Adaptive Data Movement Scheduling for Storage Systems
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Solution Overview
Problem
Current data movement scheduling for disaster recovery purposes is manually static and does not adequately account for dynamic resource consumption across different time zones and service levels, leading to potential resource overload and inefficient data transfer.
Innovation Solution
A system that proactively collects historical performance statistics to automatically schedule data movement operations by assigning weight factors to resources and using ranking algorithms to determine optimal time windows, ensuring minimal disruption due to resource availability and network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data movement operations are scheduled manually and statically based on human empirical knowledge, then scheduling simplicity is maintained, but resource consumption efficiency deteriorates due to inability to adapt to changing resource availability across different time zones and service levels
Solution Approach 1:
The patent implements dynamic scheduling by automatically determining optimal time windows for data movement operations based on real-time resource consumption patterns. The system continuously monitors resource usage across different time zones and service levels, then adapts scheduling decisions accordingly, replacing static manual schedules with dynamic automated optimization.
Solution Approach 2:
The system incorporates feedback mechanisms by collecting historical performance statistics and resource consumption data, then using this information to continuously refine and optimize scheduling decisions. The automated scheduler learns from past resource usage patterns to improve future scheduling efficiency across multiple time zones and service levels.
2Productivity
If multiple data movement operations are scheduled without adaptive resource consideration, then operational coverage is maintained, but resource overload occurs leading to infrastructure overwhelm
Solution Approach 1:
The system dynamically adjusts data movement scheduling based on real-time resource availability conditions. By monitoring resource consumption patterns across different time zones and service levels, the system automatically modifies operational schedules to prevent resource overload while maintaining comprehensive operational coverage.
Solution Approach 2:
The patent implements preliminary action by proactively determining optimal time windows for data movement operations before resource overload occurs. The system analyzes historical performance statistics and predicts future resource availability, then schedules operations in advance during optimal windows to prevent infrastructure overwhelm.
3Speed
If data movement is accelerated without considering resource contention, then transfer speed is improved, but resource contention increases causing operational disruption
Solution Approach 1:
The system dynamically balances data transfer speed with resource contention levels by continuously monitoring resource consumption patterns. The automated scheduler accelerates data movement during optimal time windows when resources are available, then reduces or pauses operations when resource contention thresholds are approached, maintaining both speed and stability.
Data Source
AI summary
Techniques for determining optimal time window for data movement from a source storage system to a target storage system are described herein. According to one embodiment, statistics data is received representing historic performance statistics over a predetermined period of time by a source storage system, where the historic performance statistics include resource consumption of a plurality of resources including at least one of a processor, memory, input-output (IO) transactions, and network bandwidth. An analysis is performed by an analysis module executed by a processor on the historic performance statistics to determine an optimal time window within the predetermined time period for data movement from the source storage system to a target storage system based on the analysis. A scheduler executed by the processor is to schedule the data movement from the source storage system to the target storage system according to the optimal time window.