Wireless Network Data Collection Using Dynamic Backend Allocation
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Solution Overview
Problem
Conventional wireless communication networks face inefficiencies in processing large volumes of data due to the need for significant processing resources at each location, leading to underutilization and high upfront costs for increased capacity, especially when using centralized or shared processing systems that require expensive and inflexible communication links for data transport.
Innovation Solution
A method and system for enabling near real-time data analysis by extracting a subset of data from distributed components and forwarding it to dynamically allocated backend processing resources, reducing the amount of data transported and the required communication link speed and size, and utilizing cloud or shared processing resources for efficient data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If data is processed locally at each distributed site, then processing autonomy is improved, but processing resource utilization deteriorates due to underutilization and high upfront costs
Solution Approach 1:
The system segments processing into two layers: distributed components perform local data collection and filtering (autonomous segment), while backend processing resources handle analytical processing (centralized segment). This segmentation allows each component to operate autonomously within its scope while maintaining overall system efficiency.
Solution Approach 2:
The invention extracts only the necessary subset of data from distributed components before forwarding to backend resources. This extraction principle reduces the data volume requiring centralized processing, improving resource utilization while maintaining processing autonomy at the distributed level.
2Productivity
If processing capacity is increased at a particular location, then processing capability is improved, but hardware costs increase significantly due to replacement or additional sets of processing cards, racks or storage
Solution Approach 1:
The system merges processing capabilities by combining distributed data collection functions with centralized backend processing resources. This consolidation allows processing capacity to be increased at the backend level without requiring proportional hardware increases at each distributed location, reducing overall hardware costs.
Solution Approach 2:
Backend processing resources are designed to handle multiple functions and serve multiple distributed components. This multi-functionality allows a single backend resource pool to support the entire network, eliminating the need for dedicated processing hardware at each location and reducing hardware costs.
3Loss of information
If all raw communication session data is forwarded to backend processing resources, then data completeness is improved, but data transport volume increases significantly
Solution Approach 1:
Distributed components extract and forward only the essential subset of data required for analytical processing to the backend. This selective extraction maintains data completeness for analysis purposes while dramatically reducing the volume of data that needs to be transported across the network.
Solution Approach 2:
Different parts of the data processing system perform different functions: distributed components perform local data filtering and extraction, while backend resources perform analytical processing. This local quality differentiation ensures that only necessary data is transported, balancing data completeness with transport efficiency.
Data Source
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AI summary
A method and apparatus for enabling near real time analysis of data for a wireless communication network using dynamic allocation backend processing resources. The method comprises, at each of a plurality of distributed components of a data processing system (e.g. MSCs), receiving data from at least one network element of the cellular communication network (e.g. RNCs), parsing the received data to extract a subset of the received data, and forwarding the extracted subset of data to the dynamic allocation backend processing resources for analytical processing of the extracted subset of data for the wireless communication network.