Timing Models for Data Processing Pipeline Latency Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Monitoring and testing of complex data processing pipelines is challenging due to component latency variations across different computing environments, affecting behavioral similarity and portability, especially in simulations and production environments.
Innovation Solution
Generating and using timing models based on log data from production environments to control the execution timing of components and input/output messages within data processing pipelines, ensuring consistent behavior across environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data processing pipelines are executed in different computing environments, then computational efficiency and resource utilization improve, but component latency variations cause behavioral inconsistencies and reduce portability
Solution Approach 1:
The patent creates timing models that copy the latency behavior characteristics from production computing environments to simulation environments. By capturing and reproducing the temporal patterns of component execution and message passing, the simulation can faithfully replicate production behavior without requiring identical hardware, thus maintaining behavioral consistency while allowing execution in different computing environments.
Solution Approach 2:
The patent introduces timing models as adjustable parameters that control the execution speed and latency of components in the data processing pipeline. By modifying these timing parameters, the system can adapt to different computing environments while maintaining the relative temporal relationships between components, thus resolving the contradiction between computational efficiency and behavioral consistency.
2Speed
If component execution timing is optimized for production environments, then processing speed improves, but testing and simulation accuracy deteriorate due to latency variations
Solution Approach 1:
The timing models copy the actual latency measurements from production environments to create accurate simulation models. By preserving the measured timing characteristics in the simulation environment, the system can accurately measure and analyze component behavior during testing while maintaining the same temporal relationships as in production, thus improving both simulation accuracy and processing speed optimization.
Solution Approach 2:
The patent performs preliminary timing measurements and model creation in production environments before conducting simulations. By capturing the actual execution timings and creating timing models in advance, the system establishes accurate baseline data that can be used to validate and optimize processing speed without compromising simulation accuracy during the testing phase.
3Reliability
If timing models are used to control component execution, then behavioral similarity across environments improves, but system complexity increases
Solution Approach 1:
The timing models act as intermediary components between the data processing pipeline and the execution environment. Rather than directly controlling each component's execution timing, the timing models serve as a mediating layer that translates high-level timing specifications into concrete execution schedules, thus improving behavioral similarity while managing system complexity through abstraction.
Solution Approach 2:
The patent applies timing models selectively to specific components and message passing operations that require precise timing control, rather than uniformly controlling all components. By focusing timing control only where necessary to maintain behavioral similarity, the system achieves the desired reliability without unnecessarily increasing overall system complexity.
Data Source
AI summary
A controller may use a timing model to control and coordinate the execution of components within a data processing pipeline. The timing model may be generated based on log data collected during execution of the components, to model component latencies and pipeline behavior in a production environment. The controller may use the timing model to control the timing of the inputs to, the outputs from, and the execution of various interacting components in the data processing pipeline. The timing model may include component-specific and/or channel-specific timing data, and in various implementations may be based on inputs provided to the components, the timing and contents of outputs from the components, and/or the number of times particular code is executed within the components.


