Cloud Desktop Pool Provisioning Across Regions Under Demand Constraints
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Solution Overview
Problem
Existing cloud-based virtual desktop systems face challenges in providing optimal cloud desktops due to fluctuating demand and regional resource constraints, leading to availability issues and unnecessary costs, especially during peak usage or disaster scenarios, without requiring human intervention.
Innovation Solution
A system with a monitoring service and desktop pool resource management engine that collects data from cloud regions and client devices to create a priority list for allocating virtual desktops based on user profiles, constraints, and dynamic conditions, ensuring efficient provisioning from multiple cloud providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If cloud desktops are provisioned from a single cloud provider region, then device complexity is reduced, but availability deteriorates during peak demand or regional failures
Solution Approach 1:
The patent combines multiple cloud provider regions into a unified desktop pool, allowing the system to provision desktops from any available region across multiple cloud providers. This merging approach maintains reliability during regional failures or peak demand by enabling cross-region provisioning, while the underlying complexity is abstracted away through automated resource management.
Solution Approach 2:
The desktop pool is designed to universally provision virtual desktops from multiple cloud provider regions through a single interface. The system can dynamically select and provision desktops from any configured cloud region based on availability, making the provisioning system multi-functional and adaptable to different regional conditions without requiring separate provisioning mechanisms.
2Reliability
If cloud desktops are dynamically provisioned across multiple cloud provider regions, then availability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a desktop pool as an intermediary layer between users and multiple cloud provider regions. This intermediary abstracts the complexity of multi-region provisioning by presenting a unified interface while handling the intricate logic of resource allocation, region selection, and cross-cloud coordination internally, thereby improving availability without exposing complexity to end users.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor cloud region availability, resource capacity, and performance metrics. This feedback enables automated adjustments to provisioning strategies, allowing the system to dynamically respond to changing conditions across multiple regions while maintaining optimal performance and availability without manual intervention.
3Speed
If cloud desktops are statically allocated in a single region, then provisioning speed is fast, but adaptability deteriorates during demand fluctuations
Solution Approach 1:
The patent transforms the static desktop allocation model into a dynamic one where desktop pools can automatically adjust resource allocation across multiple cloud regions based on real-time demand conditions. The system dynamically provisions desktops from the most appropriate regions, scales resources up or down, and redistributes capacity across regions as needed, maintaining fast provisioning speeds while adapting to fluctuating demand patterns.
Data Source
AI summary
A system and method for providing virtual desktops to client devices of users is disclosed. The system includes available cloud regions that each can provide virtual desktops and associated resources. A desktop pool resource management engine is coupled to the available cloud regions and collects constraint data from the available cloud regions as well as operational data from desktop clients and desktop agents. A cloud usage profile is created for a subset of the users from the operational data. A priority list of available cloud regions for a user in the subset is created based on the usage profile and the constraint data of the available cloud regions. The highest priority cloud region from the priority list is recommended for the user requesting a desktop. A control plane selects the highest priority cloud region according to the priority list to provide the desktop to the client device.