs while meeting performance requirements.
3Adaptability or versatility
If network topology is customized for different metaverse services, then service-specific requirements are met, but network management complexity increases
Solution Approach 1:
The patent implements universality by creating a unified network topology optimization framework that handles multiple different metaverse services through a single mathematical programming approach. The system uses universal parameters and constraints that can accommodate various service requirements (AR, VR, MR, social networking) without requiring separate management systems for each service type.
Solution Approach 2:
The patent uses parameter changes to achieve service-specific customization within a unified management framework. The optimization model adjusts parameters such as bandwidth allocation, latency constraints, and node selection based on service-specific requirements, allowing adaptable network configuration without increasing management complexity.
4Measurement precision
If user metrics and requirements are collected and analyzed, then service quality improves, but data processing requirements and system complexity increase
Solution Approach 1:
The patent introduces an intermediary optimization system that collects user metrics and service requirements, then translates them into network configuration decisions through mathematical programming. This intermediary layer processes the data systematically, reducing the complexity burden on both the data collection and network management systems by providing a structured transformation process.
Data Source
AI summary
Systems, methods, and processing nodes for managing network topology perform and/or comprise: receiving user metrics associated with a community of interest; obtaining network-associated requirements for each of a plurality of services deployed on a network, at least a portion of the plurality of services being metaverse services; obtaining computing-system-associated requirements for each of the plurality of services; and based on the user metrics, the network-associated requirements, and the computing-system-associated requirements, generating a network-site implementation plan recommendation that minimizes one or more cost functions.