Vehicle Virtual Machine Control for Predictive Resource Offloading
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Solution Overview
Problem
The increasing computational demands of autonomous driving systems and multiple passenger applications in vehicles require more resources than typically available, leading to potential operational slowdowns or malfunctions due to resource shortages, necessitating a method to predict and manage resource usage effectively.
Innovation Solution
A virtual machine (VM) is generated in a server based on the operating apparatus's resource usage, allowing for predictive monitoring and control of computation execution, ensuring reliable operation by allocating resources efficiently and preventing malfunctions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computational resources are increased to support autonomous driving and multiple passenger applications, then system functionality and service quality are improved, but device complexity and resource management difficulty increase
Solution Approach 1:
A virtual machine is introduced as an intermediary layer between the physical operating apparatus and the applications. The VM monitors resource usage, predicts future resource needs, and manages computation offloading to external servers, thereby simplifying resource management while supporting diverse functions including autonomous driving and passenger applications
Solution Approach 2:
The virtual machine performs preliminary actions by monitoring current resource usage and predicting future resource needs before actual resource shortages occur. This predictive capability allows the system to proactively manage resources, offload computations in advance, and prevent malfunctions before they happen
2Device complexity
If computational resources are limited to maintain simple device architecture, then device complexity is reduced, but system reliability and operational stability deteriorate due to resource shortages
Solution Approach 1:
The virtual machine acts as a mediator that enables the operating apparatus to maintain simple architecture while achieving high reliability. It provides predictive monitoring and computation offloading capabilities that prevent resource-related malfunctions without requiring complex hardware or software modifications to the core system
Solution Approach 2:
The system replaces physical resource expansion with virtualized resource management and cloud-based computation offloading. Instead of adding more physical computational resources to the vehicle, the VM enables dynamic allocation and offloading of computational tasks to external servers, maintaining architectural simplicity while ensuring operational stability
3Productivity
If more computational resources are allocated for autonomous driving functions, then service quality and system performance are improved, but resource availability for other applications decreases
Solution Approach 1:
The virtual machine implements dynamic resource management by continuously monitoring resource usage patterns and adaptively adjusting resource allocation. It can dynamically offload computations to external servers when resources are scarce and bring them back when resources are available, enabling the system to maintain high performance while optimizing resource utilization across multiple applications
Solution Approach 2:
The virtual machine provides universal resource management capabilities that serve multiple functions: monitoring resource usage, predicting future needs, managing computation offloading, and coordinating resources across autonomous driving and passenger applications. This single multi-functional component optimizes resource distribution throughout the system
Data Source
AI summary
One or more of an autonomous vehicle, a user terminal, and a server of the present disclosure may be linked or converged with an artificial intelligence (AI) module, an unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, virtual reality (VR), a 5G service-related device, and the like. There is provided a method for providing information in a server according to an embodiment of the present disclosure includes receiving a request message including information related to generation of a virtual machine (VM) from an operating apparatus, generating a VM corresponding to the operating apparatus based on the request message, receiving information acquired at the operating apparatus, performing computation corresponding to the acquired information by use of the VM, and transmitting information related to a result of the computation to the operating apparatus.