Device-ID Hashing for Multi-Data-Center Data Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data replication schemes in networks result in inconsistent data availability across data centers, leading to infrastructure and scalability issues due to the time required for replication and the need to designate a single primary data center, which limits performance and flexibility.
Innovation Solution
Data is segregated and stored in multiple data centers based on unique information, such as device IDs or IP addresses, using hashing algorithms to generate group identifiers, allowing data to be routed to the appropriate center for efficient access and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is replicated from a primary data center to a secondary data center, then data availability and backup are improved, but data consistency and access performance deteriorate due to replication time delays
Solution Approach 1:
The patent segments data into different groups based on unique identifiers (device IDs, IP addresses) and distributes different data groups to different data centers using hashing algorithms. This eliminates the need for full data replication across all data centers, allowing each data center to store and serve specific data segments independently, thereby eliminating replication time delays while maintaining data availability.
Solution Approach 2:
The patent implements local quality by making each data center specialized in storing and serving specific data segments rather than maintaining complete copies of all data. Each data center becomes optimized for its assigned data segments, improving access performance for those segments while maintaining overall system reliability through distributed storage across multiple specialized centers.
2Stability of the object's composition
If a single primary data center is designated, then data consistency is maintained, but system scalability and flexibility deteriorate
Solution Approach 1:
The patent makes multiple data centers simultaneously functional as primary data centers for their respective data segments. Each data center can independently serve as the primary source for its assigned data segments, eliminating the single-point limitation and enabling the system to scale by adding more data centers without compromising data consistency or requiring complex replication hierarchies.
3Device complexity
If data is stored in a single primary data center, then infrastructure complexity is reduced, but system capacity and performance deteriorate
Solution Approach 1:
The patent applies segmentation by dividing data into distinct groups and distributing them across multiple data centers using hashing algorithms based on unique identifiers. This approach increases total system capacity by utilizing multiple data centers in parallel while maintaining relatively simple infrastructure through automated, algorithm-based distribution that eliminates complex manual configuration and replication management.
Data Source
AI summary
Systems and methods are provided for distributing data to multiple data centers within a network based on unique information associated with the data. One example computer-implemented method includes receiving a request, from a service provider, for data stored at a data center and generating a group identifier based on the device ID specific to a device of a user. The method also includes identifying the data center based on the first group identifier and directing the request to the identified data center. The method then includes retrieving the data from the data center and returning the retrieved data to the service provider, in response to the request.