Dynamic Parameter Update Negotiation for Communication Bandwidth Reduction
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Solution Overview
Problem
Existing machine systems, such as those in construction and mining, face inefficiencies in communicating parameter updates, as they often transmit unnecessary data periodically, leading to high communication bandwidth and processing time usage, especially for parameters that change infrequently.
Innovation Solution
A system and method for dynamically negotiating and communicating parameter data, using machine learning to categorize parameters as periodic or non-periodic, allowing updates only when changes occur, thereby reducing unnecessary transmissions and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If parameters are communicated periodically, then the ECM receives updated parameter values reliably, but communication bandwidth and processing time are wasted for parameters that change infrequently
Solution Approach 1:
The system dynamically adjusts the communication strategy for each parameter based on its volatility characteristics. Parameters are classified as volatile (change frequently) or non-volatile (change infrequently), and different communication frequencies are applied accordingly. This dynamic adaptation resolves the contradiction by maintaining reliable updates for volatile parameters while reducing bandwidth consumption for non-volatile parameters.
Solution Approach 2:
The system changes the communication parameter (update frequency) based on the nature of each parameter. By detecting and categorizing parameters based on their change behavior, the system modifies the communication protocol parameters individually for each parameter type, allowing periodic updates for volatile parameters and event-driven updates for non-volatile parameters.
2Reliability
If parameters are communicated periodically, then the ECM ensures timely parameter updates, but processing time on the ECM increases due to handling unnecessary updates
Solution Approach 1:
The system dynamically selects the update mechanism for each parameter based on its volatility. For volatile parameters, periodic updates maintain timeliness; for non-volatile parameters, event-driven updates eliminate unnecessary processing. This dynamic approach resolves the contradiction by ensuring timely updates only when needed while minimizing processing time for parameters that rarely change.
Solution Approach 2:
The system segments parameters into distinct categories (volatile and non-volatile) and applies different update strategies to each segment. This segmentation allows the ECM to process updates efficiently by handling different parameter types differently, reducing overall processing time while maintaining timeliness for critical parameters.
3Ease of manufacture
If all parameters are updated using the same frequency, then the system is simple to implement, but it cannot optimize for parameters that change infrequently
Solution Approach 1:
The system applies different update frequencies and communication strategies to different parameters based on their individual characteristics. Instead of a uniform approach, each parameter receives customized treatment according to its volatility, allowing the system to optimize communication efficiency for each parameter while maintaining overall system manageability.
Solution Approach 2:
The system introduces dynamic parameter classification and adaptive update mechanisms that learn from historical data to determine parameter volatility. This dynamic approach enables the system to optimize communication efficiency for each parameter individually while remaining practical to implement through automated classification and configuration.
Data Source
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AI summary
A client device (102) may identify a first parameter that is to be updated periodically and a second parameter that is to be updated based on a state change. The client may transmit, via a negotiation session, a request to the server device (104). The request indicates that the server device (104) is to periodically provide information indicating a current value of the first parameter and is to provide information indicating an updated value of the second parameter when a state of the second parameter changes. The client device (102) may periodically receive, from the server device (104) and via a second communication protocol, a first datagram including the current value of the first parameter and may receive a second datagram including the updated value of the second parameter based on the server device (104) determining that the current state of the second parameter has changed.