Data Protection Manager Dynamic Concurrency Subsystem
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Solution Overview
Problem
Existing data protection systems face inefficiencies in managing concurrent operations across subsystems, leading to potential bottlenecks and performance issues due to static concurrency allocation, which can result in suboptimal performance and resource underutilization.
Innovation Solution
A data protection manager system dynamically adjusts concurrency and priority mappings based on real-time subsystem statistics to optimize the performance of data protection services, ensuring efficient resource allocation and handling of concurrent operations across subsystems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static concurrency allocation is used across subsystems, then system simplicity is maintained, but system performance and resource utilization deteriorate due to bottlenecks and suboptimal operation
Solution Approach 1:
The patent implements dynamic concurrency allocation by continuously monitoring subsystem performance metrics (such as throughput, latency, and resource utilization) and adjusting concurrency levels in real-time. This allows the system to adapt to varying workload conditions and prevent bottlenecks, directly resolving the contradiction between maintaining simple static allocation and achieving high performance through dynamic optimization
Solution Approach 2:
The system employs feedback mechanisms where performance data from subsystems is collected, analyzed, and used to adjust concurrency allocation decisions. This closed-loop control enables the system to respond to changing conditions and optimize resource utilization, transforming the static concurrency model into a performance-driven dynamic system
2Productivity
If dynamic concurrency adjustment is implemented based on real-time statistics, then system performance and resource utilization improve, but system complexity increases
Solution Approach 1:
The patent segments the concurrency management into independent subsystem-level units, where each subsystem can be monitored and adjusted separately. This modular approach reduces overall system complexity by breaking down the complex global optimization problem into smaller, manageable local decisions, while still achieving improved performance through targeted concurrency adjustments
Solution Approach 2:
The system implements self-service mechanisms where subsystems automatically monitor their own performance and adjust their concurrency levels without requiring complex external control. This autonomy reduces the management overhead and system complexity while maintaining high performance through localized optimization decisions
3Productivity
If concurrency is increased to handle more operations, then throughput improves, but resource contention and bottlenecks worsen leading to suboptimal performance
Solution Approach 1:
The patent dynamically changes concurrency parameters based on real-time system state metrics such as resource availability, workload intensity, and subsystem performance. By continuously adjusting these parameters, the system optimizes throughput while preventing resource contention and maintaining stability, resolving the contradiction between increasing operational capacity and managing resource constraints
Data Source
AI summary
In general, in one aspect, the invention relates to a method for managing performances of services, the method comprising: generating subsystem groups, wherein each subsystem group of the subsystem groups comprises a plurality of subsystems, wherein each subsystem group is associated with one a plurality of services, wherein the subsystem groups are generated using per-service subsystem requirements; and performing at least one of the plurality of services using a subsystem group of the subsystem groups.