Unified Communication Monitoring for Endpoint Connectivity Diagnosis
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Solution Overview
Problem
The complexity and hybrid nature of unified communications (UC) systems, integrating voice, video, chat, and email, make it challenging to identify and troubleshoot issues efficiently, leading to noticeable disruptions and increased troubleshooting time, especially in remote work environments, with companies facing difficulties in balancing reliability, cost-effectiveness, and user experience.
Innovation Solution
A unified communication monitoring system that collects real-time data, correlates it with a monitoring dataset, and uses a virtual model to mimic UC system functions, enabling quick identification of issues such as unregistered endpoints and connectivity problems, while reducing the need for extensive logging and costly raw log technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unified communication systems integrate multiple cloud and on-premise services, then functionality and versatility improve, but system complexity and troubleshooting difficulty increase
Solution Approach 1:
The monitoring system segments the complex UC environment into discrete monitorable entities including endpoints, services, connections, and events. Each component is tracked independently through structured data models, allowing the system to manage complexity by breaking down the monolithic UC architecture into manageable segments that can be monitored and diagnosed individually.
Solution Approach 2:
The patent introduces a monitoring system as an intermediary layer between the UC components and users. This intermediary collects, correlates, and presents information about system state without requiring users to directly interact with or understand the underlying complex UC infrastructure. The monitoring system mediates between the complex multi-cloud/on-premise environment and the end users, simplifying their view while maintaining full functionality.
2Loss of time
If real-time monitoring data is collected from all UC components, then issue identification speed improves, but data processing overhead and costs increase
Solution Approach 1:
The monitoring system implements partial monitoring by focusing on critical UC components and events rather than attempting to monitor every aspect of the system in equal detail. It collects data selectively based on predefined monitoring templates that target the most impactful metrics for troubleshooting, avoiding the excessive overhead of comprehensive full-system monitoring while still enabling rapid issue identification.
Solution Approach 2:
The patent extracts only the essential monitoring data needed for effective troubleshooting from the broader UC system data stream. By taking out and focusing on specific critical parameters and events rather than processing all available data, the system reduces processing overhead while maintaining the ability to quickly identify and respond to issues.
3Measurement precision
If detailed connectivity history is maintained with high granularity, then diagnostic precision improves, but storage requirements and system resource consumption increase
Solution Approach 1:
The monitoring system applies local quality by maintaining different levels of data granularity in different contexts. Critical diagnostic information is stored with high granularity for precise analysis, while less critical historical data is aggregated or summarized. This allows the system to provide detailed diagnostic precision where needed while reducing overall storage requirements through selective detail retention.
Solution Approach 2:
The system maintains detailed connectivity history selectively rather than uniformly across all time periods and all system components. High-granularity data is retained for recent or critical events where diagnostic precision is most valuable, while older or less critical data is aggregated or archived at lower granularity, balancing diagnostic needs with storage constraints.
Data Source
AI summary
In a system and a method for unified communication monitoring, collecting, by a processor, a real time data of a unified communication system and correlating, by the processor, the real time data with a monitoring dataset, wherein the monitoring dataset uses a collection engine. Furthermore, linking, by the processor, the monitoring dataset with a model data, wherein the model data represents a current state and a configuration of the unified communication system and presenting, by the processor, a status of a service level object based on the monitoring dataset and the model data.