Data Flow Modeling Accuracy in Multi-Domain Wireless Networks
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Solution Overview
Problem
In multi-domain wireless communication networks, network entities face challenges in accurately generating data flow models due to limited visibility of network configurations in neighboring domains, leading to incorrect optimization and resource management, especially when bottleneck links are outside the domain of control.
Innovation Solution
A method where a network entity generates a data flow model for its domain and selectively updates it based on indications from neighboring domains, using virtual links to account for flow rates and bottlenecks outside its domain, ensuring accurate modeling and resource allocation across multiple domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a network entity generates a data flow model based only on its own domain configuration, then the modeling process is simple and fast, but the accuracy of the data flow model deteriorates due to limited visibility of neighboring domains
Solution Approach 1:
The patent introduces an intermediary mechanism where network entities exchange domain configuration information and data flow model indications with neighboring domains. This intermediary information exchange allows each entity to build a more accurate global data flow model without directly observing the entire network, resolving the contradiction between model accuracy and modeling complexity.
Solution Approach 2:
The patent segments the global network into multiple domains, each with its own data flow model. By dividing the complex global modeling task into smaller domain-level models and then integrating them, the system achieves accurate global visibility without requiring each entity to directly manage the entire network's complexity.
2Reliability
If a network entity uses virtual links to account for flows outside its domain, then the resource management accuracy improves, but the device complexity increases
Solution Approach 1:
The patent creates virtual links that copy or represent the behavior of actual network links outside the domain. These virtual links replicate the flow characteristics and bottleneck properties of external links, allowing the network entity to manage resources accurately without directly controlling or observing the external physical links, thus improving reliability while managing complexity.
3Measurement precision
If a network entity selectively updates its data flow model based on neighboring domain indications, then the model accuracy improves, but the information processing requirements and time increase
Solution Approach 1:
The patent implements selective updating where network entities only update portions of their data flow models when necessary, based on received indications from neighboring domains. Instead of continuously or completely recalculating the entire model, entities perform partial updates only when changes are detected, reducing the time and processing overhead while maintaining accuracy.
4Measurement precision
If a network entity has full visibility of all network paths, then the data flow model accuracy improves, but the information processing complexity and resource consumption increase
Solution Approach 1:
The patent segments the network into autonomous domains that each maintain their own data flow models. This segmentation allows each network entity to process only local domain information and exchange minimal summary information with neighbors, achieving global model accuracy without each entity needing to process or store information about the entire network, thus reducing energy consumption.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network entity may generate a first data flow model for a first set of paths that traverse the network entity. The first network entity may receive an indication of a second data flow model for a second set of paths that traverse a second network entity, the first set including at least one path that is within the second set. The first network entity may selectively update the first data flow model based at least in part on whether the indication of the second data flow model indicates an error in the first data flow model. Numerous other aspects are described.