Dynamic Token Rate Adjustment for Fair LTE Packet Scheduling
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Solution Overview
Problem
Current priority queuing and scheduling mechanisms in LTE communication networks fail to provide fair and efficient Quality of Service (QoS) by not adequately handling the dynamic allocation of resources among different Non-GBR traffic partitions, leading to unfair packet loss and resource allocation issues, especially when the transport network is a bottleneck.
Innovation Solution
A method and arrangement that adjust token rates for each traffic class based on measured incoming traffic rates to ensure fair scheduling, using a token distribution mechanism that allocates resources dynamically among GBR and Non-GBR classes, ensuring equal packet loss across all traffic classes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If priority queuing mechanisms are used to schedule data packets, then QoS classification is maintained, but fair resource allocation among Non-GBR traffic partitions is not achieved
Solution Approach 1:
The patent applies dynamics by making the token generation rate adjustable rather than fixed. The token generation rate is dynamically adapted based on the incoming traffic rate measured during a measurement period, allowing the system to respond to changing traffic conditions and achieve fair resource allocation among Non-GBR traffic partitions while maintaining QoS classification.
2Ease of operation
If fixed token rates are used for scheduling, then scheduling simplicity is maintained, but fair scheduling under varying traffic conditions is not achieved
Solution Approach 1:
The patent implements feedback by measuring the incoming traffic rate during a measurement period and using this measurement to adjust the token generation rate. This closed-loop feedback mechanism ensures that the scheduling system adapts to actual traffic conditions, achieving fair scheduling while remaining operationally simple.
3Device complexity
If token rates are not adjusted based on traffic conditions, then system complexity is reduced, but packet loss becomes unequal across traffic classes
Solution Approach 1:
The system performs self-service by automatically measuring its own incoming traffic rate and adjusting its token generation rate accordingly, without requiring external intervention. This self-adjusting mechanism achieves equal packet loss across traffic classes while keeping the system relatively simple, as the adjustment is performed autonomously based on observed conditions.
Data Source
AI summary
The present invention relates to a method and an arrangement for scheduling data packets each belonging to a particular traffic class associated with a certain quality of service (QoS) level and transmitted between a first communication network node and a second communication network node. Initially a token rate for assigning tokens to each traffic class is set and an incoming traffic rate of each traffic class is measured by counting a number of incoming data packets during a pre-determined period of time. Then, based on said measured incoming traffic rate said token rate is adjusted in order to obtain a fair scheduling of data packets belonging to different traffic classes.