Object-Based Storage Commands with QoS Identifiers
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Solution Overview
Problem
Current data storage systems lack efficient methods for managing data operations with varying quality of service requirements, leading to suboptimal performance and reliability in handling commands across distributed networks.
Innovation Solution
The implementation of object-based commands with quality of service identifiers, which allow for flexible data storage and retrieval operations by using objects with variable-size data containers, incorporating quality of service identifiers to specify service levels for operations such as Put, Get, and Delete, enabling tailored performance and reliability settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data storage systems use fixed-size data containers and uniform service levels, then system complexity is reduced, but adaptability to varying quality of service requirements deteriorates
Solution Approach 1:
The patent implements dynamic data containers with variable sizes that can be adjusted based on quality of service requirements. Objects are allocated different amounts of storage space and service levels depending on their QoS identifiers, allowing the system to adapt to varying performance and reliability needs without requiring completely different storage structures for each scenario.
Solution Approach 2:
The system changes key parameters including data container size, service level priority, and reliability settings based on quality of service identifiers. By varying these parameters dynamically according to QoS requirements, the system achieves adaptability while maintaining a unified object-based structure that doesn't excessively increase complexity.
2Reliability
If data storage systems implement customized service levels for different operations, then quality of service varies by operation type, but device complexity increases
Solution Approach 1:
The patent applies local quality by assigning different service levels and reliability settings to specific objects or data containers based on their QoS identifiers. Rather than implementing complex global service level management, the system tailors service quality locally to each object's requirements, allowing customized reliability and performance for critical data while using standard service for less important data.
Solution Approach 2:
The unified object-based storage system performs multiple functions by handling different QoS requirements through a single framework. The same object structure supports varying service levels, reliability settings, and performance characteristics, eliminating the need for separate specialized systems for different data types while maintaining system simplicity.
3Adaptability or versatility
If data storage systems use variable-size data containers, then adaptability to different data types improves, but device complexity increases
Solution Approach 1:
The system employs dynamic data containers that can change size based on the data being stored and the QoS requirements. Objects are allocated variable storage space within a unified container structure, allowing flexible accommodation of different data types and sizes without requiring multiple specialized container formats or complex management overhead.
Data Source
AI summary
Systems and methods are disclosed for object-based commands with quality of service identifiers. In an embodiment, an apparatus may comprise a memory device having a processor configured to store data as objects, each object including an object identifier field to track the object, and a user data field for user data of the object. The processor may be further configured to receive a command including an operation directed to an object, and a quality of service identifier that specifies a level of service associated with the operation. Commands may be directed toward put, get, and delete operations, among others.