Dynamic Resource Allocation for Video Streaming Workloads
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Solution Overview
Problem
Distributed network-based data storage systems face challenges in providing reliable and cost-effective video streaming services due to dynamic real-time resource allocation issues, which are characterized as NP complete problems, leading to computationally expensive and undesirable results with conventional approaches.
Innovation Solution
A computer-implemented method that detects actual workloads and compares them to prescriptive workloads, revising the latter based on the former to optimize resource allocation in a distributed system by modifying resource allocation arrangements, including storage and access resources, to reflect actual usage patterns and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches are used to solve NP complete resource allocation problems, then deterministic solutions can be obtained, but computational expense increases and results become undesirable
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring actual workload and comparing it against prescriptive workload models. The system dynamically adjusts resource allocation arrangements based on real-time deviations, transitioning from static deterministic solutions to adaptive dynamic optimization that balances computational efficiency with reliable resource distribution.
Solution Approach 2:
The system establishes a feedback loop where actual workload is detected, compared against prescriptive models, and used to revise allocation arrangements. This feedback mechanism allows the system to learn from actual usage patterns and continuously improve resource allocation without requiring exhaustive computational searches, thereby reducing computational expense while maintaining solution quality.
2Productivity
If resource allocation is optimized to match actual workload, then resource utilization improves, but system complexity increases
Solution Approach 1:
The patent segments the resource allocation problem into discrete prescriptive workload categories, each associated with specific resource allocation arrangements. This segmentation allows the system to manage complexity by handling each category separately based on its actual workload, improving overall resource utilization while keeping the management process organized and controllable.
Solution Approach 2:
The system revises prescriptive workload parameters (such as resource capacity levels, allocation ratios, and distribution patterns) based on actual workload detection. By dynamically adjusting these parameters rather than using fixed complex algorithms, the system achieves improved resource utilization with manageable complexity, as parameter changes are simpler to implement than fundamental algorithmic redesigns.
Data Source
AI summary
A computer-implemented method includes detecting an actual workload representative of a pattern of access of a plurality of items of content; comparing the actual workload against a prescriptive workload to determine an occurrence of a substantial deviation from the prescriptive workload; and upon determining the occurrence of the substantial deviation, revising the prescriptive workload based at least in part on the actual workload. The plurality of items is stored on resources of a storage environment according to one of a plurality of resource allocation arrangements. The prescriptive workload including a plurality of categories, each category being associated with a respective one of the plurality of resource allocation arrangements.