Multi-domain Network Data Flow Modeling with Virtual Links
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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 neighbor domains, leading to incorrect optimization and resource consumption, as they lack complete information about link capacities and flow rates across domains.
Innovation Solution
A method where network entities generate and update data flow models by measuring flow rates and comparing them with expected rates, using virtual links to account for discrepancies, thereby identifying bottleneck links within or outside their domain for improved resource management and QoS satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If network entities generate data flow models using only local domain information, then device complexity is reduced and ease of operation is improved, but measurement precision and reliability deteriorate due to limited visibility of neighbor domains
Solution Approach 1:
The patent introduces virtual links as intermediary elements that represent bottleneck links extending beyond the local domain. These virtual links act as mediators between the local data flow model and the unknown external domain characteristics, allowing the model to account for external bottlenecks without requiring direct visibility or complex inter-domain coordination.
Solution Approach 2:
The patent implements a feedback mechanism where the data flow model is continuously refined by comparing expected flow rates (from the model) with measured flow rates (from actual traffic). This feedback loop allows the model to self-correct and improve accuracy over time, compensating for the initial limitation of having only local domain information.
2Device complexity
If network entities use incomplete information about link capacities and flow rates, then device complexity is reduced, but productivity and reliability worsen due to incorrect optimization and resource consumption
Solution Approach 1:
The patent changes the parameter representation by introducing virtual links with specific parameters (capacity, bottleneck indication) that transform the data flow model from an incomplete local view to a more accurate representation of end-to-end traffic characteristics, enabling better resource allocation decisions.
Solution Approach 2:
Virtual links serve as intermediaries that bridge the gap between incomplete local information and the need for accurate end-to-end optimization. These virtual constructs allow the network entity to perform efficient resource allocation without requiring complete visibility into external domains.
3Reliability
If network entities perform continuous model updates with complete information, then reliability and measurement precision are improved, but device complexity and use of energy increase
Solution Approach 1:
The patent applies partial action by selectively updating only those aspects of the data flow model that are necessary based on measured flow rate discrepancies. Rather than continuously re-computing the entire model with complete information, the system performs targeted updates using virtual links to represent external bottlenecks, reducing computational overhead and energy consumption.
Solution Approach 2:
The feedback mechanism triggers model updates only when discrepancies between expected and measured flow rates indicate the need for refinement. This event-driven approach to updates improves reliability when necessary while avoiding unnecessary computational work and energy consumption during stable conditions.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network entity may generate a data flow model for a domain associated with the network entity, the domain being part of a multi-domain network. The network entity may obtain a set of measured flow rates and a set of expected flow rates that are calculated based at least in part on the data flow model. The network entity may selectively update the data flow model based at least in part on an accuracy of the data flow model, with the accuracy determined based at least in part on the set of measured flow rates and the set of expected flow rates. Numerous other aspects are described.