Data Replica Selector for Resilient Network Storage
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Solution Overview
Problem
Existing data replication methods fail to jointly consider resiliency and communication cost, particularly in the context of catastrophic concurrent failures, leading to inefficient data availability during disaster recovery.
Innovation Solution
A computer-implemented method for selecting replication nodes in a network that determines eligible nodes based on communication costs and probabilities of concurrent failure, optimizing the placement of data replicas by factoring physical distance, electrical pathway distance, and other communication parameters to minimize costs while ensuring high availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data is replicated on nodes close to the data source (within the same LAN or building site), then replication cost is reduced, but resiliency to catastrophic failures is compromised
Solution Approach 1:
The patent changes the selection parameters for replication nodes by introducing a composite scoring mechanism that evaluates both communication cost metrics (distance, latency, bandwidth) and resiliency metrics (geographic diversity, infrastructure independence). This multi-parameter approach allows the system to select nodes that optimize the balance between cost and reliability, rather than prioritizing one factor alone.
2Reliability
If data is replicated on remote, geographically diverse sites, then resiliency to catastrophic failures is improved, but replication cost increases
Solution Approach 1:
The system transforms the node selection process by evaluating multiple parameters simultaneously including communication cost (distance, latency, bandwidth) and resiliency factors (geographic diversity, infrastructure independence). This multi-dimensional parameter evaluation enables selection of remote nodes that provide adequate protection while minimizing unnecessary replication costs.
3Reliability
If data is replicated on random nodes in peer-to-peer networks, then geographic diversity is achieved, but communication cost and delay increase significantly
Solution Approach 1:
The patent introduces a composite scoring system that evaluates candidate nodes based on multiple parameters including communication cost metrics (distance, latency, bandwidth) and resiliency metrics (geographic diversity, infrastructure independence). This structured multi-parameter evaluation replaces random selection, ensuring that geographically diverse nodes are chosen while minimizing communication costs and delays.
Data Source
AI summary
There is provided a method and system for replicating data at another location. The system includes a source node that contains data in a data storage area. The source node is coupled to a network of potential replication nodes. The processor determines at least two eligible nodes in the network of nodes and determines the communication cost associated with a each of the eligible nodes. The processor also determines a probability of a concurrent failure of the source node and each of eligible nodes, and selects at least one of the eligible nodes for replication of the data located on the source node. The selection is based on the determined communication costs and probability of concurrent failure.