Data Store Synchronization Using Periodic Update Time Examination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Synchronizing data values across multiple data stores is challenging due to the overhead of frequent updates and the need for efficient management of update times, especially in distributed systems like cloud computing environments.
Innovation Solution
A method where a data store maintains update times for objects residing on other data stores, using a data structure to order objects by update times and periodically examining this structure to determine when to request updated versions, optimizing updates by batching requests for multiple objects with proximate update times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frequent updates are performed to synchronize data values across multiple data stores, then data consistency is improved, but network bandwidth usage and system overhead increase
Solution Approach 1:
The data store periodically examines the data structure to read update times and determines whether to request updated versions of objects. This periodic examination replaces continuous or frequent updates, reducing network bandwidth usage while maintaining data consistency through timely synchronization when updates are actually needed.
Solution Approach 2:
The system uses update times stored in the data structure as feedback to make intelligent decisions about when updates are necessary. By comparing current time against stored update times, the system determines whether objects need updating, avoiding unnecessary network traffic while ensuring data consistency is maintained when changes occur.
2Reliability
If updates are requested for all objects frequently, then data synchronization is improved, but system overhead and unnecessary updates increase
Solution Approach 1:
Instead of requesting updates for all objects frequently, the system performs partial action by selectively requesting updates only for objects whose update times indicate they need synchronization. This reduces system overhead and unnecessary updates while maintaining adequate data synchronization for objects that have actually changed.
Solution Approach 2:
The system performs preliminary action by maintaining a data structure with update times for objects before actually needing to synchronize. This advance preparation allows the periodic examination to quickly determine which objects need updates without scanning or checking all objects, reducing system overhead while ensuring synchronization occurs when needed.
3Productivity
If a data structure ordering objects by update times is maintained, then update efficiency is improved, but device complexity increases
Solution Approach 1:
The data structure is preliminarily organized by update times, allowing the system to efficiently determine which objects need synchronization without complex real-time analysis. This preliminary ordering simplifies the periodic examination process, improving update efficiency while the added complexity remains manageable through structured organization.
Data Source
AI summary
A processing system, computer program product, and methods for maintaining consistent values of objects in two or more stores. A method includes a data store associating an update time for each object of a plurality of objects, where each object of the plurality of objects resides on a respective another data store. The data store maintains a data structure ordering the plurality of objects by update times. The data store periodically examines the data structure to read update times. The data store makes a decision to request an updated version of an object belonging to the plurality of objects based on an update time of the object. The data structure can be a balanced tree.