Telemetry Routing Table Path Selection
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Solution Overview
Problem
Existing communication techniques face challenges in optimizing network communications between applications, particularly for telemetry data, due to latency and throughput issues caused by congestion and varying network conditions, leading to delayed data delivery which can result in operational and financial impacts.
Innovation Solution
A system that maintains a routing table with latency and throughput metrics for multiple communication pathways, allowing the source application to select the best pathway for message transmission based on message size and performance parameters, and periodically updates these metrics using test messages to adapt to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single communication pathway is used for telemetry data transmission, then the system is simple to operate, but latency and throughput performance deteriorate under varying network conditions
Solution Approach 1:
The patent implements dynamic path selection where the source application continuously monitors performance metrics (latency, throughput, packet loss) for multiple communication pathways and adapts its routing decisions based on real-time network conditions. This allows the system to automatically switch between static and dynamic routing modes, selecting the optimal pathway for each telemetry message based on current performance data.
Solution Approach 2:
The system changes routing parameters dynamically by maintaining a routing table that stores performance metrics for multiple pathways and selects pathways based on message size and performance parameters. The source application periodically updates these metrics using test messages, allowing the system to adapt to changing network conditions without manual intervention.
2Speed
If multiple communication pathways are monitored and selected based on performance metrics, then data delivery speed is improved, but system complexity increases
Solution Approach 1:
The source application performs self-service by automatically generating test messages, measuring performance metrics, updating the routing table, and selecting optimal pathways without external intervention. The destination application similarly updates its own routing information, allowing both endpoints to independently manage and optimize their communication paths.
Solution Approach 2:
The system implements feedback loops where performance metrics are continuously measured and used to update routing decisions. The source application periodically sends test messages through multiple pathways, measures latency and throughput, and uses this feedback to select the best pathway for subsequent telemetry data transmission.
3Measurement precision
If performance metrics are continuously updated using test messages, then routing accuracy is improved, but network bandwidth is consumed
Solution Approach 1:
Instead of continuous monitoring, the system performs periodic updates of routing metrics at predetermined intervals. The source application periodically generates test messages to refresh performance data in the routing table, balancing the need for accurate metrics with the constraint of limited network bandwidth for telemetry data.
Data Source
AI summary
A computer-based method for improving the timely delivery of telemetry or other application-to-application data. A telemetry routing table is stored in memory that includes entries for a plurality of communication pathways for delivering a telemetry message from a telemetry application running on a first computer system to a telemetry reception application running on a second computer system. The table entries include a latency and a measured data delivery rate for transmittal of data over the corresponding pathway. The method includes generating a telemetry message having a particular data payload using the telemetry application and then selecting one of the communication pathways using the telemetry application based on a size of the data payload, the latencies, and the data delivery rates for the pathways (e.g., determining a total transit time for the payload for each pathway and selecting the pathway corresponding to the shortest transit time).