Dynamic Network Slice Allocation for Variable QoE Demands

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Solution Overview

Problem

Mobile media networks face challenges in maintaining optimal quality of experience due to variable network demands, as existing technologies often result in inefficient resource allocation and suboptimal performance across different applications with changing resource needs and network conditions.

Innovation Solution

Dynamic network slicing is implemented using band-level network APIs, predicting future resource demands and network conditions to assign mobile devices to appropriate network slices, allowing for scalable resource allocation based on predicted needs and conditions, thereby optimizing quality of experience.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If static network resource allocation is used, then device complexity is reduced, but quality of experience deteriorates under variable network demands

Engineering Contradiction:

Improvequality of experienceVSAvoidnetwork resource allocation complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements dynamic network slicing where network resources are not statically allocated but continuously adjusted based on real-time network conditions and application requirements. The network slice configuration changes dynamically to match varying QoE demands, transforming the rigid static allocation into a flexible dynamic system that adapts to changing conditions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system employs feedback mechanisms by monitoring network conditions and application performance metrics, then using this information to adjust network slice configurations. The network controller receives feedback about actual QoE delivery and resource utilization, and adjusts slicing parameters accordingly to maintain optimal performance.

Inventive Principle:

Principle #23Feedback

2Reliability

If network resources are over-allocated to ensure QoE, then quality of experience is maintained, but resource utilization efficiency deteriorates

Engineering Contradiction:

Improvequality of experience consistencyVSAvoidnetwork resource waste

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent changes key parameters of network slice configuration (bandwidth allocation, latency requirements, packet loss thresholds) based on actual network conditions and application needs. Rather than maintaining fixed over-provisioned parameters, the system adjusts these parameters dynamically to match actual demand, preventing both over-allocation and under-allocation.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The network slice resources transition from static over-provisioning to dynamic allocation that scales with actual demand. When network conditions are good and application demands are low, resources are reduced. When conditions deteriorate or demands increase, resources are expanded, optimizing the balance between QoE consistency and resource efficiency.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If network slicing is implemented without prediction, then device complexity is reduced, but adaptability to future network conditions deteriorates

Engineering Contradiction:

Improveresponse to changing network demandsVSAvoidnetwork slice management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by predicting future network conditions and application resource needs before they actually occur. The network controller uses prediction algorithms to anticipate upcoming QoE requirements and proactively adjusts network slice configurations in advance, allowing the system to adapt smoothly to changing conditions rather than reacting passively.

Inventive Principle:

Principle #10Preliminary action

4Productivity

If static network configuration is used, then ease of operation is improved, but productivity under variable conditions deteriorates

Engineering Contradiction:

Improvenetwork resource utilization efficiencyVSAvoidnetwork configuration complexity

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The network slicing system operates autonomously through self-service mechanisms where the network controller automatically monitors conditions, predicts requirements, and adjusts slice configurations without manual intervention. The system self-manages the complexity of dynamic resource allocation, freeing operators from manually configuring and reconfiguring network slices while maintaining high productivity under variable conditions.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20240422849A1Quality of experience optimization to meet variable network demands

Publication Date: 2024.12.19 AT&T INTELLECTUAL PROPERTY I L P

AI summary

In one example, a method includes instructing a mobile device of a user to establish a connection with an application server via a first network slice, where the first network slice is configured based on an initial resource need of a network connected application executing on the mobile device and an initial set of network conditions, sending, to the mobile device, a prediction of at least one network condition for the first network slice at a time in the future, receiving, from the mobile device, an indication of an updated resource need of the network connected application, and providing, to the mobile device, instructions for establishing a connection to the application server over a second network slice, where the second network slice is configured based on the updated resource need and a current set of network conditions.