Distributed Information Storage System Using Dynamic Assignment
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Solution Overview
Problem
Conventional distributed databases experience reduced write performance due to the need to duplicate and transmit data between information storage devices, which is inefficient and can compromise fault tolerance and scalability, especially in IoT systems with numerous small data transmissions.
Innovation Solution
A distributed information storage system where each information storage device autonomously acquires and stores data based on shared correspondence tables, eliminating the need for data duplication and transmission between devices, while ensuring data redundancy and scalability through dynamic assignment and monitoring of information reception devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is duplicated and transmitted between information storage devices to ensure data redundancy, then fault tolerance is improved, but write performance deteriorates
Solution Approach 1:
The system segments the data distribution task by assigning different data types to different information storage devices based on the correspondence tables. Each device independently stores data relevant to its assigned reception devices, eliminating the need for one device to duplicate and transmit data to multiple other devices. This segmentation resolves the contradiction by maintaining fault tolerance through distributed storage while improving write performance through parallel, independent data acquisition.
2Reliability
If data is duplicated and transmitted between information storage devices, then data redundancy is ensured, but system complexity increases
Solution Approach 1:
The correspondence tables are established in advance before data storage operations begin. These tables predefine which information storage devices are responsible for which data types and which reception devices should receive which data. This preliminary configuration eliminates the need for complex real-time data duplication and transmission logic during operation, thereby ensuring data redundancy while reducing system complexity.
3Reliability
If a distributed database stores the same data in multiple information storage devices, then fault tolerance is achieved, but scalability is compromised
Solution Approach 1:
The system dynamically assigns data types to information storage devices based on the correspondence tables, which can be flexibly configured as the system scales. When new devices are added, they can be assigned specific data types and reception devices through the correspondence tables without requiring a complete reconfiguration of the distributed storage architecture. This dynamic assignment mechanism maintains fault tolerance while enabling scalable system expansion.
Data Source
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AI summary
Data transmitted from an information transmission device can be stored in a distributed manner, without the need to duplicate or transmit/receive data among information storage devices. Under the control of a data write unit, end points to be assigned are determined in each of the information storage devices, based on the preset information indicating a correspondence between the information storage devices and end points assigned to the information storage devices. The data transmitted together with the identifier corresponding to the assigned end point is acquired from among the data transmitted from the information transmission devices, based on a first correspondence table stored in a shared setting storage unit for associating the end points with the identifiers of the types of data acquired by the end points, and the acquired data is stored in the data storage unit. Under the control of the correspondence updating unit, the correspondence with the assigned end point is entered into the second correspondence table that is stored in the shared setting storage unit.