Vehicle Compute Allocation Using Availability Prediction and 6G Slices
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Solution Overview
Problem
Existing systems struggle to efficiently utilize the processing capacity of vehicles when they are idle or parked, as they lack the ability to predict and ensure vehicle availability for compute tasks, leading to inefficiencies and task failures.
Innovation Solution
A cloud service management server leverages vehicle information status and historical data, combined with 6G network slice allocation, to predict and dynamically allocate compute tasks to vehicles, ensuring availability and reliability through confidence values and network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a cloud computing system individually queries each vehicle to check availability for compute tasks, then the system can assign tasks to available vehicles, but the vehicle may become unavailable during the task execution leading to task failure
Solution Approach 1:
The system performs preliminary actions by querying vehicle availability and obtaining confidence values before assigning compute tasks. The cloud service management server evaluates multiple factors including current status, historical data, and location information in advance to predict whether a vehicle will remain available throughout the entire task duration, thus preventing task failures due to mid-execution unavailability.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring vehicle status and using historical data to update availability predictions. The confidence value serves as feedback that indicates the reliability of assigning a compute task to a particular vehicle, allowing the system to make informed decisions based on past performance and current conditions.
2Reliability
If the system uses historical information and confidence values to predict vehicle availability, then task reliability improves, but the system complexity increases
Solution Approach 1:
The cloud service management server performs multiple functions within a single system: it manages compute task assignments, collects and analyzes historical vehicle data, evaluates current vehicle status, predicts future availability, and generates confidence values. This multi-functional approach consolidates complexity into a centralized management system rather than distributing it across multiple components.
Solution Approach 2:
The confidence value acts as an intermediary metric that simplifies the complex availability prediction process. Instead of directly managing multiple data sources and prediction algorithms, the system uses the confidence value as an intermediate representation that encapsulates the result of complex analyses, making the decision-making process more manageable.
3Speed
If the system leverages 6G network connectivity for vehicle communication, then data transmission speed and reliability improve, but network infrastructure requirements increase
Solution Approach 1:
The system dynamically adapts to available network conditions by leveraging 6G connectivity when available. The cloud service management server can adjust its communication strategies based on real-time network quality, using the high-speed 6G network for time-critical operations while potentially falling back to other communication methods when 6G is unavailable, thus optimizing performance without requiring permanent 6G infrastructure at all locations.
Data Source
AI summary
Aspects of the present application leverage vehicle information status and historical information in conjunction with 6G network slice allocation to efficiently utilize unused processing capacity of vehicles for dynamically allocating compute tasks. A cloud service management server may determine multiple vehicles' compute availability taking into account vehicles' compute capacity, vehicles' location and location history, and schedules to predict and utilize vehicles' unused processing capacity. Historical information may be utilized by the cloud service management server to predict availability of the vehicle to increase confidence for the compute task. Implementing the cloud service management server with 6G network connectivity provides for a significant upgrade in network reliability having data speeds exceeding 1 Tbps and ultra-low latency of less than 1 microsecond.