Autonomous Vehicle Fleet Routing for Aggregated Edge Computing
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Solution Overview
Problem
Autonomous vehicles often face insufficient edge computing resources while traveling, leading to unsatisfied network provider service level agreements (SLAs) due to limited edge data computing resources along their routes, resulting in inadequate network bandwidth and latency for users' computational needs.
Innovation Solution
A system dynamically predicts computing resource requirements and recommends routes for autonomous vehicles to aggregate edge computing resources by adjusting their positions and speeds to maintain a predetermined geographic area, ensuring sufficient edge computing resources are available to satisfy user demands, while incentivizing vehicle owners to participate in edge computation through a blockchain-based incentive program.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If autonomous vehicles travel independently without coordination, then each vehicle maintains its own route flexibility, but edge computing resources are insufficient to satisfy user computational needs
Solution Approach 1:
The patent merges multiple autonomous vehicles into a coordinated fleet that travels together along common routes. By combining the computing resources of multiple vehicles within a predetermined geographic area, the system aggregates sufficient edge computing power to satisfy user computational needs while maintaining route coordination through the server.
Solution Approach 2:
The patent creates a multi-functional system where autonomous vehicles serve dual purposes: their primary function of transportation and a secondary function as mobile edge computing nodes. The vehicles participate in edge computation when grouped together, providing universal computing services to users without requiring dedicated computing infrastructure.
2Quantity of substance
If vehicles are grouped together to aggregate computing resources, then sufficient edge computing resources are provided, but vehicles lose route independence and require coordination
Solution Approach 1:
The patent introduces a server as an intermediary that coordinates vehicle grouping and route adjustment. The server receives vehicle location information, determines optimal groupings to aggregate computing resources, and provides route recommendations to vehicles. This intermediary manages the coordination complexity centrally, allowing vehicles to maintain relative simplicity while still achieving resource aggregation.
Solution Approach 2:
The patent implements dynamic vehicle grouping where the composition and configuration of vehicle fleets change in real-time based on computing resource requirements and route conditions. Vehicles can dynamically join or leave groups, and the system continuously adjusts groupings to optimize both resource aggregation and route efficiency, making the coordination system adaptive rather than rigid.
3Quantity of substance
If vehicles adjust positions and speeds to maintain geographic area, then computing resources are aggregated effectively, but travel time and energy consumption increase
Solution Approach 1:
The patent applies partial coordination where vehicles adjust their positions and speeds only to the extent necessary to maintain the predetermined geographic area for resource aggregation. Rather than requiring complete synchronization or strict formation keeping, the system allows vehicles to make minimal adjustments sufficient for computing resource aggregation, reducing the time and energy overhead while still achieving the desired resource pooling effect.
Data Source
AI summary
In an approach to improve mobile computation while traveling by dynamically generating one or more routes base on computing resource requirements of one or more endpoint devices. Embodiments identify, in real time, a plurality of autonomous vehicles, wherein the plurality of autonomous vehicles are traveling along a common route. Further embodiments, adjust, in real time, relative positions and speeds of the plurality of autonomous vehicles to maintain the plurality of autonomous vehicles within a predetermined geographic area while traveling along the common route, and wherein the predetermined geographic area is sufficient to collectively provide an amount of edge computing resources to satisfy one or more computing resource requirements of the one or more endpoint devices located within a first autonomous vehicle. Additionally, embodiments adjust, in real time, a route of the first autonomous vehicle based on the common route of the plurality of autonomous vehicles providing the edge computing resources.