Dynamic Resource Allocation in Virtualization Systems
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Solution Overview
Problem
Conventional virtualization systems face challenges in efficiently managing resources, including I/O congestion, inadequate resource allocation, and inflexible configuration, which leads to inefficiencies and poor performance in handling varying application demands and infrastructure changes.
Innovation Solution
The introduction of supply chain economics and container management techniques to optimize resource allocation and performance in container systems, allowing for dynamic adjustment of resources based on demand, using virtual currency units and automated decision-making to allocate and reallocate resources efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional virtualization systems allocate excessive resources to handle peak demands, then system reliability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where the virtualization system continuously monitors resource utilization metrics and automatically adjusts resource allocation based on actual demand. This allows the system to maintain reliability during peak demands while optimizing resource utilization during lower demand periods, resolving the contradiction between reliability and resource efficiency.
Solution Approach 2:
The system employs feedback mechanisms that monitor resource usage patterns and performance metrics, then use this information to dynamically adjust resource allocation. The feedback loop enables the system to respond to changing demands in real-time, maintaining reliability while avoiding excessive resource allocation, thus improving overall resource utilization efficiency.
2Productivity
If virtualization systems perform multiple I/O intensive tasks concurrently, then productivity is improved, but I/O congestion increases
Solution Approach 1:
The patent implements I/O scheduling mechanisms that ensure continuous and balanced access to storage resources across multiple virtual machines. By carefully managing the timing and priority of I/O operations, the system maintains high productivity while preventing congestion through continuous monitoring and adjustment of I/O flows.
Solution Approach 2:
The system dynamically changes I/O parameters such as queue depth, transfer sizes, and timing based on current system conditions. This allows the system to optimize productivity by adjusting I/O parameters in real-time while preventing congestion through parameter adaptation to current load conditions.
3Device complexity
If conventional virtualization systems use static resource allocation, then device complexity is reduced, but adaptability to varying demands deteriorates
Solution Approach 1:
The patent implements self-service resource allocation where the virtualization system automatically monitors its own resource usage and dynamically adjusts allocation without requiring complex external management. This self-managing approach maintains low operational complexity while achieving high adaptability to varying demands through automated decision-making based on real-time metrics.
Data Source
AI summary
Methods, systems, and apparatus, including computer program products, for assuring application performance by matching the supply of resources (e.g., application resources, VM resources, or physical resources) with the fluctuating demand placed on the application. For example, the systems and methods disclosed herein can be used to ensure that the application is allocated sufficient resources when it is initially deployed to handle anticipated demand; dynamically alter the resources allocated to the application during operation by matching the resource requirements to the actual measured application demand; and predict future resource requirements based on planning assumptions related to future application demand.