Vehicle Computing Resource Allocation with Dedicated and Shared Units
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Solution Overview
Problem
Existing computing resource allocation methods in central computing platforms for vehicles result in insufficient resources in some service domains, leading to reduced service processing capability and instability due to resource preemption among domains.
Innovation Solution
Implementing a method that allocates 'a' dedicated computing units and 'b' shared computing units, where 'a' and 'b' are positive integers, to ensure service domains receive the necessary resources by dynamically adjusting shared computing units based on user usage habits and prior information, thereby ensuring stable service processing capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing resources are pre-divided and allocated to different service domains, then resource allocation is simple and stable, but computing resources may be insufficient in some service domains during usage, reducing service processing capability
Solution Approach 1:
The computing resources are segmented into two distinct types: dedicated computing units and shared computing units. Dedicated units are pre-allocated to specific service domains to ensure stable baseline resources, while shared units form a common pool that can be dynamically allocated. This segmentation resolves the contradiction by maintaining simple pre-allocation for stability while enabling flexible dynamic allocation from the shared pool to enhance service processing capability when needed.
Solution Approach 2:
The system implements dynamic resource allocation by allowing the shared computing units to be flexibly assigned to different service domains based on real-time resource usage patterns and service requirements. The allocation is adjusted dynamically during vehicle usage rather than being fixed, enabling the system to adapt to changing demands and ensure sufficient computing resources for high-priority services without requiring complete reallocation of all resources.
2Reliability
If dedicated computing units are allocated to service domains, then service domain stability is ensured, but resource preemption occurs when computing requirements are large, reducing overall resource utilization efficiency
Solution Approach 1:
By dividing computing resources into dedicated and shared segments, the system ensures that dedicated units provide stable, guaranteed resources for each service domain, maintaining reliability. Meanwhile, the shared segment provides flexible, adaptable resources that can be allocated to any service domain experiencing high computing requirements, preventing resource preemption issues while maintaining service stability.
Solution Approach 2:
The shared computing units act as an intermediary resource pool between the dedicated computing units and the service domains. When a service domain experiences increased computing requirements, the shared units can be allocated to that domain without requiring preemption of dedicated units from other domains, thus maintaining both service domain stability and resource flexibility simultaneously.
3Adaptability or versatility
If shared computing units are allocated dynamically based on usage data, then resource allocation flexibility is improved, but system complexity increases due to monitoring and adjustment mechanisms
Solution Approach 1:
The shared computing units serve multiple service domains universally, rather than being dedicated to a single domain. This multi-functionality allows the same pool of resources to be flexibly allocated to different domains based on real-time needs, improving adaptability without requiring separate monitoring and control systems for each domain, thus limiting the increase in system complexity.
Solution Approach 2:
The system uses usage data from historical periods as feedback to inform dynamic allocation decisions. By monitoring resource usage patterns and adjusting shared unit allocation based on this feedback, the system achieves flexible, adaptive resource allocation. The feedback mechanism is simplified by using aggregated usage data rather than complex real-time monitoring of each individual service domain's instantaneous needs.
Data Source
AI summary
A method for adjusting a computing resource comprising A dedicated computing units and B shared computing units, where the A dedicated computing units are allocated to m service domains. The method includes obtaining first usage data of each of k service domains; determining, based on the first usage data, a first quantity of computing units required by a target service domain in the k service domains, where the k service domains are one or more of the m service domains; determining, in the B shared computing units based on the first quantity and a second quantity of dedicated computing units in the A dedicated computing units and that have been allocated to the target service domain, a third quantity of shared computing units that needs to be allocated to the target service domain; and allocating the third quantity of shared computing units to the target service domain.