Weighted MEC Selection for Application-Based Traffic Steering
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Solution Overview
Problem
Current Multi-Access Edge Computing (MEC) steering techniques lack the ability to dynamically consider the current status of third-party developed MEC platforms, user equipment device location, and network performance parameters, leading to suboptimal traffic steering in complex network environments.
Innovation Solution
A centralized database generates MEC selection weight values based on current user equipment location, application status, and network performance parameters, enabling mobile network service providers to dynamically steer traffic to the most suitable MEC platforms, owned by either the provider or third-party developers, for reduced latency and improved network efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current MEC steering techniques are used, then traffic routing is simplified, but traffic steering becomes suboptimal in complex network environments
Solution Approach 1:
The patent introduces a centralized database as an intermediary component that stores and manages MEC platform status information, user equipment location data, and network performance parameters. This intermediary enables the steering function to access real-time information without directly managing the complexity of collecting and processing data from multiple sources, thus optimizing traffic steering while maintaining system modularity.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors MEC platform status, user equipment location, and network performance parameters, then uses this feedback information to dynamically adjust traffic steering decisions. The centralized database stores historical and real-time feedback data, enabling adaptive optimization of traffic routing based on current network conditions.
2Loss of time
If static MEC selection is used, then system complexity is reduced, but latency cannot be optimized for dynamic network conditions
Solution Approach 1:
The patent transforms the static MEC selection process into a dynamic system that automatically adapts to changing network conditions. The system continuously updates MEC platform status information, user equipment location, and network performance parameters in the centralized database, enabling real-time optimization of traffic routing to minimize latency based on current conditions rather than predetermined configurations.
Solution Approach 2:
The patent pre-establishes the centralized database structure and populates it with initial MEC platform status information, user equipment location data, and network performance parameters before actual traffic steering begins. This preliminary setup enables the system to immediately start making optimized routing decisions without requiring complex real-time data collection mechanisms to be built from scratch during operation.
3Adaptability or versatility
If third-party MEC platforms are integrated, then platform versatility is improved, but status monitoring capability deteriorates
Solution Approach 1:
The patent designs the centralized database with universal data structures and interfaces that can accommodate information from both provider-owned and third-party MEC platforms. The system uses standardized formats for storing MEC platform status information, user equipment location, and network performance parameters, enabling versatile integration of different platform types while maintaining consistent monitoring and management capabilities across all platforms.
Data Source
AI summary
A network device receives location information for a user equipment device (UE), an application identifier (ID), and a latency requirement associated with a data session involving the UE. The network device retrieves from a database, based on the UE's location information, the application ID, and the latency requirement, Multi-Access Edge Computing (MEC) selection weight values associated with multiple MEC platforms. The network device selects a MEC platform, from among the multiple MEC platforms, based on the retrieved MEC selection weight values, and causes the data session to be established between the selected MEC platform and the UE.