Application Framework for Simulation Data Normalization

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Solution Overview

Problem

The complexity and cost associated with integrating and processing data from diverse sources with different formatting and packaging requirements in distributed computing environments, particularly in cloud-based systems, hinder efficient simulation and application development, making it challenging to test prototype applications across various architectures.

Innovation Solution

An application framework is implemented with an abstract service layer and a real service layer, utilizing services like data ingestion, time series storage, and event handling to manage data formatting and configuration, allowing applications to subscribe to data channels and process data in standardized formats, thereby reducing the need for custom coding and overhead.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data from diverse sources with different formatting and packaging requirements is integrated and processed, then data utility and application functionality are improved, but system complexity and integration cost increase

Engineering Contradiction:

Improvedata compatibilityVSAvoidintegration complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces a data normalization service as an intermediary component that sits between diverse data sources and applications. This service automatically transforms and standardizes data from various sources (different formats, packaging, time series) into a unified structure, eliminating the need for custom integration code for each data source while maintaining full compatibility with application requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If custom code is written to configure and adapt data from designated sources for specific applications, then data processing accuracy is improved, but development time and effort increase

Engineering Contradiction:

Improvedata processing accuracyVSAvoiddevelopment time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The data normalization service operates autonomously to perform data transformation and configuration tasks. Instead of requiring developers to write custom adaptation code, the system self-configures data pipelines by automatically detecting source characteristics and applying appropriate transformation rules, thereby maintaining processing accuracy while eliminating manual coding effort

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The normalization service provides universal data transformation capabilities that work across multiple data sources and application types. A single service instance can handle various data formats, packaging schemes, and time series configurations, replacing the need for multiple specialized custom code solutions

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If data formatting and configuration tasks are performed manually by system engineers, then integration quality is improved, but labor cost and overhead increase

Engineering Contradiction:

Improveintegration qualityVSAvoiddevelopment cost

Core Design Contradiction:

ReliabilityVSEase of manufacture

Solution Approach 1:

The patent replaces the manual mechanical process of data configuration (engineers writing and debugging integration code) with an automated computational system. The normalization service uses algorithmic rules and automated detection to perform formatting and configuration tasks, maintaining integration quality while eliminating manual labor costs and reducing overhead

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Reliability

If prototype applications are tested across different computing architectures with real-time large-scale data platforms, then application reliability is improved, but testing complexity and resource requirements increase

Engineering Contradiction:

Improveapplication reliabilityVSAvoidtesting complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The normalization service creates standardized data copies that can be efficiently distributed and tested across multiple computing architectures. By normalizing data beforehand, the system enables parallel testing on different platforms without requiring complex architecture-specific data preparation, thereby improving reliability verification while reducing testing complexity

Inventive Principle:

Principle #26Copying

Data Source

PatentUS10747595B2Application framework for simulation engineering

Publication Date: 2020.08.18 SAP SE

AI summary

Systems and methods for defining application preferences for one or more attributes associated with data communicated between one or more applications and one or more data sources. A first set of attributes may be associated with data communicated with a first application. At least the first application, in an application framework implemented over an abstract service layer and a real service layer, may be deployed. The abstract service layer may comprise a first set of services including at least one of a data ingestion service, a time series storage service and event handling service. The real service layer may comprise a second set of services including at least one of a local file system, a cloud-based file system, and a streaming data resource for communicating data with at least the first application via a streaming mechanism over one or more data channels.