Hybrid Real-Time Data Replication for Heterogeneous Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data replication techniques face limitations in preserving data integrity over long haul networks due to latency and network fault sensitivity, and require homogeneous source and destination devices, making them inadequate for real-time data replication across heterogeneous systems.
Innovation Solution
Hybrid real-time data replication techniques that capture all data changes synchronously while performing replication asynchronously, allowing data replication between heterogeneous devices and enabling business continuance, content distribution, and backup consolidation without the need for identical device types or architectures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous data replication is used to preserve data integrity, then data consistency is improved, but latency and network fault sensitivity increase
Solution Approach 1:
The patent segments the data replication process into two distinct phases: a synchronous commit phase that ensures data integrity by obtaining acknowledgments from target devices, and an asynchronous data transfer phase that moves the actual data without blocking the client. This segmentation allows the system to achieve both data integrity and reduced latency by decoupling the critical acknowledgment step from the bulk data transfer.
Solution Approach 2:
The patent performs preliminary actions by first capturing data attributes and metadata before the actual data transfer. The system prepares replication descriptors, validates data integrity, and establishes replication contexts in advance, allowing the subsequent data transfer to proceed asynchronously without impacting the client's perceived performance.
2Reliability
If synchronous data replication is used to ensure data consistency, then data integrity is improved, but network fault sensitivity increases
Solution Approach 1:
The patent divides the replication operation into a critical synchronous segment (attribute capture and acknowledgment) and a non-critical asynchronous segment (bulk data transfer). Network faults during the asynchronous transfer do not affect data consistency because the critical integrity checks were already performed synchronously. This segmentation isolates the system from network fault sensitivity while maintaining data consistency.
Solution Approach 2:
The patent implements beforehand cushioning by capturing data attributes and creating replication descriptors before initiating the data transfer. This preliminary preparation includes validating data integrity and establishing error handling mechanisms, so that even if network faults occur during transmission, the core data consistency is already ensured and recovery can proceed without compromising integrity.
3Productivity
If conventional replication techniques are used, then data replication is achieved, but device homogeneity is required
Solution Approach 1:
The patent implements universality by designing a replication system that can operate across heterogeneous device types, architectures, and operating systems. The replication descriptor format and attribute capture mechanism are architecture-agnostic, allowing the same replication engine to work with different storage devices, processors, and software environments without requiring device homogeneity.
Solution Approach 2:
The patent enables adaptability to heterogeneous devices by dynamically adjusting replication parameters based on the source and target device characteristics. The system captures device-specific attributes and modifies replication behavior accordingly, allowing seamless operation across different device types while maintaining core replication functionality.
4Productivity
If asynchronous replication is used to reduce latency, then performance is improved, but data integrity may be compromised
Solution Approach 1:
The patent segments the replication process into an integrity-critical synchronous phase (attribute capture and acknowledgment) and a performance-optimized asynchronous phase (bulk data transfer). This segmentation ensures that data integrity is established before the asynchronous transfer begins, while the asynchronous phase maximizes performance by not blocking the client. The two phases work together to achieve both integrity and performance goals.
Data Source
AI summary
Techniques are described for replicating data from one to one or more heterogeneous data processing or communication devices for the purpose of remote backup, redundancy, content distribution, communications, observations or measurements. In a first phase, the attributes of the data that are modified or created on a device or that are passing through the device are tracked and journaled in volatile or non-volatile storage in real-time. In a second phase, the attributes that match patterns pre-specified in a configuration are used to determine which data to replicate and which modifications to make the devices. In a third phase, the data is replicated. In a preferred embodiment, the described techniques comprise an application that runs on a host device or is embedded in a logic or memory device. The described invention is designed to be transparent for system redundancy and error recovery processes such as error correction, re-transmission on links, and raid configuration.