Virtualized Architecture for Network Parameter Identification
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Solution Overview
Problem
Manual configuration of system parameters in communication networks is impractical due to the exponential number of possible combinations, leading to suboptimal performance and increased costs in testing all combinations for desired network performance.
Innovation Solution
A virtualized architecture utilizing reinforcement learning and a virtualized testbed to generate and test system parameter combinations, emulating network traffic scenarios and assigning rewards based on key performance indicators to identify optimal parameter settings for improved network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration of system parameters is performed, then network component performance can be optimized, but the complexity and time required to test all possible parameter combinations increases exponentially
Solution Approach 1:
The patent creates a virtualized copy of the network component and its operating environment. Instead of testing parameters on physical hardware, the system uses virtual machines to replicate network components, allowing exhaustive parameter combination testing in a virtual environment without the constraints and costs of physical device testing. This virtual copy enables comprehensive optimization while avoiding the exponential complexity burden of physical testing.
Solution Approach 2:
The system performs preliminary configuration and testing of system parameters in the virtualized environment before deploying to physical network components. By pre-testing all parameter combinations in virtual machines, the optimal configuration is determined in advance, eliminating the need for complex on-site parameter tuning and reducing the practical complexity of deployment.
2Measurement precision
If all system parameter combinations are tested to ensure optimal performance, then the accuracy of parameter identification improves, but the time and computational resources required increase exponentially
Solution Approach 1:
Virtual machines serve as computationally efficient copies of physical network components. These virtual representations allow the system to evaluate all possible parameter combinations rapidly without the time constraints of physical device testing. The virtual environment maintains measurement precision while dramatically reducing the time required to complete exhaustive parameter sweeps.
Solution Approach 2:
The virtualized testing environment enables continuous, uninterrupted parameter testing. Unlike physical hardware that may require reconfiguration or physical access between tests, virtual machines can rapidly transition between parameter states without downtime. This continuous action allows exhaustive testing to be completed in fraction of the time it would take with physical devices.
3Productivity
If extensive testing of system parameters is conducted to improve network performance, then operational efficiency and resource utilization improve, but the cost and complexity of the testing infrastructure increase
Solution Approach 1:
The patent merges the testing function with the operational environment by using virtual machines that can serve both as test subjects and as deployable network components. The same virtual infrastructure used for testing becomes the deployment target, eliminating the need for separate dedicated testing hardware. This consolidation reduces infrastructure complexity while enabling comprehensive parameter optimization that improves network productivity.
Data Source
AI summary
One or more computing devices, systems, and/or methods for system parameter identification and network component configuration are provided. A state comprising a system parameter combination, a traffic model, and a channel assignment may be generated. A network traffic scenario is executed through a virtualized testbed using the state. A reward for the system parameter combination may be generated based upon key performance indicators output by the network traffic scenario. A reward policy and rewards generated for system parameter combinations are used to select a system parameter combination that is used to configure a network component of a communication network.