Intelligent VoIP Call Routing via Decentralized Quality Monitoring
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Solution Overview
Problem
Existing VoIP and VioIP systems face challenges in call routing, including cost inefficiencies and quality issues such as packet loss, delay, and jitter, which affect user experience and are difficult to diagnose due to the complexity of endpoint devices and network connections.
Innovation Solution
A system where endpoint devices monitor call quality factors and send data to a centralized server for analysis, using decentralized testing mechanisms to distinguish between local and intermediate routing issues, and apply algorithms to select optimal call routes based on weight factors and cost metrics, allowing for intelligent call-routing decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If call routing is optimized for cost, then cost efficiency improves, but call quality may deteriorate due to selection of lower-quality routes
Solution Approach 1:
The system dynamically adjusts routing decisions by continuously monitoring call quality metrics and cost factors, allowing the routing path to adapt in real-time rather than being static. This enables the system to select optimal routes that balance both cost and quality requirements
Solution Approach 2:
The system changes routing parameters by assigning different weight factors to various call quality metrics (packet loss, delay, jitter) and cost metrics, allowing flexible optimization of the routing decision based on prioritized parameters
2Measurement precision
If decentralized testing mechanisms are implemented at endpoint devices, then call quality monitoring improves, but device complexity increases
Solution Approach 1:
Endpoint devices implement feedback mechanisms that continuously monitor call quality metrics and report them to the routing system. This feedback loop enables precise measurement of call quality without requiring complex manual intervention
Solution Approach 2:
The endpoint devices perform self-testing and self-monitoring of call quality parameters, eliminating the need for external testing infrastructure and reducing the complexity burden on the devices
3Measurement precision
If multiple call quality factors are measured and analyzed, then routing decision accuracy improves, but processing complexity increases
Solution Approach 1:
The system segments the call quality assessment by attributing quality issues to specific portions of the call route (endpoint device, local connection, intermediate network). This segmentation allows focused analysis of individual factors rather than overwhelming processing of all factors simultaneously
Solution Approach 2:
The system introduces an intermediary routing server that collects, aggregates, and analyzes call quality metrics from multiple endpoints. This intermediary handles the complex processing of multiple quality factors, relieving the endpoint devices of heavy computational burdens
Data Source
AI summary
A variety of methods, systems, devices and arrangements are implemented for assessing and/or controlling call routing for Internet-based (e.g., VoIP/VioIP) calls. According to one such method, endpoint devices are used to monitor and/or assess the call-quality. The assessment is sent to a centralized server arrangement and call-routing is controlled therefrom. Endpoint devices employ a decentralized testing mechanism to further monitor and assess call quality. Aspects of call quality are analyzed and attributed to endpoint devices and/or local connections or networks to distinguish intermediate routing issues from local/endpoint issues.