Data Center Load Balancing via Virtualized Migration
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Solution Overview
Problem
Modern data centers face challenges in optimizing configuration due to tightly coupled applications and physical resources, leading to disruptive reconfigurations and over-provisioning, as changes require shutting down or quiescing applications and migrating data, which discourages administrators from optimizing.
Innovation Solution
A method and system that monitors loads in data centers, detects overloads, and combines server and storage virtualization to plan and orchestrate allocation migrations between modules, reducing overloads through planned migration and load balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If physical reconfiguration is performed to optimize data center, then resource utilization is improved, but application service continuity deteriorates due to required shutdowns
Solution Approach 1:
The system segments the data center into virtualized server modules and storage modules, allowing independent management and migration of virtual resources without affecting the entire system. This enables selective reconfiguration of specific virtual machines or storage volumes while maintaining service continuity for other components.
Solution Approach 2:
The patent introduces a virtualization layer as an intermediary between physical resources and applications. This virtualization intermediary abstracts the physical infrastructure, allowing reconfiguration at the virtual level without direct impact on running applications, thus maintaining service continuity during optimization.
2Productivity
If administrators perform reconfiguration optimizations, then resource efficiency is improved, but operational complexity increases due to migration planning
Solution Approach 1:
The system implements automated monitoring and self-service capabilities that continuously track resource utilization and automatically initiate migration processes when optimization opportunities are detected. This reduces the need for manual administrative intervention and simplifies operational complexity while maintaining resource efficiency improvements.
Solution Approach 2:
The patent employs preliminary action by pre-planning migration paths and pre-allocating target resources before actual migrations occur. The system continuously monitors and prepares migration candidates, so when optimization is needed, the execution is streamlined and less complex for administrators.
3Reliability
If over-provisioning is used to prevent overloads, then service availability is improved, but resource waste increases
Solution Approach 1:
The system implements dynamic resource allocation that automatically adjusts resource distribution based on real-time workload demands. Instead of static over-provisioning, the virtualization platform continuously monitors load conditions and dynamically migrates resources to match actual needs, preventing both overloads and resource waste simultaneously.
Solution Approach 2:
The patent incorporates feedback mechanisms through continuous monitoring of resource utilization metrics. This feedback loop enables the system to detect when resources are underutilized or overloaded and automatically trigger migration or reallocation actions, replacing static over-provisioning with adaptive resource management that eliminates waste while maintaining availability.
Data Source
AI summary
The invention provides a method and system for continuous optimization of a data center. The method includes monitoring loads of storage modules, server modules and switch modules in the data center, detecting an overload condition upon a load exceeding a load threshold, combining server and storage virtualization to address storage overloads by planning allocation migration between the storage modules, to address server overloads by planning allocation migration between the server modules, to address switch overloads by planning allocation migration mix between server modules and storage modules for overload reduction, and orchestrating the planned allocation migration to reduce the overload condition in the data center.