Network Subscriber Abstraction Module for Real-Time Data Correlation
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Solution Overview
Problem
Mobile operators face challenges in aggregating and correlating subscriber information across network elements to provide value-added services, as existing systems lack the ability to efficiently collect, analyze, and present network-wide data in real-time, leading to profitability issues due to increased data traffic and competition from over-the-top services.
Innovation Solution
A communication system with a network, service, and subscriber abstraction module that collects and abstracts data from various network elements, correlates it using similarity metrics, and presents it in a coherent format, enabling real-time analytics and service orchestration, allowing for the creation of new revenue streams and enhanced subscriber experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile operators add capacity and services to meet accelerating demands, then service coverage and subscriber satisfaction improve, but network costs and operational complexity increase
Solution Approach 1:
The patent segments the network information architecture into distinct functional components: network elements that generate data, an information server that aggregates and correlates data, and external entities that consume information. This segmentation allows each component to specialize in specific tasks, improving service coverage while managing complexity through modular design.
Solution Approach 2:
The information server acts as an intermediary between network elements and external entities. It collects information from distributed network elements, correlates the data using predefined criteria, and presents processed information to external entities. This intermediary layer shields external systems from the complexity of network element details while enabling comprehensive service access.
2Productivity
If operators invest in network assets to launch new services, then revenue opportunities increase, but infrastructure costs and deployment time increase
Solution Approach 1:
The system performs preliminary actions by pre-defining correlation criteria and information structures in the information server before external entities need the data. Network elements continuously populate the information server with correlated data using predefined rules, so when external entities request information, it is immediately available. This eliminates deployment delays and enables rapid service launch.
Solution Approach 2:
The information server provides universal functionality by serving multiple external entities with different information needs through a single correlated data repository. Rather than building separate information systems for each service, the universal information server supports diverse revenue-generating services including location-based services, subscriber analytics, and network optimization, reducing both cost and deployment time.
3Loss of information
If operators aggregate information from distributed network elements, then service intelligence and revenue opportunities improve, but data processing complexity and storage requirements increase
Solution Approach 1:
The patent applies local quality by allowing different network elements to contribute different types of information based on their local capabilities and characteristics. Each network element contributes the information it is best suited to generate, and the information server correlates these diverse inputs using location-specific criteria. This approach enables comprehensive information aggregation while managing complexity through localized data contribution.
4Speed
If operators provide real-time network-wide data access, then service velocity and subscriber experience improve, but network load and processing requirements increase
Solution Approach 1:
The information server performs preliminary correlation and processing of network data before external entities request it. Network elements continuously populate the server with pre-correlated information using predefined criteria, so real-time data access is achieved by retrieving already-processed information rather than performing complex queries across distributed network elements at the moment of request. This dramatically reduces processing load while maintaining high service velocity.
Data Source
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AI summary
A data control task (DCT) method is provided and includes receiving (1102) data from a network element, determining (1104) a candidate data processing task (DPT) for the received data based upon a first similarity metric between the received data and data currently associated with the candidate data processing task, and sending (1106) the received data to the candidate data processing task. The candidate DPT may determine (1108) whether the received data is suitable for the candidate data processing task based upon a second similarity metric. Moreover, a message indicative of whether the candidate data processing task has accepted the received data may be sent based upon whether the received data is suitable for the data processing task. Similarity information for the candidate DPT may be updated (1110) based upon whether the candidate data processing task has accepted the received data. In accordance with one or more embodiments, network, service, and subscriber abstraction module collects information or data from various network elements within communication system and abstracts the data by examining one or more correlating factors between collected data, such as an IP address or mobile subscriber identifier, to combine the correlating data together based upon the correlating factors into a consistent store of data which can be later accessed and utilized. Data is abstracted out from different sources and organized into a coherent format that can be translated into one or more external protocols, such as HTTP, XMPP, or DIAMETER.