Headend System Data Gap Reconciliation Across Networks
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Solution Overview
Problem
In networks with multiple endpoints using different communication technologies, data may be missed due to hardware, software, or network issues, and existing systems lack adaptability to collect missing data across various technologies without overloading or impairing the network.
Innovation Solution
A headend system automatically detects missing data and adjusts communication parameters like speed, batch size, and retry processes to collect missing data, supporting technologies such as RF, PLC, and cellular, through gap detection, reconciliation, and retry processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a uniform data collection process is used across all endpoints regardless of communication technology, then the process is simple to implement, but it may overload or impair networks using different communication technologies
Solution Approach 1:
The system dynamically adjusts data collection parameters (batch size, speed, retry processes) based on the communication technology being used. The headend system modifies its behavior adaptively rather than using a fixed uniform process, allowing optimal performance across different network types while maintaining a single standardized interface.
Solution Approach 2:
The patent changes operational parameters such as batch size, communication speed, and retry attempts based on the detected communication technology. Each technology type (RF, PLC, cellular) receives customized parameter settings that optimize its specific performance characteristics, resolving the contradiction between process simplicity and network reliability.
2Loss of information
If the headend system collects missing data from all endpoints simultaneously, then data completeness is improved, but network overload occurs
Solution Approach 1:
The system segments the data collection process by dividing endpoints into groups based on their communication technology type. Instead of collecting data from all endpoints simultaneously, it processes each technology group separately with customized batch sizes and timing, ensuring data completeness while distributing network load appropriately.
Solution Approach 2:
The headend system applies partial action by collecting data in staged batches rather than all at once. It uses technology-specific batch sizes that are calibrated to match each network type's capacity, collecting enough data to ensure completeness while avoiding excessive network load through controlled, incremental retrieval.
3Loss of time
If the headend system uses fast communication speed to collect missing data, then data collection time is reduced, but data loss or corruption may occur
Solution Approach 1:
The system applies local quality by tailoring communication speed to each specific endpoint's technology type and conditions. Rather than using a single high speed for all endpoints, it optimizes speed locally for each technology (RF, PLC, cellular) based on their specific capabilities and error rates, reducing collection time while maintaining data integrity through appropriately matched speeds.
Data Source
AI summary
Systems and methods automatically detect missing data and attempt to collect the missing data. The missing data may be related to a data reading or may be related to an event. The missing data is detected by comparing a communication received from an endpoint with previously received communications from the endpoint. The communication technology used by the endpoint may be considered in determining how to detect missing data and how to request the missing data from the endpoint. A single headend system may communicate with endpoints that use different communication technologies by adjusting the speed, batch size and the retry process used.