Per-Class Load Management in 802.11 WLANs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current WLANs face challenges in proactive load management, particularly for real-time services like VoIP, due to the lack of effective classification of voice terminals and inadequate resource management, leading to potential voice degradation and network congestion.
Innovation Solution
The method involves proactive load management in 802.11 WLANs by collecting per-class station count information and traffic specifications, allowing for classification of wireless stations based on access categories, user priorities, or services, and influencing association decisions between stations and access points to balance load and maintain service quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proactive load management is implemented to maintain GoS, then the probability of unsuccessful sessions is reduced, but the complexity of classifying and managing different user classes increases
Solution Approach 1:
The patent segments wireless stations into different classes based on service type (voice, video, data) and applies separate load management thresholds and metrics for each class. This allows the system to manage GoS for each service category independently, reducing the overall complexity by breaking down the monolithic load management problem into manageable segments with class-specific parameters.
Solution Approach 2:
The patent implements preliminary classification of wireless stations into different service classes before load management decisions are made. By pre-categorizing stations based on their service requirements and establishing class-specific thresholds in advance, the system avoids complex real-time classification during load management, thereby reducing operational complexity while maintaining reliable GoS.
2Measurement precision
If per-class station count metrics are collected and used for load management, then the precision of load assessment is improved, but the amount of information to be processed and transmitted increases
Solution Approach 1:
The patent extracts only the essential per-class station count metrics needed for load management decisions rather than collecting and processing all possible network parameters. By selecting and transmitting only the critical class-based counts and thresholds, the system achieves precise load assessment while minimizing information overhead and avoiding unnecessary data transmission.
Solution Approach 2:
The patent applies different levels of measurement detail to different service classes based on their specific requirements. For example, voice services may require more precise real-time station count monitoring compared to best-effort data services. This localized approach to measurement precision ensures accurate load assessment where needed while reducing information overhead for less critical services.
3Measurement precision
If available admission capacity information is provided for all user priorities, then QoS selection accuracy is improved, but the network signaling overhead increases
Solution Approach 1:
The patent implements partial information provision by supplying available admission capacity data only for the most critical user priorities and service classes rather than all possible categories. This allows roaming stations to make accurate QoS decisions for high-priority services while reducing signaling overhead by omitting less critical information, applying the principle of doing just enough to achieve the required QoS selection accuracy.
Data Source
Figure 1
Figure 2~4
Figure 5~6
AI summary
An apparatus and method proactively managing the load of an 802.11 WLAN based on one or more per-class station counts, in which the stations are classified according to access categories, user priorities, or services. Alternatively, the load of an 802.11 WLAN may also be proactively managed based on provisional or non-provisional per-class traffic specification, depending upon the status of traffic streams. Load balancing may be achieved by (a) collecting per-class station count information, either through an AP, or through exchanges with neighboring APs or wireless stations, and (b) proactively influencing association decisions between wireless stations and APs.