Cloud Resource Provisioning via Usage Data Analysis
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Solution Overview
Problem
Users face challenges in determining suitable cloud deployment architectures due to dynamic instantiation and termination of applications and processes, making it difficult to track resource usage and ensure efficient resource allocation in cloud computing environments.
Innovation Solution
A decision system that gathers resource usage data, analyzes it considering varying importance levels of resources, and provides customized deployment architectures by adjusting resource requirements based on importance levels, ensuring optimal allocation of cloud resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud resources are dynamically allocated to support multiple applications and processes, then the system's adaptability and scalability improve, but the complexity of tracking and managing resource usage increases
Solution Approach 1:
The patent introduces a cloud resource management system that acts as an intermediary between cloud resource providers and users. This system automatically tracks resource usage, monitors process requirements, and dynamically allocates resources without requiring users to manually monitor or manage the complexity of cloud resource tracking.
Solution Approach 2:
The system implements continuous feedback mechanisms by monitoring resource usage patterns, process performance metrics, and user requirements. Based on this feedback, the system automatically adjusts resource allocation to maintain optimal performance while simplifying user interaction with the complex cloud infrastructure.
2Manufacturing precision
If users manually monitor and track cloud processes, then resource allocation accuracy improves, but the time and effort required increases
Solution Approach 1:
The cloud resource management system performs self-service by automatically monitoring its own resource allocation, tracking process usage, and adjusting resource distribution without requiring manual user intervention. The system maintains accurate resource tracking while eliminating the time users would otherwise spend on manual monitoring activities.
Solution Approach 2:
The patent replaces manual mechanical monitoring processes with automated electronic systems that continuously track resource usage through software agents and monitoring tools, achieving high accuracy in resource allocation without the time investment required for manual tracking.
3Adaptability or versatility
If cloud processes spawn new processes dynamically, then the system's functionality improves, but the difficulty of tracking the original deployment architecture increases
Solution Approach 1:
The system implements a hierarchical tracking structure where parent processes and child processes are nested within a unified monitoring framework. Each spawned process inherits tracking identifiers from its parent, allowing the system to maintain a nested view of the entire process hierarchy and its resource requirements without losing track of the original deployment architecture.
Data Source
AI summary
An example cloud resource provisioning method comprises: receiving a cloud resource usage data identifying a first cloud resource consumed, a first usage level associated with the first cloud resource, a second cloud resource consumed, and a second usage level associated with the second cloud resource; identifying a preference for the first cloud resource over the second cloud resource; and causing, in view of the analyzing, the first cloud resource to be provisioned at least at the first usage level and the second cloud resource to be provisioned at a reduced usage level below the second usage level.