Distributed Sensor Network Consistency via Selective Model Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed sensor systems face challenges in managing communication bandwidth and computation load, particularly when a large number of sensors are used, and can fail if a central computer fails, while also struggling to ensure consistency of information across devices.
Innovation Solution
A system where devices communicate only when the information significantly improves the model, using an evaluation function that depends on the update information and current model, with devices organized in layers to reduce communication load and ensure consistency of state variables across the group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensors are coupled to a central computer that collects data from all sensors, then complete information can be obtained, but communication bandwidth and computation load become excessively high
Solution Approach 1:
The system divides sensors into multiple groups, with each group associated with a separate agent. Each agent maintains a local model for its group and selectively forwards information to other agents. This segmentation reduces the communication burden on any single central computer while preserving information completeness through distributed collaboration.
Solution Approach 2:
The patent extracts only the essential information from sensor data that is necessary for model updates. Agents evaluate sensor information and selectively forward only those data points that significantly improve the model, rather than transmitting all sensor data. This extraction principle reduces communication bandwidth while maintaining information quality.
2Ease of operation
If a central computer is used to process data from all sensors, then centralized control is achieved, but the system fails entirely when the central computer fails
Solution Approach 1:
The system segments the centralized control function into multiple distributed agents. Each agent independently processes sensor data from its associated group and maintains local models. This distribution eliminates the single point of failure inherent in centralized systems while preserving coordinated control through inter-agent communication.
Solution Approach 2:
Agents act as intermediaries between sensor groups and the overall system model. Each agent receives sensor data, processes it locally, and selectively forwards relevant information to other agents. This intermediary structure enables distributed control while maintaining system-wide consistency without requiring a central computer.
3Loss of energy
If agents forward information based on local model evaluation, then communication load is reduced, but sensor information valuable to one agent may not reach that agent if another agent decides the information is not valuable
Solution Approach 1:
The system implements feedback mechanisms where agents evaluate received information against their local models and selectively forward updates. The evaluation function determines whether information significantly improves the model, creating a feedback loop that reduces unnecessary communication while ensuring valuable information is propagated. This feedback-driven approach balances communication efficiency with information delivery reliability.
Data Source
Figure 1~2
Figure 3~5
Figure 4
AI summary
Distributed devices with sensors each maintain a copy of a common model. The devices each perform updates of state variables of the model in response to update information received from other devices in the group. Each device derives update information from its own sensor and decides whether or not to share the update information with the other devices. If it does not share the information the devices does not use the information itself either. Thus it is ensured that all devices keep their models consistent. Each device applies an evaluation function to the update information in the context of its current model to determine whether or not share the update information. The evaluation function may be adapted dependent on available communication bandwidth or information needs indicated by a device from a controlling layer that uses information from the model.