Dynamic MTU Adjustment for Wireless QoS Optimization
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Solution Overview
Problem
Wireless networks face challenges in dynamically adjusting maximum transmission unit (MTU) parameters to optimize communication efficiency and quality of service (QoS) for varying traffic types and user equipment (UE) conditions, leading to issues like packet fragmentation and dropped packets.
Innovation Solution
Implementing a dynamic MTU adjustment system that uses artificial intelligence/machine learning techniques to predictively adjust MTU sizes based on QoS parameters, service level agreements, network slices, traffic types, and UE attributes, allowing for granular control of MTU configurations on a per-UE or per-UE group basis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed MTU size is used in wireless networks, then device complexity is reduced and ease of operation is improved, but communication efficiency deteriorates and packet fragmentation increases
Solution Approach 1:
The patent implements dynamic MTU adjustment by allowing the MTU size to change based on network conditions, traffic types, and UE attributes. The network can selectively apply different MTU sizes for different UEs or UE groups, transforming the static MTU parameter into a dynamic one that adapts to varying communication requirements, thereby improving communication efficiency without requiring complex manual configuration
Solution Approach 2:
The patent changes the MTU parameter value based on different conditions such as traffic type, QoS requirements, and network slice. By adjusting the MTU size parameter dynamically, the system optimizes packet transmission efficiency for different scenarios while maintaining manageable complexity through automated decision-making algorithms
2Productivity
If MTU size is increased to reduce fragmentation, then communication efficiency improves, but packet loss risk increases and reliability deteriorates
Solution Approach 1:
The patent applies different MTU sizes to different UEs or UE groups based on their specific requirements, traffic types, and QoS parameters. Instead of using a uniform MTU size, the system tailors the MTU parameter locally for each communication scenario, optimizing both efficiency and reliability for different types of traffic and devices
Solution Approach 2:
The system dynamically adjusts MTU size based on real-time network conditions and traffic characteristics. For time-sensitive or reliability-critical traffic, the system can select smaller MTU sizes to reduce loss risk, while for less critical traffic, larger MTU sizes improve efficiency, creating a dynamic balance between these competing requirements
3Productivity
If dynamic MTU adjustment is implemented, then communication efficiency improves and packet fragmentation reduces, but device complexity and system complexity increase
Solution Approach 1:
The patent implements automated MTU adjustment mechanisms where the network system itself determines and applies appropriate MTU sizes based on pre-configured policies, QoS parameters, and traffic analysis. This self-service approach eliminates the need for manual MTU configuration while achieving optimized communication efficiency, managing complexity through automation rather than human intervention
Solution Approach 2:
The system performs preliminary configuration of MTU adjustment policies and criteria before actual communication occurs. By pre-establishing the rules and parameters for dynamic MTU selection, the system prepares the framework for efficient automated decision-making, reducing the complexity of real-time adjustments while maintaining high communication efficiency
4Productivity
If larger MTU sizes are used for large data transfers, then productivity improves, but packet loss and errors increase
Solution Approach 1:
The patent dynamically changes the MTU parameter based on the characteristics of the data being transferred. For large data transfers, the system can initially use larger MTU sizes to improve efficiency, but automatically adjusts to smaller sizes when packet loss or errors are detected, creating a adaptive parameter adjustment mechanism that balances efficiency and reliability based on actual transfer conditions
Data Source
AI summary
A system described herein may identify a requested communication session between a UE and a network, such as a core of a wireless network. The system may identify Quality of Service (“QoS”) information associated with the UE and/or the requested communication session. The QoS information may include or may be based on a network slice identifier, a QoS value, a Service Level Agreement (“SLA”), one or more models associated with UE attributes, or other suitable information. The system may determine a maximum transmission unit (“MTU”) configuration for the UE based on the identified QoS information and/or models that associate UE attributes to MTU configurations. The system may implement the determined MTU configuration, including providing the MTU configuration to one or more gateways or endpoints of the network and/or to the UE. The UE and the network may accordingly use the MTU configuration when communicating via the requested communication session.