Autonomous Vehicle Compute Pooling for Low-Latency Workload Allocation
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently aggregating and allocating their computing resources to process computation requests in real-time, leading to potential latency and inefficiencies when collaborating for computational workloads.
Innovation Solution
A system that utilizes machine learning to predict available computing resources across autonomous vehicles, dynamically allocates these resources to meet computational needs, and manages workload distribution, incorporating smart contracts for security and traffic management, while considering factors like weather and health conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles aggregate computing resources to process computation requests, then processing speed improves, but system complexity increases
Solution Approach 1:
The patent combines computing resources from multiple autonomous vehicles into a unified pool that can be dynamically allocated to computation requests. The system merges CPU cycles, memory, and storage resources across vehicle boundaries, enabling aggregated processing power while maintaining individual vehicle autonomy. This resolves the contradiction by achieving faster processing through resource consolidation without requiring complex permanent infrastructure.
Solution Approach 2:
The system implements dynamic resource allocation where computing resources are flexibly assigned based on real-time demands and vehicle availability. The allocation mechanism adjusts resource distribution dynamically rather than using fixed assignments, allowing the system to adapt to changing computational needs while simplifying resource management through automated orchestration.
2Productivity
If computing resources are allocated dynamically across autonomous vehicles, then resource utilization efficiency improves, but allocation complexity increases
Solution Approach 1:
The patent implements a self-service allocation mechanism where autonomous vehicles independently declare their available computing resources and the system automatically matches these resources to computation requests based on compatibility and availability. This eliminates the need for complex centralized management by enabling vehicles to self-manage their resource offerings and the system to autonomously perform optimization-based allocation.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor resource usage, vehicle availability, and computation request patterns to optimize allocation decisions. This feedback mechanism enables the system to learn from past allocations and improve resource utilization efficiency over time while maintaining relatively simple allocation rules through iterative refinement rather than complex predetermined logic.
3Productivity
If computation requests are processed by multiple autonomous vehicles, then processing capability increases, but coordination overhead increases
Solution Approach 1:
The patent segments computation requests into independent tasks that can be distributed across multiple autonomous vehicles. By dividing large computational workloads into smaller, manageable segments, the system enables parallel processing by multiple vehicles while reducing coordination overhead through task independence. Each vehicle processes its assigned segment autonomously without requiring continuous coordination with other vehicles.
Data Source
AI summary
A method, computer system, and a computer program product for allocating unused computing resources of a plurality autonomous vehicles is provided. The present invention may include receiving at least one computation request from at least one user. The present invention may include identifying the unused computing resources of the plurality of autonomous vehicles. The present invention may include predicting an amount of computational activities performable by the unused computing resources of the plurality of autonomous vehicles. The present invention may include allocating the unused computing resources of the plurality of autonomous vehicles to perform the predicted amount of computational activities, wherein the received at least one computation request is allocated at least a portion of the unused computing resources. The present invention may include distributing a processing load to at least one of the plurality of autonomous vehicles.