Software Performance Prediction via Benchmark Suite Matching
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Solution Overview
Problem
Current methods for predicting the performance of software applications on multi-tier target systems are complex, error-prone, and inefficient, leading to inaccurate capacity planning and significant losses due to the need for rebuilding models with changes in software application behavior or infrastructure.
Innovation Solution
A system and method that generates a benchmark suite based on standard software applications' performance characteristics, identifies a matching benchmark, remotely executes standard applications on the target system, and predicts the software application's performance using regression equations and Principal Component Analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulation methods are used for performance prediction, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent creates a virtual copy of the target system architecture that mirrors the structural relationships and interaction patterns of the actual multi-tier system. This virtual architecture model serves as a simplified representation that captures essential performance characteristics without requiring full simulation complexity, enabling accurate prediction through analogy rather than exhaustive simulation.
Solution Approach 2:
The patent divides the complex performance prediction problem into separate segments: (1) generating performance data from standard applications on source system, (2) creating virtual architecture model of target system, (3) identifying correlations between source and target performance characteristics, and (4) predicting target system performance. This segmentation reduces overall complexity by handling each aspect independently rather than through monolithic simulation.
2Measurement precision
If analytical models are used for performance prediction, then measurement precision is improved, but adaptability worsens
Solution Approach 1:
The patent implements a dynamic approach where the virtual architecture model can be updated to reflect changes in target system infrastructure, and the correlation relationships are re-established when software application behavior changes. This dynamic adaptation allows the system to maintain prediction accuracy without requiring complete model rebuilding, as the model evolves with the system it predicts.
Solution Approach 2:
The patent changes the fundamental parameter from fixed analytical models to variable correlation parameters derived from actual performance data. By using performance characteristics and correlations discovered from standard applications rather than predetermined analytical formulas, the system adapts to different software applications and infrastructure configurations without requiring model restructuring.
3Ease of operation
If architectural simulator is used for single-server systems, then ease of operation is improved, but adaptability worsens
Solution Approach 1:
The patent creates a universal performance prediction system that functions across both single-server and multi-tier architectures through the virtual architecture model. The same correlation-based prediction methodology applies regardless of system complexity, making the tool universally applicable while maintaining ease of operation. The virtual model abstracts away architectural differences, allowing the same simple interface to handle diverse system types.
Data Source
AI summary
System and method for predicting performance of a software application over a target system is disclosed. The method comprises generating a benchmark suite such that benchmark indicates a combination of workloads applied over a set of standard software applications running on a source system. The method further comprises identifying a benchmark of the benchmark suite, wherein the benchmark has performance characteristics same as that of the software application. The method further enables remotely executing the set of standard software applications associated with the benchmark on the target system with the combination of workload as specified by the benchmark. The method further enables recording a performance of the set of standard software applications on the target system. Based on the performance of the standard software applications on the target system the performance of the software application is predicted.