Cross-Region Data Placement for Lower Load-Balancing Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cloud-based services experience increased latency and resource consumption due to static datastore regions and eventual consistency requirements, leading to inefficient data synchronization during load balancing, especially during traffic spikes.
Innovation Solution
Offload requests to a server device in a different region for load balancing, dynamically determine the target region of the client device requesting the data, and store the generated data in the target region's datastore, rather than in the nearest datastore to the server device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in the closest datastore to the server device for load balancing, then storage efficiency is improved, but data synchronization latency increases
Solution Approach 1:
The system determines the target region of the client device before storing the generated data, and proactively stores the data in the appropriate target region's datastore. This preliminary action ensures that when the client device requests the data, it is already available in the correct location, eliminating the need to wait for synchronization from other regions.
Solution Approach 2:
The system introduces an intermediary component (the region determination mechanism) that identifies the target region and guides data placement. This intermediary enables the system to bypass the conventional approach of storing data only in the server's closest datastore and instead places it directly in the client's target region datastore, reducing synchronization latency.
2Productivity
If requests are offloaded to server devices in different regions for load balancing, then system capacity is improved, but data access latency increases
Solution Approach 1:
The system performs preliminary region determination to identify where the client device is located and stores the generated data in that specific target region's datastore. This preliminary action ensures that even though processing occurs in a different region, the data is already positioned for immediate access by the client device, eliminating access latency.
Solution Approach 2:
The system applies local quality by storing data in the specific target region's datastore that is local to the client device, rather than using a uniform approach of storing data in the server's closest datastore. This localized data placement optimizes access performance for each client device based on its specific location.
3Loss of energy
If data is stored in the nearest datastore to the server device, then bandwidth consumption is reduced, but resource consumption during synchronization increases
Solution Approach 1:
The system performs preliminary region determination and stores data directly in the target region's datastore in advance. This eliminates the need for subsequent synchronization operations, thereby avoiding the processing and memory resource consumption that would otherwise be required to replicate data across multiple regions.
Data Source
AI summary
Optimization of data synchronization latency when load balancing requests is provided. A request directed to a first server device in the first region is offloaded to a second server device in a second region that is different from the first region for load balancing. Data is generated based on processing the request by the second server device in the second region. A target region of a client device requesting the generated data is dynamically determined such that the target region is different from the second region. The generated data is stored in a datastore of the target region of the client device requesting the generated data. Thus, data is advantageously directly stored in the region(s) where clients are requesting that data without needing to wait for eventual synchronization of data to the region(s) where clients are requesting that data.