Cloud Database Zone Identifier Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In cloud computing systems with multiple deployment zones, data replication across zones leads to duplicated operations and resource consumption, while eliminating replication results in data inconsistencies and reduced reliability.
Innovation Solution
A system that writes data to a database in each cloud deployment zone with a deployment zone identifier, allowing cloud resources to perform operations only on data originating from the same zone, thereby filtering out replicated data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data replication is performed across multiple cloud deployment zones, then reliability and redundancy are improved, but processing resources and network bandwidth are consumed due to duplicate operations
Solution Approach 1:
The patent extracts the deployment zone identifier from the data metadata to enable filtering of replicated data. By taking out this identifying feature, the system can distinguish between original and replicated data, allowing cloud resources to process only necessary data and avoid redundant operations across deployment zones.
Solution Approach 2:
The deployment zone identifier acts as an intermediary mechanism that mediates between data replication for reliability and resource consumption. This identifier enables the system to maintain replicated data for consistency while simultaneously allowing resources to identify and skip redundant processing, thus mediating the contradiction between reliability and energy loss.
2Reliability
If data replication is performed across multiple cloud deployment zones, then redundancy is improved, but network bandwidth is consumed due to duplicate data transmission
Solution Approach 1:
The system extracts deployment zone identifiers from data metadata to enable intelligent routing and filtering. This extraction allows the network to recognize replicated data and avoid redundant transmissions, reducing network bandwidth consumption while maintaining the redundancy benefits of multi-zone deployment.
Solution Approach 2:
The deployment zone identifier serves as a network intermediary that enables efficient data routing. By including this identifier in data metadata, the system allows network resources to distinguish between original and replicated data transmissions, thereby maintaining redundancy while minimizing unnecessary network bandwidth consumption.
3Reliability
If cloud resources perform operations on all replicated data, then data consistency is maintained, but processing time increases due to duplicate operations
Solution Approach 1:
The patent extracts deployment zone identifiers to enable rapid identification and filtering of replicated data. This extraction allows cloud resources to quickly distinguish between original and replicated data, maintaining data consistency through selective processing while significantly reducing the time spent on duplicate operations.
Solution Approach 2:
The deployment zone identifier acts as a processing intermediary that enables cloud resources to make quick decisions about data processing. By using this identifier, the system maintains data consistency across zones while avoiding the time penalty of processing duplicate data, as resources can efficiently identify and skip replicated entries.
4Reliability
If multiple copies of applications execute in different cloud deployment zones, then service availability is improved, but resource consumption increases due to duplicated processing
Solution Approach 1:
The system extracts deployment zone identifiers from data to enable cloud resources to identify and process only relevant data from their local zone. This extraction allows multiple application copies to run in different zones for availability while reducing overall cloud resource consumption by eliminating redundant processing of replicated data.
Solution Approach 2:
The deployment zone identifier serves as a mediator between service availability and resource consumption. It enables the system to maintain multiple application copies across zones for high availability while simultaneously allowing resources to filter and process only necessary data, thus mediating the contradiction between reliability and energy loss.
Data Source
AI summary
In some implementations, a cloud system may obtain data via a copy of an application executing in a first cloud deployment zone of the multiple cloud deployment zones, wherein the application has copies executing in respective cloud deployment zones of the multiple cloud deployment zones. The cloud system may store, in a database executing in the first cloud deployment zone, the data with a deployment zone identifier that indicates the first cloud deployment zone, where the multiple cloud deployment zones include respective databases of multiple databases including the database. The cloud system may perform, via a cloud resource in the first cloud deployment zone, an operation using the data based on the data including the deployment zone identifier that indicates the first cloud deployment zone and based on the cloud resource being in the first cloud deployment zone.