Request Arbitration Model for Vehicle Slot Allocation
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Solution Overview
Problem
In a distributed computing ecosystem for providing multimodal transportation services, conflicting requests for vehicle resources often arise, leading to inefficiencies and delays in allocating seats on flights.
Innovation Solution
A computationally efficient approach using a request arbitration model is implemented to prioritize and allocate vehicle slots. This model evaluates incoming requests based on factors such as user account information, travel constraints, and service provider reliability to determine the highest priority requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a distributed computing ecosystem processes multiple transportation requests simultaneously, then service coverage and request handling capacity increase, but resource allocation conflicts and system complexity increase
Solution Approach 1:
The system segments the complex resource allocation problem into independent evaluation dimensions (user account information, travel constraints, service provider reliability). Each dimension is processed separately by the request arbitration model, which then integrates these segmented evaluations to determine overall request priority and allocate vehicle slots without full system-level complexity
Solution Approach 2:
The request arbitration model serves as an intermediary layer between incoming transportation requests and the vehicle slot register. This mediator evaluates requests based on multiple factors, deconflicts resource allocations, and manages the vehicle slot register, thereby handling high request volumes without proportionally increasing overall system complexity
2Productivity
If vehicle slots are allocated based on multiple evaluation factors, then allocation efficiency and service quality improve, but computational overhead and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing the request arbitration model with defined evaluation criteria (user account information, travel constraints, service provider reliability) before requests arrive. This preliminary configuration allows the model to rapidly evaluate incoming requests without performing complex ad-hoc computations, thus improving allocation efficiency while minimizing processing time
Solution Approach 2:
The request arbitration model changes evaluation parameters dynamically based on request characteristics. By adjusting which factors (user account information, travel constraints, service provider reliability) are weighted more heavily depending on the specific request context, the system achieves efficient allocations without fixed computational overhead, adapting processing intensity to actual needs
3Measurement precision
If the system deconflicts conflicting resource requests, then resource allocation accuracy improves, but computational complexity and processing load increase
Solution Approach 1:
The deconflictment process is segmented into independent evaluation dimensions (user account information, travel constraints, service provider reliability) rather than attempting to resolve all conflicts simultaneously. This segmentation enables the request arbitration model to achieve accurate allocations by systematically evaluating each dimension separately, reducing computational complexity while maintaining precision
Data Source
AI summary
Example aspects of the present disclosure provide for an example method. The example method can include accessing a first request for providing transportation along a first multi-leg transportation journey and a second request for providing transportation along a second multi-leg transportation journey. The example method can include querying a vehicle slot register to access data descriptive of unallocated vehicle slots for providing transportation services. The example method can include computing, using a request arbitration model, a first allocation for servicing the first request and a second allocation for servicing the second request. The example method can include updating the vehicle slot register based on the first allocation and the second allocation. The example method can include outputting a first response for the first request indicating the first allocation. The example method can include outputting a second response for the second request indicating the second allocation.