Adaptive Bandwidth Reduction for IoT Gateway Devices
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Solution Overview
Problem
IoT devices at the edge of networks often generate large amounts of data, leading to bandwidth inefficiencies as they typically discard data to conserve bandwidth, despite having limited processing power and available bandwidth.
Innovation Solution
An IoT gateway device analyzes sensor data trends and determines a mathematical model to represent the data, adjusting the number and precision of coefficients based on stability or approaching thresholds, then communicates these parameters to a cloud compute device to optimize bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is transmitted to cloud-based servers, then data monitoring capability is improved, but bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential information from sensor data by fitting mathematical models to represent the data trends. Instead of transmitting raw sensor data, the system transmits model parameters (coefficients) that capture the essential behavior, thereby reducing bandwidth consumption while maintaining monitoring capability.
Solution Approach 2:
The system dynamically changes the parameters of the mathematical model (number of coefficients, model complexity) based on the characteristics of the sensor data. When data is stable, simpler models with fewer parameters are used; when data shows significant trends or approaches thresholds, more complex models with additional parameters are employed, optimizing the balance between monitoring accuracy and bandwidth usage.
2Loss of energy
If data is discarded to limit bandwidth usage, then bandwidth consumption is reduced, but information loss increases
Solution Approach 1:
Instead of transmitting the complete raw data, the system creates a simplified mathematical representation (copy) of the data that preserves the essential information. The mathematical model acts as a compressed copy that can be transmitted with minimal bandwidth while still enabling accurate reconstruction and analysis of the original data trends at the cloud server.
3Measurement precision
If mathematical models with more coefficients are used, then data representation accuracy is improved, but processing complexity increases
Solution Approach 1:
The system dynamically adjusts the complexity of the mathematical model based on the actual characteristics of the sensor data. The number of coefficients and the type of model (linear, polynomial, exponential) are selected adaptively according to the data's trend behavior, ensuring that the model is as simple as possible while still accurately representing the data, thus minimizing processing complexity while maintaining necessary accuracy.
Data Source
AI summary
Technologies for adaptive bandwidth reduction for an Internet of Things (IoT) gateway device are disclosed. The IoT gateway device receives data from one or more sensors, and determines a mathematical model to represent the sensor data. Certain aspects of the mathematical model used, such as the quantity of coefficients and the precision of the coefficients are determined based on the sensor data. For example, if the sensor data is within a normal range, a relatively small number of coefficients might be used, but if the sensor data is past or near an alert threshold, a larger number of coefficients might be used, which allows for the behavior of the sensor data to be better represented.