Network Informed Policy Creator for Backup Optimization
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Solution Overview
Problem
Current backup software treats all stages of data backup as a single process, leading to unpredictable load distribution and potential backup failures due to overloading of primary and secondary storage systems, as it lacks the ability to determine the best time and path for data transfer based on network device information and historical data.
Innovation Solution
A network informed policy creator (IPC) is integrated into the backup software to monitor network device information, recommend optimal transfer times, and select the best paths for data transfer by analyzing historical data and available resources, decoupling backup stages and optimizing data transfers across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If backup software applies a single backup policy to all stages, then the system is simple to manage, but the primary and secondary storage systems become overloaded during backup windows causing backup failures
Solution Approach 1:
The patent segments the backup process into distinct stages (snapshot creation, data transfer, verification) and applies separate policies to each stage. This allows the system to manage complexity through structured division while preventing overload by controlling resource usage at each stage independently, thus maintaining both reliability and manageable complexity.
2Device complexity
If backup software treats all backup stages as a single process, then the system architecture is simple, but it cannot determine the best time and path for data transfer
Solution Approach 1:
The backup process is divided into separate stages that can be independently managed and optimized. Each stage can be executed at different times and through different network paths based on current system conditions, enabling efficient resource utilization without requiring a completely complex architecture.
Solution Approach 2:
The system dynamically selects the best time and path for each backup stage based on real-time network conditions and system load. This dynamic adaptation allows the backup process to optimize data transfer efficiency while maintaining a relatively simple overall architecture that reacts to changing conditions rather than requiring complex pre-planning.
3Loss of time
If network operators use traditional path selection tools, then they can select the shortest route, but they lack information about the best time to transfer data
Solution Approach 1:
The system performs preliminary analysis of network conditions and historical data before executing backup operations. By pre-assessing network load patterns, bandwidth availability, and system conditions, the system can determine the optimal time for data transfer in advance, preventing time loss without requiring complete real-time information during the actual transfer.
Solution Approach 2:
The system utilizes feedback from network monitoring tools and historical performance data to continuously improve path and time selection. By analyzing past backup performance and current network conditions, the system learns optimal transfer times and routes, converting available network information into actionable insights that reduce transfer time without requiring additional information sources.
Data Source
AI summary
Embodiments for optimizing a backup operation for a data protection system, by connecting with network devices in a network implementing the backup operation, the backup operation implementing a policy that specifies a plurality of service requirements and that is initiated at a time within a plurality of time windows, and determining a size of dataset to be backed up by the backup operation. The method further monitors a flow of data between a source and a destination of data in the network, compiles historical data of operational parameters for data transfers between the source and destination, and determines an optimum time within the plurality of time windows based on the dataset size and the historical data.