Data Sharding Model for Storage Efficiency in Information Handling Systems
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Solution Overview
Problem
Computing devices face inefficiencies in storing data due to hardware components being unavailable or incapable of storing data, leading to inefficiencies in composed information handling systems.
Innovation Solution
Implementing a data sharding model using telemetry data to identify optimal storage locations based on availability, capability, and proximity, with an enhanced networking interface that performs preferential writes of data to the most capable storage resources, reducing network congestion and improving storage efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in composed information handling systems using available hardware components, then storage capacity is increased, but storage efficiency deteriorates due to hardware unavailability or incapability
Solution Approach 1:
The patent introduces a data sharding model as an intermediary layer between the application and the distributed storage resources. This model analyzes telemetry data from multiple information handling systems to identify optimal storage locations based on hardware availability, capability, and proximity, thereby mediating the data placement decision to improve storage efficiency while utilizing available capacity
Solution Approach 2:
The system dynamically changes storage parameters by selecting different storage locations based on real-time telemetry data. The data sharding model evaluates multiple parameters including hardware availability, storage capability, and network proximity to determine the optimal destination for each data shard, thereby adapting to changing system conditions to maintain high storage efficiency
2Reliability
If data is distributed across multiple storage locations, then storage reliability is improved, but network congestion increases due to additional data transmission
Solution Approach 1:
The data sharding model applies local quality by selecting storage locations based on their specific characteristics and proximity to the data source. By analyzing telemetry data about each potential storage location's capability and proximity, the system directs data to the most appropriate local resource, thereby distributing data for reliability while minimizing network transmission distance and congestion
3Device complexity
If traditional storage methods are used without data sharding analysis, then system complexity is reduced, but storage efficiency deteriorates due to inability to identify optimal storage locations
Solution Approach 1:
The system implements self-service by having the data sharding model automatically analyze telemetry data and make intelligent storage decisions without requiring complex external management. The model autonomously evaluates hardware capabilities, availability, and proximity to determine optimal storage locations, thereby improving storage efficiency while keeping the system relatively simple through automated decision-making
Data Source
AI summary
A system for managing storage of data in a information handling systems includes a first information handling system, and a specialized information handling system comprising an enhanced networking interface, wherein the enhanced networking interface is programmed to: obtain data to be processed by the system, perform a data sharding analysis using telemetry data to identify the first information handling system, and transmit the data to the first information handling system based on the identifying.