Distributed Database Cache Priority Management
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Solution Overview
Problem
Distributed database systems in Wide Area Networks (WANs) face inefficiencies in cache management and coherence due to long distances between slave database locations, leading to adverse effects on real-time responses and continuous replication in telecommunication systems.
Innovation Solution
A method and system for handling subscriber data in a database system with a master database and multiple slave databases, where data clusters are configured with priorities, dynamically updated based on successful or unsuccessful movements, and operations are executed at either the slave or master database depending on priority, ensuring efficient replication and updating across geographically separated locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If memory caches are provided in areas closely located with requester applications to achieve fast data access, then access speed is improved, but database integrity maintenance becomes more complex due to the need to update all memory caches on transactions
Solution Approach 1:
The database system is segmented into a master database and multiple slave databases (memory caches) distributed at different locations. Each slave database serves local applications while the master database maintains the single source of truth for data integrity, dividing the management complexity across multiple independent nodes
Solution Approach 2:
The master database acts as an intermediary between applications and slave databases. It receives update requests, processes transactions, and distributes changes to relevant slave databases, thereby maintaining database integrity without requiring direct coordination between all slave caches
2Stability of the object's composition
If a centralized master database is used to maintain database integrity across distributed systems, then data consistency is improved, but system availability decreases due to single point of failure risk
Solution Approach 1:
Different roles are assigned to different database instances: the master database provides centralized control and data consistency, while slave databases provide local caching and high-speed access. This differentiation allows the system to maintain consistency through the master while achieving high availability through redundant slave instances
Solution Approach 2:
Slave databases can be independently added, removed, or replaced without affecting the master database or other slave databases. The system can discard failed slave instances and recover by promoting new ones, maintaining availability while preserving master database integrity
3Reliability
If data is replicated to multiple slave databases to improve availability and performance, then system reliability is improved, but coherence maintenance becomes more difficult due to long distances in WAN environments
Solution Approach 1:
The system dynamically determines which slave databases need to be updated based on the location and requirements of requester applications. Instead of updating all slave databases unconditionally, the master database identifies and notifies only the relevant slave databases, reducing coherence management complexity in WAN environments
Data Source
AI summary
Method and system for accessing subscriber data in a telecommunication system, and providing a database system with a master database and slave databases acting as memory caches located with requester applications. The method including: configuring data clusters at the master database, each data cluster identifying subscriber data associated with an operation and assigned a priority; determining at the master database the priority of the data cluster associated with a received operation; and either providing the data cluster associated with the operation from the master database towards the slave database, replicating the received data cluster at the slave database, and executing the operation with the received data cluster at the slave database, where the priority of the data cluster is higher than for previous operations; or executing the operation with the data cluster at the master database, where the priority of the data cluster is lower than for a previous operation.