Usage-Scored Virtual Device Scaling for Tenant Demand
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Solution Overview
Problem
Cloud computing systems face challenges in efficiently allocating resources to tenants with diverse usage profiles, leading to overallocation and inefficiencies that increase costs and power consumption.
Innovation Solution
A virtual service upgrade system that collects usage data, evaluates unique characteristics, and determines a current usage score to dynamically upgrade or downgrade virtual devices based on usage patterns, optimizing resource allocation without interrupting user services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud computing systems allocate sufficient resources to meet peak demand, then service reliability is improved, but resource waste increases due to overallocation during low usage periods
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring usage patterns and automatically adjusting virtual device specifications over time. The system transitions from static resource allocation to dynamic adjustment, allowing resources to be reallocated based on actual usage behavior, thereby reducing waste during low usage periods while maintaining reliability during peak demand.
Solution Approach 2:
The system employs feedback mechanisms by collecting usage data, analyzing usage patterns, and using this information to drive resource allocation decisions. The feedback loop includes monitoring current usage, comparing against historical data, and adjusting resource allocation accordingly, which enables the system to optimize between reliability and energy efficiency.
2Adaptability or versatility
If cloud computing systems provide flexible resource allocation, then adaptability is improved, but system complexity increases due to need for continuous monitoring and adjustment
Solution Approach 1:
The system implements self-service automation where resource allocation decisions are made automatically based on predefined criteria and usage patterns. The virtual device management system autonomously analyzes usage data and adjusts resources without requiring manual intervention, reducing the operational complexity despite maintaining high adaptability.
Solution Approach 2:
The patent utilizes parameter changes by modifying virtual device specifications such as CPU capacity, memory size, and storage allocation based on analyzed usage patterns. By systematically changing these parameters in response to usage data, the system achieves flexible resource allocation while managing complexity through automated parameter adjustment processes.
3Productivity
If virtual devices are upgraded frequently to match changing usage patterns, then resource utilization efficiency is improved, but operational disruption increases
Solution Approach 1:
The system performs preliminary analysis of usage patterns and prepares upgrade decisions in advance. By analyzing usage data continuously and pre-calculating optimal resource allocations, the system can execute upgrades during low-activity periods or in advance of predicted demand increases, minimizing operational disruption while maintaining efficiency.
Solution Approach 2:
The patent implements periodic review and adjustment cycles where resource allocation is optimized at scheduled intervals. Rather than continuous disruption, the system performs periodic assessments of usage patterns and executes upgrades during designated maintenance windows, balancing efficiency improvements with minimal operational interruption.
Data Source
AI summary
The present disclosure relates to systems, methods, and computer-readable media for receiving usage data for a virtual device (or other virtual service), analyzing the usage data to determine a usage bucket characteristic of usage of the virtual device over a period of time, and determining a usage score for the virtual device. The systems described herein further involve causing a deployment of the virtual device to be upgraded, downgraded, or otherwise modified based on the usage bucket and associated usage score. The features and functionalities described herein can provide an efficient mechanism for administrating a tenant deployment as well as implementing a more efficient utilization of cloud computing resources for a variety of virtual services.