Virtual Desktop Deployment Model Selection System
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Solution Overview
Problem
The challenge in selecting the appropriate virtual desktop deployment model for enterprises is that existing methods lack a systematic approach, often relying on individual expertise, and fail to balance user needs with enterprise goals effectively, leading to suboptimal solutions that may not meet user satisfaction or fulfill enterprise objectives.
Innovation Solution
A method and system that derive an appropriate target operating environment by defining configuration parameters to identify user and enterprise characteristics, creating fingerprints for operating environments and applications, and comparing these to determine a suitable deployment model based on similarity factors and predetermined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a systematic approach is implemented to select virtual desktop deployment models, then the precision of matching user needs and enterprise goals is improved, but the complexity of the selection process increases
Solution Approach 1:
The patent transforms the selection process by changing parameters from subjective expert judgment to objective systematic evaluation. It defines specific parameters including user characteristics (access flexibility, hardware requirements, personalization needs) and enterprise characteristics (compliance requirements, data security, management ease) that can be measured and compared systematically against different deployment models (thick client, thin client, balanced compute).
Solution Approach 2:
The patent segments the selection process into distinct components: (1) identifying user characteristics and needs, (2) identifying enterprise characteristics and goals, (3) evaluating multiple deployment model options, and (4) systematically comparing options against defined parameters. This segmentation makes the complex selection process more manageable and systematic.
2Adaptability or versatility
If multiple deployment model options are evaluated systematically, then the adaptability to different user needs and enterprise goals is improved, but the time required for assessment increases
Solution Approach 1:
The patent applies preliminary action by pre-defining the evaluation framework, parameters, and deployment model options before the actual selection process. User characteristics, enterprise characteristics, and deployment model criteria are established in advance, allowing for faster systematic evaluation when specific selection needs arise.
Solution Approach 2:
The patent creates a universal evaluation framework that can assess multiple deployment models (thick client, thin client, balanced compute) against the same set of user and enterprise characteristics. This multi-functional approach allows the same systematic process to adapt to different scenarios, users, and enterprise goals without requiring separate assessment methodologies.
3Ease of operation
If expert-based selection methods are used to choose deployment models, then the ease of operation is improved, but the reliability of the solution decreases
Solution Approach 1:
The patent substitutes the mechanical system of expert-based subjective judgment with a systematic evaluation mechanism. Instead of relying on individual expert knowledge and experience, the system uses defined parameters, characteristics, and comparative analysis to objectively determine the most suitable deployment model, thereby improving reliability while maintaining ease of operation through structured processes.
Data Source
AI summary
The present invention relates to a configurable parameter driven system and method for providing an appropriate target operating environment based on user specific needs and enterprise objectives. The configuration parameters can be changed to account for newer computing environment solutions that could appear and could also be tailored for enterprise specific needs. The method fingerprint the end users' based on characteristics and requirements to derive user needs and enterprise criteria's. The method is systematic and flexible amenable to change in varying enterprise environment.