Inference Difference Transmission for Bandwidth Reduction
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Solution Overview
Problem
Current data collection systems face challenges in efficiently managing data transmission, leading to increased network bandwidth consumption and energy usage, particularly in distributed environments where transmitting large quantities of data can overwhelm communication systems and devices.
Innovation Solution
The implementation of a system that uses twin inference models (TIM) and aggregator inference models (AIM) to predict data, where the data aggregator generates an inference difference and transmits it to the data collector, allowing the collector to reconstruct the AIM inference without transmitting the AIM itself, thereby reducing data transmission and conserving bandwidth and energy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is transmitted from data collector to data aggregator in distributed environment, then measurement accuracy is maintained, but network bandwidth consumption increases and energy usage increases
Solution Approach 1:
The patent extracts only the essential information needed for accurate measurement reconstruction. Instead of transmitting complete raw data from data collectors to aggregators, the system transmits compressed representations or inferred data that contain sufficient information to maintain measurement accuracy while significantly reducing transmission volume and energy consumption.
Solution Approach 2:
The patent creates and transmits copies of inferred data or compressed data representations instead of original raw measurements. Data collectors generate local inferences or compressed versions of measurements, which are then transmitted to aggregators. These copies suffice for maintaining measurement accuracy while reducing the energy cost of transmission.
2Measurement precision
If data is transmitted from data collector to data aggregator in distributed environment, then measurement accuracy is maintained, but network bandwidth consumption increases
Solution Approach 1:
The system extracts only the critical components of measurement data that are necessary for maintaining accuracy. By identifying and transmitting only these essential elements rather than complete datasets, the patent reduces the quantity of data transmitted over the network while preserving measurement precision at the aggregator.
Solution Approach 2:
The patent transforms measurement data from its original high-volume format into a compressed or inferred representation with different parameters. This parameter transformation reduces data size suitable for transmission while maintaining the information necessary for accurate measurements, thereby reducing network bandwidth consumption.
3Quantity of substance
If twin inference models and aggregator inference models are used to predict data, then data transmission is minimized, but device complexity increases
Solution Approach 1:
The patent implements preliminary action by deploying inference models at data collectors before data transmission occurs. These models pre-process and compress measurements locally, generating inferred data that can be transmitted with minimal bandwidth. The aggregator receives pre-processed data that requires less computational resources to reconstruct accurate measurements.
Solution Approach 2:
The inference models act as intermediaries between raw measurements and transmitted data. Rather than directly transmitting raw measurements, the patent introduces inference models that transform measurements into compressed representations. This intermediary processing layer reduces transmission requirements while maintaining measurement accuracy.
Data Source
AI summary
Methods and systems for managing data collection are disclosed. To manage data collection, a system may include a data aggregator and a data collector. The data aggregator may utilize complex inference models to predict the future operation of the data collector, while the data collector may host simpler inference models. The data collector may access inferences from the complex models by obtaining a difference between complex and simple inferences from the data aggregator and locally reconstructing the complex differences. To reduce data transmission, the data collector may transmit a data difference (e.g., a reduced-size representation of a measurement) to the data aggregator using the reconstructed complex inferences. The data aggregator may reconstruct data from the data collectors using the data difference from the data collector and inferences from the complex inference model.