Vehicle Service Discovery Learning With Dormant-Mode Persistence
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Solution Overview
Problem
Existing vehicle control module systems do not optimally establish relationships between control modules and their services, leading to inefficiencies in service discovery.
Innovation Solution
A method and system for service discovery learning among vehicle control modules, where a trigger initiates a dormant mode learning process to identify services and IP addresses, which are stored in non-volatile memory, and are used to efficiently request and offer services when needed, waking only necessary modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service discovery learning is performed continuously among all control modules, then service discovery efficiency is improved, but energy consumption and system complexity increase
Solution Approach 1:
The system performs service discovery learning in advance during dormant mode before services are actually required. Control modules learn and store service relationships and IP addresses in non-volatile memory during idle periods, so that when services are needed, the modules can quickly retrieve pre-learned information without performing extensive discovery operations, thereby improving service discovery efficiency while minimizing energy consumption during active operation.
Solution Approach 2:
Service discovery learning is performed periodically during dormant modes rather than continuously. The system alternates between learning phases (during dormant mode) and operational phases (when services are required), allowing control modules to update their service knowledge base intermittently. This periodic approach maintains service discovery efficiency while significantly reducing overall energy consumption compared to continuous learning.
2Reliability
If all control modules remain active to provide services, then service availability is improved, but energy consumption and device complexity increase
Solution Approach 1:
Control modules perform service discovery learning in advance during dormant mode, storing service relationships, IP addresses, and service offerings in non-volatile memory before services are actually required. This preliminary learning ensures that when services are needed, modules can quickly retrieve pre-learned information and establish connections efficiently, maintaining service availability without requiring all modules to remain continuously active.
Solution Approach 2:
The system creates and stores copies of service discovery information (service relationships, IP addresses, service offerings) in non-volatile memory during dormant mode. These stored copies allow control modules to quickly retrieve service information without needing to query other modules in real-time, reducing system complexity and energy consumption while maintaining service availability.
3Device complexity
If service discovery learning is performed after services are required, then system simplicity is maintained, but service discovery time and productivity decrease
Solution Approach 1:
The system performs service discovery learning in advance during dormant mode before services are actually required. Control modules learn service relationships, IP addresses, and service offerings, storing this information in non-volatile memory. When services are needed, modules can quickly retrieve pre-learned information from storage rather than performing extensive discovery operations in real-time, significantly reducing service discovery time while maintaining system simplicity.
4Measurement precision
If control modules perform extensive service discovery operations, then service interaction accuracy is improved, but processing time and productivity decrease
Solution Approach 1:
Control modules perform service discovery learning in advance during dormant mode, accurately learning and storing service relationships, IP addresses, and service offerings in non-volatile memory. When services are actually required, modules can quickly retrieve this pre-learned accurate information from storage without performing extensive discovery operations in real-time, thereby maintaining high service interaction accuracy while minimizing processing time.
Data Source
AI summary
Methods and systems are provided that include a transceiver and one or more processors. The transceiver is configured to at least facilitate receiving an indication of a trigger for service discovery learning for a plurality of control modules for a vehicle. The one or more processors are coupled to the transceiver, and are configured to at least facilitate performing service discovery learning among the plurality of control modules as to services to be offered or required by each of the control modules, storing information as to the services in a non-volatile memory, and after the indication of the trigger and before the services are actually required; and subsequently, when an event occurs in which the services are actually required, requesting and offering the services via the plurality of control modules based on the service discovery learning.