Testing Platform Load Adjustment for Device Under Test
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional test tools face challenges in maintaining a target operations rate at a device under test throughout a testing period, especially in environments with varying processing demands and estimating data processing rates for L7 communications.
Innovation Solution
A testing platform adjusts the number of simulated users or virtual threads to maintain or obtain a target operations rate by determining the optimum number of concurrent executions, using an iterative convergence algorithm to hone in on the correct virtual thread count or number of simulated users that results in an operations rate closest to the target.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional test tools send streams of test packets to a device under test, then the device can be tested for functionality and performance, but the tools face challenges in maintaining a target operations rate throughout the testing period
Solution Approach 1:
The testing platform implements a feedback mechanism where the load adjustment controller continuously monitors the current operations rate at the device under test and compares it to the target operations rate. Based on this feedback, the system dynamically adjusts the number of simulated users or virtual threads to maintain the target rate, resolving the contradiction between reliability and complexity by introducing intelligent control
Solution Approach 2:
The system transitions from static test packet transmission to dynamic load adjustment by modifying the number of concurrent simulated users or virtual threads during the testing period. This dynamic adaptation allows the system to maintain target operations rate despite varying processing demands, addressing the reliability challenge
2Productivity
If the testing platform increases the number of simulated users or virtual threads to achieve higher operations rates, then the target rate can be reached, but the processing demands on the device under test increase
Solution Approach 1:
The system changes the parameter of simulated user count or virtual thread count to control the operations rate. By adjusting this parameter dynamically based on feedback, the system can achieve target productivity while managing the stress on the device under test through controlled increments rather than maximum immediate load
3Measurement precision
If the testing platform uses an iterative convergence algorithm to determine the optimum number of virtual threads, then the target operations rate can be precisely achieved, but the testing process requires multiple iterations
Solution Approach 1:
The system performs preliminary testing iterations to establish the relationship between virtual thread count and operations rate before the main benchmarking test. This preliminary action creates a lookup table or model that allows the system to quickly determine the appropriate thread count during the actual test, reducing the time loss while maintaining measurement precision
Data Source
AI summary
Methods, systems, and computer readable media for adjusting load at a device under test are disclosed. According to one method, the method occurs at a testing platform. The method includes determining whether a current operations rate associated with a device under test (DUT) is near a target operations rate, wherein the current operations rate is associated with one or more simulated users being simulated by the testing platform. The method also includes adjusting the current operations rate by increasing or decreasing the number of simulated users interacting with the DUT in response to determining that the current operations rate associated with the DUT is not near a target operations rate.