Edge Cloud Computer Resource Allocation for Vehicle Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cloud computing systems face latency issues due to long signal propagation paths, making it challenging to execute time-critical computation algorithms for self-driving transportation vehicles, which require decentralized computing power for efficient operation.
Innovation Solution
A method for operating an edge cloud computer that involves detecting resource information, transmitting it to terminals, and providing computing capacity based on this information, enabling near-instantaneous and efficient provision of decentralized computing power, particularly for transportation vehicles, through push-based communication and periodic updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If centralized cloud computing is used, then computing capacity is available, but latency increases due to long signal propagation paths
Solution Approach 1:
The patent segments the centralized cloud computing system into decentralized edge cloud computers distributed at multiple locations. Each edge cloud computer independently provides computing capacity to terminals in its vicinity, eliminating the need for all computations to route through a central cloud. This segmentation reduces signal propagation distance and latency while maintaining distributed computing capacity.
Solution Approach 2:
The patent implements local quality by providing computing services at localized edge cloud computers near terminals rather than through a remote centralized cloud. Each edge cloud computer serves the specific local needs of terminals in its service area, reducing the distance data must travel and minimizing latency for time-critical applications.
2Power
If multiple edge cloud computers are available, then computing capacity is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service through automated resource allocation mechanisms. Edge cloud computers automatically detect their own resource status and transmit this information to terminals. Terminals autonomously select appropriate edge cloud computers based on transmitted resource information without requiring manual configuration or complex centralized management, thereby reducing operational complexity despite having multiple available computers.
Solution Approach 2:
The patent employs feedback mechanisms where edge cloud computers continuously transmit their resource information status to terminals. This feedback loop enables terminals to make informed decisions about which edge cloud computer to select based on real-time resource availability, simplifying the selection process despite the presence of multiple computers.
3Productivity
If resource information is transmitted frequently, then computing power distribution is optimized, but energy consumption increases
Solution Approach 1:
The patent implements periodic action by having edge cloud computers transmit resource information at predetermined time intervals rather than continuously. This periodic transmission approach optimizes computing power distribution by ensuring terminals have up-to-date information while reducing energy consumption compared to continuous broadcasting, as transmissions occur only at scheduled intervals.
Data Source
AI summary
A method for operating an edge cloud computer when providing a computing power to at least one terminal, in particular, a transportation vehicle including detecting resource information at the edge cloud computer, transmitting resource information to the at least one terminal, and providing at least one portion of a computing capacity of the edge cloud computer to the at least one terminal depending on the resource information.