Automated Testing of Distributed Processing Grids

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Solution Overview

Problem

Existing methods fail to provide an effective, automated way to test the performance of distributed component-based systems, particularly in terms of workload distribution, fault tolerance, and scalability, especially when dealing with a high number of hardware resources and complex workflows.

Innovation Solution

A method and system that utilize distributed agents and a centralized unit to dynamically adjust workload and monitor the operating status of processing units, allowing for automated testing of distributed-component applications by generating and modifying application loads based on performance data, thereby simulating stress conditions to identify operational limits and verify adaptive mechanisms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If distributed agents and centralized unit are used to dynamically adjust workload and monitor operating status, then automation extent and measurement precision are improved, but device complexity increases

Engineering Contradiction:

Improveautomated testingVSAvoidsystem structure

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The system is divided into multiple distributed agents deployed across the grid infrastructure and a centralized control unit. Each agent independently monitors local processing units and collects performance data, while the centralized unit coordinates overall testing and analyzes aggregated results. This segmentation enables automated testing without requiring a single complex monolithic system.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The centralized control unit acts as an intermediary that receives performance data from distributed agents, processes the information, and sends control signals back to adjust workload distribution. This intermediary structure enables coordinated automation across the distributed grid while maintaining manageable system complexity through clear separation of monitoring and control functions.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If processing workload is increased to test performance limits, then productivity and measurement precision are improved, but reliability deteriorates due to system stress

Engineering Contradiction:

Improvetesting efficiencyVSAvoidsystem stability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system dynamically adjusts workload distribution across processing units based on real-time performance data collected by distributed agents. The centralized control unit modifies testing intensity and workload allocation in response to observed system conditions, enabling high-productivity testing while maintaining system reliability through adaptive load management that prevents overwhelming any single component.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Distributed agents continuously monitor operating status and performance metrics of processing units, feeding this data back to the centralized control unit. The control unit uses this feedback to adjust workload distribution and testing parameters, ensuring that performance limits are tested effectively while system reliability is maintained through real-time adaptive control that responds to actual system conditions.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If monitoring of operating status is performed across multiple processing units, then measurement precision and reliability are improved, but loss of information increases due to data collection complexity

Engineering Contradiction:

Improveperformance monitoring accuracyVSAvoiddata management overhead

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

Performance monitoring is segmented into local data collection by distributed agents at each processing unit and centralized data aggregation by the control unit. Each agent collects and pre-processes performance data locally, reducing the information management burden on the centralized system while maintaining comprehensive monitoring coverage across all processing units for high measurement precision.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Distributed agents perform multiple functions including local performance monitoring, data collection, preliminary data processing, and communication with the centralized control unit. This multi-functionality reduces the overall information management overhead by distributing data processing tasks across the grid infrastructure itself, enabling comprehensive monitoring without proportionally increasing data management complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS8726243B2Method and system for automatically testing performance of applications run in a distributed processing structure and corresponding computer program product

Publication Date: 2014.05.13 TELECOM ITALIA SPA

AI summary

Performance of applications run on a distributed processing structure including a grid of processing units is automatically tested by: running at least one application on the distributed processing structure; loading the application with processing workload to thereby produce processing workload on the distributed processing structure; sensing the operating status of the processing units in the distributed processing structure under the processing workload and producing information signals indicative of such operating status; collecting these information signals; providing a rule engine and selectively modifying, as a function of the rules in the rule engine and the information signals collected, at least one of: the processing workload on the application, and the operating status of the processing units in the grid.