Storage Modules With Independent Scheduling Queues For Video Streaming
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Solution Overview
Problem
Current data storage systems, particularly RAID systems, face limitations in scalability and reliability when handling high-bandwidth video streaming due to mechanical constraints and the need for large disk arrays, which increase latency and reduce mean-time-to-failure, while also being inefficient in content distribution and load balancing.
Innovation Solution
A method and system that utilize a plurality of storage modules with independent scheduling queues to asynchronously manage data file requests, allowing for efficient streaming of multimedia content by determining start locations and queue positions based on capacity and transmission rates, enabling simultaneous streaming of multiple content files with reduced latency and increased reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of disks in a RAID array is increased to increase bandwidth, then the bandwidth of the storage system increases proportionally, but the reliability decreases as the mean-time-to-failure becomes shorter
Solution Approach 1:
The system divides the storage system into multiple independent storage modules, each with its own scheduling queue. This segmentation allows each module to operate independently, maintaining reliability while achieving high bandwidth through parallel operation of multiple modules.
Solution Approach 2:
The patent transitions from a single centralized queue to multiple independent scheduling queues distributed across storage modules. This dimensional change from 1D (single queue) to 2D (multiple queues across modules) architecture enables simultaneous data retrieval from multiple modules without the reliability penalties of increasing disks in a single array.
2Productivity
If a large RAID array is used to satisfy high streaming bandwidth requirements, then the bandwidth capacity increases, but the system complexity and centralized control requirements increase
Solution Approach 1:
The storage system is segmented into multiple independent storage modules, each managing its own scheduling queue. This distributes the control logic and reduces centralized complexity while maintaining high streaming bandwidth capacity through parallel operation of modules.
Solution Approach 2:
Each storage module autonomously manages its own scheduling queue and data retrieval operations without requiring centralized coordination. This self-service approach simplifies system complexity by eliminating the need for a complex centralized controller while maintaining high bandwidth capacity.
3Productivity
If traditional RAID striping is used for content distribution, then bandwidth is increased through parallel access, but content replication increases storage requirements
Solution Approach 1:
The system segments content into parts distributed across multiple storage modules, with each module maintaining its own scheduling queue. This enables parallel bandwidth access without requiring full replication of content across all modules, as each module holds a segment that can be independently retrieved.
Data Source
AI summary
In one example, multimedia content is requested from a plurality of storage modules. Each storage module retrieves the requested parts, which are typically stored on a plurality of storage devices at each storage module. Each storage module determines independently when to retrieve the requested parts of the data file from storage and transmits those parts from storage to a data queue. Based on a capacity of a delivery module and/or the data rate associated with the request, each storage module transmits the parts of the data file to the delivery module. The delivery module generates a sequenced data segment from the parts of the data file received from the plurality of storage modules and transmits the sequenced data segment to the requester.