Database Aware Routers Optimizing Replication Streams
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Solution Overview
Problem
Current distributed storage solutions are inefficient due to complex and resource-intensive database replication processes, lacking context-specific redundancy elimination and optimal caching, especially in database cluster topology unaware systems, which leads to suboptimal network resource utilization and high computational costs.
Innovation Solution
The system optimizes database replication by determining and utilizing the underlying data storage/database cluster topology, enabling routers to optimize replication streams through topology awareness, caching, and policy application, specifically configuring edge routers to manage replication streams and cache data effectively, thereby reducing redundancy and improving network resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional database replication is used across multiple nodes, then data redundancy is achieved, but network resources (memory, CPU cycles) are excessively consumed
Solution Approach 1:
The router is pre-configured with database topology information before replication operations begin. This allows the router to anticipate replication patterns and optimize resource allocation in advance, identifying which data changes need replication and routing them efficiently before the actual replication process consumes network resources.
Solution Approach 2:
The solution applies different replication strategies to different parts of the database topology based on local characteristics. Routers make context-specific decisions about which data changes to replicate to which nodes, rather than uniformly replicating all changes to all nodes. This localized approach reduces unnecessary network traffic while maintaining data redundancy where needed.
2Productivity
If replication process is made context-specific and optimized, then network resource efficiency improves, but system complexity increases due to topology awareness requirements
Solution Approach 1:
The router automatically utilizes the pre-configured topology information to make intelligent replication decisions without requiring complex real-time analysis or manual intervention. The system serves itself by using the stored topology data to autonomously optimize replication paths and resource allocation, achieving context-specific optimization without proportionally increasing operational complexity.
3Stability of the object's composition
If uniform redundancy elimination is applied across all nodes, then data consistency is maintained, but computational cost increases and context-specific optimization is lost
Solution Approach 1:
The solution implements context-specific redundancy elimination at each router based on local topology knowledge. Each router evaluates its own position in the database topology and applies elimination strategies appropriate to its local context, rather than applying a uniform approach across all nodes. This maintains data consistency while reducing overall computational costs by avoiding unnecessary elimination operations.
Data Source
AI summary
A method and system for optimizing replication in a distributed network is described. The instant invention allows for determining existing cluster topology of the network by one or more router(s) device(s) operating in the network, identifying and optimizing a data replication stream/service in use in network, by said router(s); determining a routing scheme based on the cluster topology by the router routing data packets though said network based on said routing scheme and applying predefined policy to a predefined set of router(s) corresponding to identified data replication stream by the router.