Closed Control Loops for Data Center Service Relocation
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Solution Overview
Problem
Cloud providers face challenges in dimensioning data centers and managing access bandwidth due to the rapid creation and change of applications, leading to performance degradation for customers.
Innovation Solution
Implementing closed control loops within data centers that monitor network congestion and class of service data to autonomously adjust and relocate hosted services based on performance thresholds and time-based criteria, allowing for real-time optimization without external control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud providers rapidly create and change applications due to virtualization, then service agility and responsiveness are improved, but data center dimensioning and bandwidth management become difficult, leading to performance degradation
Solution Approach 1:
The patent implements closed control loops that continuously monitor network congestion and class of service data, then automatically adjust hosted service allocation and relocation decisions based on real-time performance feedback. This feedback mechanism enables the system to adapt to changing conditions while maintaining performance stability through automated corrective actions.
Solution Approach 2:
The control application executes autonomously within the data center, making independent decisions about service allocation and relocation without external control. The system self-manages performance optimization by automatically analyzing monitoring data, determining threshold violations, and executing service relocation decisions based on predefined policies and real-time conditions.
2Reliability
If hosted services are frequently relocated based on network conditions, then performance optimization is improved, but system complexity and control mechanisms increase
Solution Approach 1:
The control application operates autonomously within the data center, independently analyzing monitoring data and executing service relocation decisions without requiring external control systems. This self-contained approach manages complexity by embedding the control logic directly in the data center environment rather than adding external control infrastructure.
Solution Approach 2:
The system uses predefined performance thresholds and time-based criteria as parameters to trigger service relocation decisions. By establishing clear quantitative thresholds for congestion and class of service violations, the system simplifies complex performance optimization decisions into rule-based automated actions that reduce control system complexity.
3Reliability
If performance monitoring and automated service adjustment are implemented, then customer experience is improved, but processing requirements and operational complexity increase
Solution Approach 1:
The control application continuously monitors network conditions and maintains hosted services in optimal locations through ongoing performance assessment and automated adjustment. This continuous operation ensures consistent customer experience by preventing performance degradation rather than reacting to it, while the automated nature maintains operational efficiency through elimination of manual intervention.
Solution Approach 2:
The closed control loop continuously collects performance data, analyzes threshold violations, and executes corrective service relocation decisions. This feedback-driven approach improves customer experience by rapidly responding to performance issues while maintaining operational efficiency through automated decision-making that eliminates manual analysis and intervention steps.
Data Source
AI summary
Concepts and technologies are disclosed herein for providing a closed control loop for data centers. The data centers can receive monitoring data that can include congestion data and class of service data. The data centers can store the monitoring data in a data storage device, analyze the monitoring data, and determine that a performance threshold is satisfied. In response to a determination that the performance threshold is met, the data centers can determine that a time-based threshold is met. In response to a determination that the time-based threshold is met, the data centers can adjust execution of a hosted service.