Live Origin Storage for Immutable Caching and Low-Latency Reads
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Solution Overview
Problem
Conventional live origin servers are not optimized for live streaming, leading to slow read requests due to the lack of strong read after write consistency, high latency from single cloud region operation, and inefficient deletion of small media content item segments.
Innovation Solution
Implement a distributed datastore with selective consistency support for mutable and immutable data, caching immutable data for faster access, and using multi-cloud region awareness to handle network jitter and optimize storage utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional live origin servers implement strong read after write consistency, then data accuracy is improved, but read request processing speed deteriorates
Solution Approach 1:
The patent segments data into mutable and immutable categories, applying different consistency strategies to each. Immutable data segments are cached with strong consistency guarantees, while mutable data uses eventual consistency, thereby improving read speed for immutable data without sacrificing data accuracy where needed.
Solution Approach 2:
The patent implements local quality by applying strong read after write consistency selectively to immutable data segments that require it, rather than uniformly to all data. This allows the system to maintain data accuracy for critical immutable segments while improving overall read performance by not enforcing strong consistency on mutable data.
2Device complexity
If conventional live origin servers operate in a single cloud region, then system complexity is reduced, but latency increases due to network jitter
Solution Approach 1:
The patent extends the system from a single cloud region to multiple cloud regions, adding a geographic dimension to the architecture. This allows the system to replicate data across regions and select optimal regions for read operations, thereby reducing latency caused by network jitter without significantly increasing system complexity through standardized replication mechanisms.
3Reliability
If publishing servers write small media content item segments with high frequency, then content freshness is improved, but write request throughput deteriorates due to throttling
Solution Approach 1:
The patent uses copying by replicating immutable data segments to cache layers and multiple cloud regions. This allows the primary write path to complete quickly without waiting for all replication operations, improving write throughput while maintaining content freshness through asynchronous replication to cache and secondary regions.
4Reliability
If conventional live origin servers store all data versions in distributed storage, then data completeness is improved, but deletion time deteriorates
Solution Approach 1:
The patent extracts immutable data segments from the main distributed storage system and places them in a specialized cache layer. This separation allows for faster deletion operations on the cache layer while maintaining data completeness through the persistence of immutable segments in the underlying distributed storage system.
Data Source
AI summary
One embodiment of a method for storing data includes determining whether first data to be stored is mutable data that can be modified or immutable data that is not modified, in response to determining that the first data is mutable data, storing the first data in a datastore, and in response to determining that the first data is immutable data, storing the first data in the datastore and in a cache.