Micro Network Access Agents for Scalable LTE Traffic Analysis
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Solution Overview
Problem
Conventional communication network monitoring solutions struggle to provide real-time, scalable, and accurate analysis of performance data, especially in high-traffic environments like 4G/LTE networks, due to the need to capture and process all traffic packets and build extensive data records, leading to scalability issues and increased costs.
Innovation Solution
The implementation of micro network access agents at various access points within the service delivery chain, which distribute packet analysis and allow for real-time processing and tagging of packets, reducing the need for large processing units and enabling scalable and cost-effective monitoring by analyzing traffic in a distributed manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional hardware probes are installed at aggregate network nodes to detect service and traffic degradations, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent segments the network monitoring function by deploying lightweight software agents at distributed network access points rather than using centralized hardware probes. Each agent independently monitors local traffic, dividing the monitoring task across multiple simple components that collectively provide comprehensive coverage without requiring complex centralized hardware infrastructure
Solution Approach 2:
The patent replaces physical hardware probes with software-based monitoring agents that run on existing network infrastructure. This substitution eliminates the need for expensive specialized hardware while achieving the same monitoring objectives through software implementation on standard devices
2Device complexity
If random sampling techniques are used to monitor data packets, then device complexity is reduced, but measurement precision deteriorates as only a fraction of packets can be examined
Solution Approach 1:
The patent implements intelligent packet selection that examines more than random sampling would allow by prioritizing packets based on relevance criteria. The system selectively processes a targeted subset of packets that are most likely to reveal performance issues, achieving better detection accuracy than random sampling while maintaining lower complexity than full packet inspection
3Measurement precision
If all traffic packets are captured and processed to build extensive data records, then measurement precision is improved, but productivity decreases due to scalability issues with current network traffic volumes
Solution Approach 1:
The patent extracts only the essential performance metrics and characteristics from network traffic that are necessary for service quality assessment. Rather than capturing and processing all packet data, the system identifies and extracts key performance indicators, eliminating unnecessary data processing while maintaining accurate performance measurement capability
Solution Approach 2:
The system performs selective packet analysis by examining only the portion of traffic that contains performance-relevant information. This partial action approach processes sufficient data to achieve accurate performance measurement without the excessive processing burden of analyzing every packet, enabling real-time analysis at scale
4Measurement precision
If conventional monitoring systems are deployed to handle current network traffic volume, then measurement precision is maintained, but loss of time increases as systems cannot scale in real-time
Solution Approach 1:
The patent segments monitoring functions across distributed software agents that operate independently at network access points. This segmentation enables parallel processing of traffic data across multiple locations simultaneously, reducing analysis time and enabling real-time monitoring that scales with network growth without centralizing processing bottlenecks
Solution Approach 2:
The software agents continuously monitor and pre-process network traffic in real-time, maintaining up-to-date performance metrics before issues manifest. This preliminary continuous monitoring eliminates delays associated with batch processing or reactive analysis, enabling immediate detection and response to service degradations
Data Source
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AI summary
Techniques for providing visualization and analysis of performance data are disclosed. In one particular exemplary embodiment, the techniques may be realized as a system for providing visualization and analysis of performance data. The system may comprise one or more processors communicatively coupled to a mobile communications network. The one or more processors may be configured to provide a user interface at a mobile device for a user to view network performance data associated with the mobile communications network. The one or more processors may further be configured provide one or more user-selectable options to a user at a mobile device to view the network performance data. The one or more processors may also be configured to dynamically filter the network performance data based on the one or more user-selectable options. The one or more processors may further be configured to provide a visualization to be displayed at the mobile device based on the dynamically filtered network performance data, where the visualization presents one or more views that identify potential problems associated with the mobile communications network to allow the user to improve customer experience assurance.