Geopartitioned Data Caching for Latency Reduction
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Solution Overview
Problem
Existing content delivery systems face latency and bandwidth bottlenecks, particularly in scenarios involving network accessible devices, such as advertisements and alerts, where rapid and reliable data access is crucial for user experience and infrastructure resilience, especially during natural disasters.
Innovation Solution
Implementing a geopartitioned data caching system that leverages geolocation data and behavioral characteristics to store and retrieve data locally, reducing latency by caching user profiles near the user's geographical region and rerouting traffic to unaffected areas during disasters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored centrally in a single location, then data management is simplified, but network latency increases and reliability decreases during disasters
Solution Approach 1:
The patent segments the centralized data storage system into multiple geographically distributed data caches. Each cache stores copies of data in different geographical regions, allowing users to access data from the nearest cache location. This segmentation reduces network latency while maintaining data availability and system reliability even if one cache fails or is affected by a disaster.
Solution Approach 2:
The patent introduces a geographical dimension to data storage by distributing caches across multiple locations. Instead of a single-point storage model, the system creates a spatial distribution architecture where data exists across multiple dimensional coordinates (geographical locations), enabling both low-latency local access and high reliability through redundancy.
2Loss of time
If data is cached geographically distributed, then network latency is reduced, but system complexity increases
Solution Approach 1:
The patent creates a universal data cache architecture where each geographically distributed cache serves multiple functions: local data storage, rapid data access, and disaster recovery. This multi-functionality reduces the need for separate systems for each purpose, thereby managing complexity while achieving low latency and high reliability simultaneously.
Solution Approach 2:
The system uses copying to distribute data across multiple geographical caches rather than creating complex point-to-point connections. Each cache contains copies of the data, simplifying the architecture by using identical replicated units rather than complex interconnected systems, thereby reducing overall system complexity while maintaining performance benefits.
3Reliability
If data is accessed from remote data source, then data consistency is maintained, but bandwidth usage increases
Solution Approach 1:
The patent applies preliminary action by pre-caching data from the central data source to multiple geographically distributed caches before users need to access it. This advance preparation reduces the bandwidth required during actual data access operations, as users retrieve data from local caches rather than continuously streaming from the remote source, while data consistency is maintained through periodic synchronization.
Data Source
AI summary
Geopartitioned data caching is disclosed. For example, a data source is connected over a network to a geographically remote data cache in communication with a load balancer service. A processor on the data cache executes to receive, from the data source, a plurality of data entries in the data cache, where the plurality of data entries is selected based on a geographical region of the data cache. A data request for a data entry of the plurality of data entries is received from the load balancer service, where a requestor of the data request is in a second geographical region proximately located with the data cache. The data entry is sent to the load balancer service, where the load balancer service forwards the data entry to a receiver.