Vehicle-Remote Computer Timing for Latency-Aware Message Transmission
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Solution Overview
Problem
Communication latency and congestion in vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) networks can lead to delayed message receipt and decreased network efficiency, affecting the timely operation of vehicles.
Innovation Solution
A system that determines a transmission time for data messages based on a best fit line calculated from timestamps, adjusting for expected communication latency to optimize data transfer and reduce network congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data messages are transmitted immediately without latency adjustment, then real-time communication is maintained, but network congestion increases and throughput decreases
Solution Approach 1:
The system performs preliminary actions by calculating the best fit line from historical timestamp data and determining the expected communication latency in advance. This allows the transmission time to be optimized before actual data message transmission occurs, resolving the contradiction by preparing latency compensation parameters beforehand that will maximize throughput while maintaining timely delivery.
Solution Approach 2:
The system changes the transmission time parameter based on calculated latency values derived from best fit line analysis of historical timestamp data. By dynamically adjusting the transmission time parameter rather than using fixed immediate transmission, the system optimizes network throughput while compensating for communication latency, thus resolving the technical contradiction.
2Productivity
If transmission time is adjusted based on best fit line calculation, then network efficiency is maximized, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically calculating the best fit line from its own historical timestamp data and determining optimal transmission times without external intervention. This self-contained approach maximizes network efficiency while managing complexity internally, as the system uses its existing timestamp records to generate optimization parameters without requiring additional complex external systems.
Solution Approach 2:
The system uses feedback from historical timestamp data to continuously refine transmission time calculations. By analyzing past transmission and reception timestamps through best fit line calculation, the system generates feedback loops that improve network efficiency over time while keeping the processing complexity manageable through iterative optimization rather than complex upfront design.
3Measurement precision
If multiple timestamps are collected and processed, then latency prediction accuracy improves, but data processing time increases
Solution Approach 1:
The system applies partial action by collecting and processing a sufficient number of timestamps to achieve adequate latency prediction accuracy without unnecessarily accumulating excessive historical data. The best fit line calculation uses enough timestamp points to generate reliable predictions while avoiding the diminishing returns of processing overly large datasets, thus balancing prediction accuracy with processing time efficiency.
Solution Approach 2:
The system performs preliminary action by pre-calculating the best fit line from historical timestamp data before actual transmission optimization is needed. This preliminary processing of multiple timestamps allows the system to establish accurate latency prediction models in advance, reducing the need for intensive real-time processing and thereby minimizing data processing time while maintaining high prediction accuracy.
Data Source
AI summary
Upon transmitting respective messages to a remote computer communicatively coupled to a computer via a network, respective first timestamps are generated. Upon receiving, from the remote computer, respective second timestamps at which the remote computer received the respective messages via the network, a best fit line is determined based on respective first timesteps between the respective first timestamps and respective second timesteps between the respective second timestamps. A transmission time is determined based on the best fit line and a future second timestep. A data message is transmitted to the remote computer via the network at the transmission time.