Virtual Meeting Performance Pattern Analysis for Resource Diagnosis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large-scale communication systems face challenges in diagnosing transient down-layer performance issues, as existing methods struggle to efficiently identify resource-related problems during virtual meetings, leading to quality degradation and high costs due to over-provisioning or under-provisioning of resources.
Innovation Solution
A method that retrieves time-based performance patterns of virtual meetings, determines attributes associated with poor performance, and establishes a performance relationship between these attributes and resources, generalizing the findings to overall non-meeting-specific resource performance for proactive troubleshooting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If administrators provision resources for maximum possible usage, then system reliability is improved, but resource cost increases
Solution Approach 1:
The system performs preliminary analysis of performance patterns and resource usage trends before problems occur. By retrieving and analyzing time-based performance patterns of virtual meetings, the system proactively identifies resources that are likely to experience issues, allowing administrators to optimize resource allocation in advance rather than over-provisioning for all possible scenarios.
Solution Approach 2:
The system dynamically adjusts resource allocation based on changing performance parameters and usage patterns. By monitoring virtual-meeting attributes and their relationship to resource performance, the system can optimize resource parameters (such as bandwidth, processing power, memory) based on actual demand patterns rather than static maximum provisioning.
2Reliability
If administrators provision resources for maximum possible usage, then quality of service is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The system implements dynamic resource allocation that adapts to changing virtual meeting patterns and performance requirements. By continuously analyzing performance patterns and virtual-meeting attributes, the system adjusts resource allocation in real-time to match actual demand, ensuring high quality of service during peak demands while improving overall resource utilization efficiency during lower-demand periods.
3Ease of operation
If existing diagnostic methods are used, then implementation simplicity is maintained, but ability to detect transient performance issues deteriorates
Solution Approach 1:
The system implements a feedback mechanism that retrieves performance patterns from virtual meetings and uses this feedback to identify transient performance issues. By analyzing the relationship between virtual-meeting attributes and resource performance, the system detects subtle patterns that indicate emerging problems, improving detection capability while maintaining automated operation that preserves ease of use.
4Quantity of substance
If resource allocation is optimized based on actual usage, then resource cost is reduced, but system complexity increases
Solution Approach 1:
The system implements self-service automation where the diagnostic and analysis processes operate autonomously without requiring complex manual configuration. The system automatically retrieves performance patterns, analyzes virtual-meeting attributes, and generates diagnostic information, reducing the perceived complexity for administrators while enabling sophisticated resource optimization that reduces costs.
Data Source
AI summary
In one embodiment, a method includes retrieving a time-based performance pattern of virtual meetings previously mediated by a communications platform executing in a computing environment, wherein the computing environment comprises a plurality of resources. The method further includes determining, from the time-based performance pattern, at least one virtual-meeting attribute associated with relatively poor virtual-meeting performance. Also, the method includes determining a performance relationship between the at least one virtual-meeting attribute and a particular resource of the computing environment. In addition, the method includes generalizing the performance relationship to overall, non-meeting-specific performance of the particular resource.