Service Area Reliability Estimation in Edge Networks
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Solution Overview
Problem
Current communication systems face challenges in estimating the reliability and latency of direct communication between mobile clients in dynamic networks, such as those involving vehicles, where continuous data exchange is not scalable and fails to provide reliable predictions, especially in heterogeneous networks with changing communication channels.
Innovation Solution
A system and method that utilize Mobile or Multiaccess Edge Computing (MEC) to process and distribute service areas, allowing clients to estimate overall communication reliability and latency by collecting and processing reliability and latency information from base stations and GeoServices, enabling precise predictions even when communication partners are in different service areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous data exchange between sender and receiver is used to estimate connection quality, then measurement precision is improved, but device complexity and overhead increase significantly
Solution Approach 1:
The patent extracts the measurement function from the communication protocol itself and places it in the application layer. Applications perform their own measurements using available data (signal strength, position information, historical data) without requiring continuous data exchange through the communication protocol, thereby reducing overhead while maintaining measurement capability
Solution Approach 2:
The patent introduces position information and service area data as intermediary elements that enable connection quality estimation without direct continuous measurement exchange. By using geographic location and service area coverage data, the system can predict connection quality indirectly, avoiding the need for continuous direct measurement communication
2Reliability
If continuous monitoring of communication connections is implemented, then reliability of quality assessment is improved, but loss of time and energy increase due to constant data exchange
Solution Approach 1:
Instead of continuous monitoring, the patent employs periodic updates of position information and service area data. The system refreshes connection quality estimates at intervals based on movement detection or significant environmental changes, maintaining reliability while reducing the time and energy consumption associated with constant monitoring
Solution Approach 2:
The system uses self-service mechanisms where devices autonomously update their position information and retrieve service area data from local databases or cached information. This eliminates the need for continuous request-response cycles with network servers, reducing time loss while maintaining up-to-date assessment capability
3Productivity
If position-based methods with service area distribution are used, then productivity of quality estimation is improved, but measurement precision may decrease in heterogeneous networks
Solution Approach 1:
The patent implements local quality assessment by dividing the network into service areas with heterogeneous parameters. Each service area maintains its own quality characteristics (signal strength, latency, reliability), and the system selects the appropriate service area model based on the device's location. This allows fast estimation using local pre-characterized data while maintaining precision by accounting for local network conditions
Solution Approach 2:
The system dynamically changes estimation parameters based on the detected service area. When a device moves between service areas, the system switches between different quality models and parameter sets appropriate for each area. This enables rapid adaptation to changing network conditions while maintaining accuracy through context-appropriate parameter selection
4Ease of operation
If service area information is distributed to all clients, then ease of operation is improved, but loss of information increases due to potential data inconsistency
Solution Approach 1:
The system performs preliminary actions by pre-characterizing service areas with quality parameters and distributing this static or slowly-changing information to clients. This advance preparation enables fast local estimation without requiring real-time data synchronization, maintaining data consistency while providing widespread access to quality information
Solution Approach 2:
Service area information is updated periodically rather than in real-time. The system refreshes service area databases at intervals, allowing all clients to operate with consistent data for extended periods. This periodic synchronization maintains data consistency across the network while still providing timely quality estimation for applications
Data Source
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AI summary
A first user unit (100) is provided. The first user unit (100) includes a storage unit (110) configured to store at least initial reliability information about the initial reliability of a first communication link for a service area in which the first user unit (100) is located, or at least initial latency information about the initial latency of the first communication link for the service area in which the first user unit (100) is located.Furthermore, the first user unit (100) comprises a receiving module (120) configured to receive a message from a second user unit, wherein the message includes at least a second reliability information about a second reliability of a second communication link for a service area in which the second user unit is located, or wherein the message includes at least a second latency information about a second latency of the second communication link for the service area in which the second user unit is located.Furthermore, the first user unit (100) comprises a processor unit (130) configured to determine the overall reliability of the entire communication link between the first user unit (100) and the second user unit, depending on the first reliability information and the second reliability information, or to determine the overall latency of the entire communication link between the first user unit (100) and the second user unit, depending on the first latency information and the second latency information. The service area in which the second user unit is located is either identical to the service area in which the first user unit (100) is located, or it is different from the service area in which the first user unit (100) is located.