Entity Identifier Synchronization Prioritization Protocol
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Solution Overview
Problem
Synchronization of entity identifiers across multiple data centers becomes costly and inefficient due to the high frequency of updates in large-scale systems, with existing methods failing to prioritize data changes effectively.
Innovation Solution
Implementing a prioritization protocol that assesses data changes based on factors such as the quantity and type of data changed, subscription status across data centers, and update frequency, allowing for immediate or near-immediate synchronization of high-priority updates while batching lower-priority changes, and dynamically sorting synchronization tasks in a queue based on scoring systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data updates are synchronized immediately across data centers, then data consistency is improved, but synchronization cost and system latency increase
Solution Approach 1:
The patent changes the parameter of synchronization timing from immediate to delayed based on priority levels. High-priority updates are synchronized immediately while low-priority updates are deferred to batch processing, reducing overall synchronization cost while maintaining data consistency for critical data
Solution Approach 2:
The patent segments data updates into different priority levels (high, medium, low) and applies different synchronization strategies to each segment. This segmentation allows the system to maintain consistency for important data while reducing costs for less critical data
2Reliability
If all data updates are synchronized immediately across data centers, then data consistency is improved, but system latency increases
Solution Approach 1:
The patent changes the timing parameter of synchronization based on data priority. High-priority data undergoes immediate synchronization with minimal latency, while low-priority data is batched for later synchronization, reducing overall system latency while maintaining consistency for critical updates
3Productivity
If data synchronization is prioritized by assessing data changes, then synchronization efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces priority parameters and scoring mechanisms to evaluate data changes. By assigning priority levels and scores to different types of data modifications, the system can efficiently determine synchronization timing without requiring complex decision-making logic
Solution Approach 2:
The patent performs preliminary assessment of data changes by evaluating their priority and impact before triggering synchronization. This preliminary action includes checking data types, modification depths, and priority levels to determine whether immediate or batched synchronization is appropriate
Data Source
AI summary
The present disclosure relates to synchronizing entity identifiers across multiple data centers. In some embodiments, an entity identifier translation server may be deployed within a cloud-based distributed environment. The entity identifier translation server may receive data from multiple different data centers and detect changes/updates to entity identifiers within the data centers. In response to detected changes, the entity identifier translation server may identify one or more corresponding entity identifiers within the other data centers. For each of the corresponding entity identifiers within the other data centers, the entity identifier translation server may determine whether or not the corresponding entity identifier is to be synchronized with the newly-changed entity identifier in the first data center, and if so, may initiate synchronization processes.