Decentralized Transport Software Update Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current software update systems for vehicles are inefficient and insecure, relying on centralized networks and lacking comprehensive testing across a large number of transports, which can lead to software updates being propagated without adequate validation.
Innovation Solution
A decentralized system using blockchain technology to validate and propagate software updates, where updates are tested across subsets of vehicles based on usage and environmental conditions, with smart contracts ensuring secure and efficient distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software updates are distributed through a centralized server using WAN, then software updates can be delivered to transports, but the system becomes inefficient and insecure
Solution Approach 1:
The patent segments the centralized update distribution system into multiple peer-to-peer nodes (transports) that collectively perform validation and propagation. Instead of a single centralized server, the system divides the workload across many transports, each validating updates locally and sharing validated updates with others, thereby improving both security through distributed validation and efficiency through localized peer-to-peer transmission.
Solution Approach 2:
The patent introduces blockchain technology as an intermediary layer that mediates between the centralized source and distributed transports. The blockchain serves as a trusted intermediary that records and validates update information, allowing transports to verify updates without direct centralized control, thus enhancing security while maintaining efficient distributed propagation.
2Reliability
If software updates are propagated without extensive testing, then update distribution is faster, but the reliability and security of updates deteriorates
Solution Approach 1:
The patent implements preliminary validation actions where a subset of transports tests and validates software updates before full propagation. This preliminary testing phase occurs in advance of widespread distribution, ensuring update reliability while the validation results are then quickly propagated to all transports, minimizing overall time loss.
Solution Approach 2:
The patent applies partial validation by having only a subset of transports perform extensive testing initially, rather than requiring all transports to validate before propagation. This partial action approach achieves sufficient validation reliability while significantly reducing the total time required, as the validated subset can then rapidly share proven updates with the remaining transports.
3Loss of information
If a centralized system collects information from millions of transports, then comprehensive tracking is achieved, but the system complexity and security risks increase
Solution Approach 1:
The patent segments the centralized information collection function into distributed peer-to-peer information sharing among transports. Each transport maintains and shares its own update validation information locally, eliminating the need for a complex centralized collection system while achieving comprehensive information gathering through the distributed network.
Solution Approach 2:
The patent enables transports to self-manage their own update information and validation data without requiring centralized collection. Each transport independently tracks and shares its validation results with peers, reducing system complexity while maintaining comprehensive information availability through self-service information management at the distributed level.
Data Source
AI summary
An example operation may include one or more of receiving a software update at a transport, performing a first validation of the software update in a first environment, wherein the first environment includes a least amount of potential interactions, and performing a further validation of the software update when the first validation is successful, in a further environment, wherein the further environment includes an amount of potential interactions greater than the first environment.