Pervasive Data Center Architecture for Distributed Data Gravity
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Solution Overview
Problem
Existing data management systems face challenges in addressing data gravity, which leads to unfavorable complexity, increased costs, security concerns, and regulatory barriers due to centralized data storage, making it difficult to move data across geographical locations and maintain compliance.
Innovation Solution
A data gravity analytics system that calculates a Data Gravity index score using data mass, activity, bandwidth, and latency to optimize data storage and distribution, recommending adjustments and migrations through automated tools and machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If centralized data storage is used, then data management simplicity is improved, but data gravity complexity and migration difficulty increase
Solution Approach 1:
The patent segments data storage across multiple geographic locations and platforms rather than centralizing it. The system divides data into distributed components that can be independently managed, reducing data gravity complexity while maintaining operational simplicity through the unified analytics interface.
Solution Approach 2:
The patent adds a new dimension to data management by introducing geographic and platform distribution as organizational axes. Instead of managing data along a single centralized-distributed spectrum, the system operates across multiple dimensions including location, platform type, and data characteristics, thereby reducing the complexity of data gravity.
2Adaptability or versatility
If data is distributed across multiple locations, then data mobility is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal data gravity analytics system that functions across multiple platforms and geographic locations simultaneously. The unified analytics interface provides multi-functional capabilities to manage distributed data without requiring separate systems for each location, thereby maintaining data mobility while controlling system complexity.
Solution Approach 2:
The patent introduces a data gravity analytics system as an intermediary layer between distributed data stores and users. This mediator handles the complexity of data distribution, location tracking, and migration analysis, allowing users to benefit from data mobility without directly managing the underlying system complexity.
3Ease of operation
If centralized data storage is used, then security management is simplified, but security risks and compliance costs increase
Solution Approach 1:
The patent applies local quality by allowing different security measures to be implemented at different geographic locations and platforms based on specific risk profiles. Rather than enforcing uniform security policies, the system enables localized security adaptations while maintaining overall compliance through centralized analytics and reporting.
4Reliability
If data is moved across geographical locations, then regulatory compliance is improved, but migration complexity and costs increase
Solution Approach 1:
The patent performs preliminary actions by calculating data gravity indices and analyzing migration pathways before actual data movement occurs. The system pre-identifies optimal migration routes, estimates costs, and prepares compliance documentation in advance, thereby reducing the complexity and risks associated with actual data migration execution.
Data Source
AI summary
Embodiments of a system for determining a data gravity index score and implementing pervasive data center architecture is disclosed. In some embodiments, the system can calculate a data gravity index score based on the amount of data stored in a given location, an amount of data in motion in the given location, a bandwidth index associated with the given location, and a latency index associated with the given location. Based on data gravity index scores, in some embodiments, the system can localize traffic to improve network performance, improve security operations, and generate software-defined-network overlay.