Coordinated Data Replication Scheduling Protocol
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Solution Overview
Problem
Storage replication methods often face challenges in efficiently scheduling replication events to meet recovery point objectives (RPOs) while minimizing network bandwidth utilization and reducing the impact of RPO violations, leading to poor network bandwidth utilization and unpredictable completion times.
Innovation Solution
A protocol that generates and schedules replication events for data sets by calculating a fitness value based on penalties for RPO violations and computational resource utilization, selecting the best schedule to minimize bandwidth usage and RPO violations within given allotments, using techniques such as random perturbation and crossover operations to optimize replication timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If replication events are scheduled independently for different data objects, then each data object's RPO requirement can be met, but network bandwidth utilization becomes poor and completion times become unpredictable
Solution Approach 1:
The patent combines multiple independent replication schedules into a single coordinated schedule that manages replication events across multiple data objects simultaneously. This coordination merges previously independent scheduling decisions into a unified approach that optimizes network bandwidth utilization while ensuring all RPO requirements are met.
Solution Approach 2:
The patent introduces dynamic scheduling that adjusts replication timing based on network conditions and data object priorities. Rather than fixed independent schedules, the system dynamically coordinates replication events to optimize bandwidth usage while maintaining RPO compliance, making the scheduling adaptive to changing conditions.
2Productivity
If intelligent scheduling of replication events is used to improve network bandwidth utilization, then bandwidth efficiency improves, but it may not be possible to satisfy the RPO for all data objects over time given available network bandwidth
Solution Approach 1:
The patent changes scheduling parameters dynamically, adjusting replication timing and priorities based on network bandwidth availability and RPO requirements. By modifying these parameters intelligently, the system achieves optimal bandwidth utilization while maintaining RPO satisfaction for all data objects.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor network bandwidth usage and RPO compliance in real-time, using this information to adjust future replication scheduling decisions. This feedback loop ensures that bandwidth optimization does not compromise RPO requirements.
3Reliability
If replication events are repeated at scheduled points in time to satisfy RPO, then data protection is ensured, but total network bandwidth consumption increases
Solution Approach 1:
The patent implements periodic replication actions that are coordinated across multiple data objects. By scheduling replications periodically but in a coordinated manner rather than independently, the system maintains data protection while reducing overall network bandwidth consumption through efficient resource sharing and load balancing.
Data Source
AI summary
The replication of a group of data sets is coordinated into a single schedule based on the recovery point objective (RPO) of each data set. The resulting generated schedule satisfies each data set's RPO requirements and minimizes bandwidth use. If necessary bandwidth exceeds available bandwidth, the resulting generated schedule attempts to best satisfy each data set's RPO requirements given the available bandwidth.