Data Storage Load Balancing via Farthest Asset Placement
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Solution Overview
Problem
Conventional data storage systems face challenges in balancing scalability and availability while being overly complex and cumbersome to query, particularly when optimizing for ease of data retrieval and various querying forms.
Innovation Solution
A method for load balancing in a data storage system that creates new data storage containers on the asset farthest from existing ones to distribute data records across multiple assets, optimizing storage in sequential and finite data spaces for efficient querying and capacity management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data storage systems are configured to optimize for availability and scalability, then system reliability is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The system automatically performs load balancing by selecting data storage assets farthest from existing containers, eliminating the need for manual intervention in container placement decisions and reducing operational complexity while maintaining high availability
Solution Approach 2:
The system changes the placement parameter from random or nearest-asset selection to 'farthest asset selection' based on distance calculations, which optimizes both availability and simplifies the load balancing mechanism
2Reliability
If conventional data storage systems are configured to optimize for scalability, then system reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically manages container placement and load balancing without requiring user intervention, maintaining high availability while simplifying query operations through automated optimization
3Productivity
If data storage containers are created on assets farthest from existing containers, then load distribution is improved and scalability is enhanced, but the number of required storage assets increases
Solution Approach 1:
The system dynamically selects assets based on real-time distance calculations from existing containers, optimizing the placement of new containers to maximize load distribution efficiency and delay the need for additional assets
Solution Approach 2:
The system proactively places new containers on the farthest available assets before load imbalances occur, preventing the need for additional assets by optimizing placement decisions in advance
Data Source
AI summary
Various implementations of the invention provide load balancing in a data storage system. A computing processor receives a request to create a new data storage container on a selected one of a plurality of data storage assets, where each of the plurality of data storage assets is configured to host a plurality of data storage containers. The computing processor determines which of the plurality of data storage assets is farthest away from an existing data storage container corresponding to the new data storage container and creates the new data storage container on the data storage asset that is farthest away from the existing data storage container.