Streaming Media Server Capacity Planning System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Streaming media service providers face difficulties in evaluating the capacity of media server configurations to support expected workloads, leading to challenges in determining the most cost-effective configuration that can maintain desired service quality, especially during non-compliant periods and node failures.
Innovation Solution
A capacity planning system that receives workload information and service parameters to determine the number of servers needed for a given configuration, using interval analysis and performability parameters to ensure compliance with service characteristics, including Statistical Demand Guarantees and Utilization Constraints, and Regular-Mode and Node-Failure-Mode Overload Constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If media server configuration capacity is increased to support higher workloads, then service availability and reliability improve, but system cost and complexity increase
Solution Approach 1:
The patent applies preliminary action by performing capacity evaluation and analysis before deploying the media server configuration. The system evaluates workload characteristics, analyzes service parameters, and determines optimal configuration settings in advance, allowing providers to select configurations that ensure service availability without unnecessarily increasing system complexity and cost.
2Device complexity
If media server configuration is optimized for cost-effectiveness, then system cost decreases, but service quality and reliability during peak loads may deteriorate
Solution Approach 1:
The patent applies parameter changes by systematically evaluating multiple configuration parameters (such as buffer sizes, thread counts, cache settings) and adjusting them to find the optimal balance point. The capacity evaluation tool analyzes how different parameter combinations affect both cost and service quality, enabling selection of configurations that maintain acceptable service quality during peak loads while minimizing system cost.
3Manufacturing precision
If detailed service parameters are enforced to maintain quality of service, then service quality compliance improves, but system complexity and configuration difficulty increase
Solution Approach 1:
The patent applies self-service by implementing automatic evaluation and determination mechanisms that reduce manual configuration effort. The capacity evaluation tool automatically analyzes workload characteristics, checks compliance with service parameters, and determines optimal configuration settings without requiring extensive manual intervention, thereby maintaining service quality compliance while reducing configuration complexity.
4Measurement precision
If capacity evaluation is performed for multiple server configurations, then optimal configuration selection improves, but evaluation time and computational resources increase
Solution Approach 1:
The patent applies partial or excessive action by implementing a tiered evaluation approach. The system performs comprehensive capacity evaluation for configurations that are most likely to be optimal based on preliminary analysis, while using simplified evaluation methods for less promising configurations. This approach maintains sufficient evaluation accuracy to identify optimal configurations while significantly reducing the total evaluation time and computational resources required.
Data Source
AI summary
According to at least one embodiment, a method comprises receiving, into a capacity planning system, workload information representing an expected workload of client accesses of streaming media files from a site. The method further comprises receiving, into the capacity planning system, at least one service parameter that defines a desired service characteristic to be provided by a media server configuration under the expected workload. The method further comprises determining, by the capacity planning system, for at least one server configuration, how many servers of the at least one server configuration to be included at the site for supporting the expected workload in compliance with the at least one service parameter.


