MBBR Mode Selection for Adaptive SCS Flow Roaming
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Solution Overview
Problem
Existing MBBR mode selection for Stream Classification Service (SCS) flows does not account for dynamic network conditions and application-specific requirements, leading to suboptimal roaming experiences.
Innovation Solution
An Access Point (AP) determines the MBBR mode based on application-specific roaming requisites, flow features, or using a machine learning model to select the optimal mode that balances complexity and seamless roaming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed MBBR mode is used for all SCS flows, then device complexity is reduced, but adaptability to different application requirements deteriorates
Solution Approach 1:
The patent implements dynamic MBBR mode selection by evaluating multiple modes (Mode 1, Mode 2, Mode 3) based on real-time conditions including application type, network conditions, and flow characteristics. The Access Point dynamically determines the optimal mode for each SCS flow rather than using a fixed configuration, thereby achieving adaptability while managing complexity through structured decision logic.
Solution Approach 2:
The system changes operational parameters by selecting different MBBR modes based on varying conditions such as application requirements (voice, video, data), network load, and client capabilities. This parameter-based approach allows the system to adapt to different scenarios without requiring complete system redesign, resolving the contradiction between adaptability and complexity.
2Reliability
If MBBR mode is selected based on application profiles, then roaming reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring application profiles with specific MBBR mode preferences and roaming parameters before actual roaming occurs. When a client device connects, the system matches the detected application type against pre-defined profiles to quickly determine the appropriate mode, improving reliability through preparedness while reducing real-time processing complexity.
Solution Approach 2:
The system uses copying by creating standardized application profiles that replicate optimal roaming configurations for different application types. Instead of analyzing each roaming scenario from scratch, the system copies proven configurations from matching profiles, thereby improving reliability through reuse while simplifying the decision process.
3Adaptability or versatility
If MBBR mode is determined based on flow features, then adaptability to flow characteristics is improved, but measurement and detection difficulty increases
Solution Approach 1:
The patent extracts key flow features from the complete set of possible network parameters, focusing only on the most relevant characteristics such as packet size distribution, throughput, latency, and application type. By taking out only the essential features needed for mode selection rather than analyzing all possible flow parameters, the system achieves adaptability while reducing detection and measurement complexity.
Data Source
AI summary
Make-Before-Break Roaming (MBBR) mode selection for a Stream Classification Service (SCS) flow may be provided. An Access Point (AP) may receive SCS request from a station for a SCS flow. The SCS request may include MBBR requisites for the SCS flow. The AP may determine a MBBR mode for the SCS flow based on the MBBR requisites and a MBBR mode policy. The AP may configure the determined MBBR mode for the SCS flow. The AP may send a SCS response for the SCS request to the station. The SCS response may include the determined MBBR mode for the SCS flow.