Automated Application Modeling for Virtualization
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Solution Overview
Problem
The complexity of managing computing services for groups, particularly in thin client architectures, is exacerbated by application compatibility issues and the resource-intensive nature of robust application virtualization, which can be a barrier for larger organizations due to the need for substantial modeling processes.
Innovation Solution
Automated application modeling for application virtualization is incorporated into an application installer or operating system component, using an auto-modeling agent that employs active or passive strategies to assess and generate application modeling data, reducing the need for extensive manual modeling and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robust application virtualization is implemented, then application isolation and security are improved, but the complexity and resource investment required for manual modeling processes increase significantly
Solution Approach 1:
The system performs self-modeling by automatically analyzing application behavior and generating virtualization models without requiring manual intervention. The modeling process serves itself by using the application's own execution patterns to create the isolation framework.
Solution Approach 2:
The system performs preliminary analysis of application installation packages and execution behavior before full deployment, capturing modeling data in advance to prepare the virtualization environment proactively rather than reactively.
2Manufacturing precision
If manual application modeling is performed for each application, then virtualization accuracy is improved, but the time and resources required increase prohibitively for large organizations
Solution Approach 1:
The system creates copies of application behavior patterns and modeling data that can be reused across multiple applications. By capturing and replicating execution patterns, the system avoids redundant analysis while maintaining accuracy.
Solution Approach 2:
The modeling system serves multiple functions: it analyzes individual applications, generates virtualization models, and creates reusable pattern libraries that benefit future applications, making the process universally applicable across the organization.
3Ease of operation
If thin client architecture is implemented, then management and maintenance burdens are reduced, but application compatibility issues arise due to execution environment constraints
Solution Approach 1:
The system dynamically adjusts virtualization parameters and execution environment configurations based on the specific application being deployed, allowing the same thin client infrastructure to adapt to different application requirements while maintaining centralized management.
Data Source
AI summary
Automated application modeling for application virtualization (auto-modeling) may be incorporated into an application installer and/or other suitable component of a computer operating system. Auto-modeling may be performed by an auto-modeling agent. The auto-modeling agent may employ one or more of multiple auto-modeling strategies. The auto-modeling agent may assess one or more of a particular application, application installation package and/or application environment in order to determine a suitable auto-modeling strategy. Auto-modeling strategies may include active auto-modeling and passive auto-modeling. Active auto-modeling strategies may require at least partial installation and/or execution of the application to be modeled, whereas passive auto-modeling may generate corresponding auto-modeling data independent of application installation and/or execution, for example, by obtaining suitable data from a corresponding application installation package.