Storage Network Data Replication Policy Generation

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Solution Overview

Problem

Existing data replication systems in storage networks are limited to location attributes, restricting administrators' ability to generate or modify replication policies to accommodate a wide range of resource attributes, thereby limiting flexibility and adaptability.

Innovation Solution

Implementing systems and methods that allow data objects to be replicated based on user-specified count selections and attribute specifications, using a policy generation module to generate replication policies that consider various resource attributes and rank candidates according to factors like cost, enabling dynamic adaptation and flexibility in data replication.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data replication is based on limited location attributes, then the replication policy framework is simple to implement, but the flexibility and adaptability to accommodate various resource attributes is reduced

Engineering Contradiction:

Improveflexibility to accommodate resource attributesVSAvoidcomplexity of replication policy framework

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system enables a single replication policy framework to handle multiple types of attributes (location, cost, performance, security, etc.) through a universal attribute specification mechanism. The policy engine can process diverse resource attributes using the same framework, making the system multi-functional and adaptable to different replication scenarios without requiring separate policy frameworks for each attribute type.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system allows dynamic specification of resource attributes as parameters in replication policies. Administrators can define policies based on different attribute parameters (such as cost thresholds, performance requirements, security levels) and the system adapts the replication behavior by changing these parameters. This enables flexible policy modification without structural changes to the framework.

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If administrators are locked into location-based replication policies, then the policy implementation is straightforward, but the ability to specify replication based on diverse resource attributes is limited

Engineering Contradiction:

Improveease of policy specificationVSAvoidability to accommodate resource attributes

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system provides self-service capabilities through automated policy generation and resource matching. The policy engine automatically evaluates available resources against specified attributes and generates appropriate replication policies without requiring manual configuration for each scenario. This maintains ease of operation while enabling support for diverse attributes through automated attribute evaluation and policy synthesis.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The replication policy framework transitions from static location-based rules to dynamic attribute-based policies. The system can adapt policies in real-time based on changing resource attributes, availability, and specified criteria. Administrators can specify dynamic conditions (such as cost thresholds, performance requirements) and the system dynamically adjusts replication behavior accordingly, maintaining operational simplicity while increasing versatility.

Inventive Principle:

Principle #15Dynamics

3Productivity

If replication policies are generated without considering multiple resource attributes, then the policy generation process is simple, but the suitability of replicated data on target resources is reduced

Engineering Contradiction:

Improveefficiency of data replicationVSAvoidsuitability of data replication

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements feedback mechanisms where the policy engine continuously evaluates resource attributes and replication outcomes. By monitoring resource performance, availability, and attribute changes, the system provides feedback to adjust and optimize replication policies. This ensures that replication maintains both efficiency (through automated policy enforcement) and reliability (through continuous validation of resource suitability based on specified attributes).

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary evaluation of target resources against specified attributes before executing replication. By pre-assessing resource suitability based on cost, performance, security, and other attributes, the system ensures that replication only occurs to appropriate destinations. This preliminary action maintains efficiency by avoiding unsuitable replication targets while ensuring reliability through pre-validation of resource attributes.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9311374B2Replicating data objects within a storage network based on resource attributes

Publication Date: 2016.04.12 RED HAT INC

AI summary

Embodiments relate to systems and methods for replicating data from a primary resource to a secondary resource within a storage network based on resource attributes. In particular, a user can specify a policy framework comprising one or more count selections and one or more attributes. A policy generation module can determine candidate resources that match the policy framework, and order the candidate resources based on one or more factors. The policy generation module can generate a replication policy based on the ordered resources and replicate the data according to the replication policy.