Dynamic Virtual Cluster Expansion for Resource Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing virtual cluster systems cannot automatically expand to meet increasing resource demands, leading to reduced job processing speed and potential data loss due to fixed sizes, despite advancements in hypervisor technology and resource management for single virtual machines.
Innovation Solution
A system and method for dynamically expanding virtual clusters by monitoring resource availability, adjusting thresholds based on VM instances, access times, and server pool resources, and automatically allocating additional VM instances of specific types to meet resource requirements, ensuring efficient resource utilization and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the virtual cluster size is fixed after establishment, then the system structure is simple and stable, but the processing speed reduces and data loss occurs when resource demand increases
Solution Approach 1:
The patent implements dynamic expansion of virtual clusters by automatically adding VM instances based on monitored resource usage metrics. The system transitions from a fixed cluster size to a dynamic one where the number of VM instances can increase or decrease automatically according to resource availability and demand, resolving the contradiction between fixed structure stability and processing speed requirements.
Solution Approach 2:
The patent employs feedback mechanisms by continuously monitoring resource usage metrics (CPU utilization, memory usage, storage capacity) and using this information to trigger automatic expansion or contraction of the virtual cluster. This closed-loop control system ensures the cluster size adapts to actual workload demands, improving processing speed while maintaining manageable complexity through automated decision-making.
2Extent of automation
If manual modification of virtual cluster settings is required for expansion, then system stability is maintained, but automation level is low and response time is slow
Solution Approach 1:
The patent enables the virtual cluster to self-manage its expansion and contraction based on predefined policies and monitored metrics. The system automatically determines when expansion is needed, selects appropriate VM instances to add, and configures them without human intervention. This self-service capability dramatically improves automation level and reduces the time lag between resource demand and allocation.
Solution Approach 2:
The patent implements preliminary action by pre-configuring expansion policies and thresholds before resource demands arise. The system is prepared in advance with defined rules for when and how to expand, allowing immediate automated response when triggers are activated, thus reducing response time while maintaining controlled stability.
3Productivity
If the virtual cluster size is increased to meet growing data processing needs, then processing capacity improves, but resource utilization efficiency decreases
Solution Approach 1:
The patent applies dynamics by making the virtual cluster size adaptable rather than static. The system automatically adjusts the number of VM instances based on real-time resource usage monitoring, ensuring that processing capacity scales with actual demand. This prevents over-provisioning and maintains high resource utilization efficiency while meeting growing data processing needs.
Solution Approach 2:
The patent utilizes parameter changes by adjusting key operational parameters (number of VM instances, resource allocation per instance) based on monitored performance metrics. The system dynamically modifies these parameters to optimize the balance between processing capacity and resource utilization efficiency, avoiding both under-provisioning and wasteful over-provisioning.
4Adaptability or versatility
If monitoring and automatic expansion systems are implemented, then productivity and adaptability improve, but system complexity increases
Solution Approach 1:
The patent achieves universality by designing a monitoring and control system that handles multiple functions through a unified framework. The same infrastructure monitors various resource metrics (CPU, memory, storage) and applies consistent expansion/contraction logic across different scenarios. This multi-functional approach improves adaptability while managing complexity through standardized processes rather than separate specialized systems.
Data Source
AI summary
Provided are a system and method for dynamically expanding a virtual cluster having one or more virtual machines (VMs), based on the resource availability of the virtual cluster and the type of the virtual cluster. The system for dynamically expanding a virtual cluster having one or more virtual machines (VMs), the system comprising a monitor unit which measures resource availability of a target virtual cluster and provides the resource availability to an expansion control unit, the expansion control unit which determines whether to expand the target virtual cluster based on the resource availability and determines a type and number of VM instances to be additionally allocated to the target virtual cluster by reflecting the resource availability and a type of the target virtual cluster and a virtual cluster configuration unit which modifies profile information of the target virtual cluster such that the determined number of VM instances of the determined type by the expansion control unit can be additionally allocated to the target virtual cluster.