Wireless Network Data Supervision for Queue Management
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Solution Overview
Problem
Existing wireless networks face challenges in efficiently supervising data traffic and managing queue fullness at base stations, which can lead to service quality issues and user experience degradation.
Innovation Solution
A method and system for supervising data in wireless networks, which involves noting times associated with data packets, evaluating the service provided by base stations based on these times, and determining whether actions should be taken to reduce queue fullness or improve service quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data traffic is increased to improve network utilization, then productivity is improved, but queue fullness at base stations increases leading to service quality degradation
Solution Approach 1:
The patent implements a feedback mechanism where the supervisor notes times associated with data packets, evaluates service quality based on these times, and determines actions to reduce queue fullness when service quality degrades. This closed-loop feedback system dynamically adjusts traffic management based on real-time queue conditions, allowing high network utilization while preventing service quality degradation through timely corrective actions.
2Productivity
If queue capacity is increased to handle more data, then productivity is improved, but the time to clear queues increases leading to longer delays
Solution Approach 1:
The supervisor performs preliminary evaluation of service quality by noting packet times and assessing queue fullness before queues become completely full. This allows proactive traffic management actions to be taken in advance, preventing excessive queue buildup and reducing the overall time required for queue clearance while maintaining high data handling capacity.
3Reliability
If traffic management actions are taken to reduce queue fullness, then service quality is improved, but network utilization decreases
Solution Approach 1:
The supervisor applies partial traffic management actions by determining whether actions should be performed based on evaluated service quality metrics. Rather than continuously reducing traffic, actions are applied partially or selectively when queue fullness reaches certain thresholds, thereby improving service quality while minimizing the impact on network utilization through targeted rather than blanket traffic reduction.
Data Source
AI summary
Examples of methods, systems, and computer program products relating to supervising data in a wireless network are disclosed. At least part of a system may be located between a packet data network and a base station, and/or may be at least logically separate from the base station. The system may be capable of evaluating the service provided by the base station, and may be capable of determining whether or not any action should consequently be performed. Examples of an action may include an action which may not necessarily affect en-route data packets such as outputting a report, and/or an action which may affect en-route data packets such as delaying packets, not delaying packets, and/or stopping the delaying of packets. An action which affects data packets may or may not affect data packets uniformly. An action may or may not result in an improvement in quality of user experience.