Per-Application Traffic Multiplexing Agent for Network Optimization
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Solution Overview
Problem
User devices face challenges in optimizing network traffic distribution across multiple networks (e.g., Wi-Fi and LTE) to provide the best quality of experience (QoE) for various applications, as different networks offer varying levels of performance in terms of latency and throughput.
Innovation Solution
Implementing a traffic multiplexing agent on user devices that receives key performance indicator (KPI) information from network monitoring servers to determine the optimal distribution of traffic across multiple networks on a per-application basis, using a traffic multiplexing and de-multiplexing process facilitated by a proxy server to ensure applications utilize networks that provide better performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traffic is routed through a single network, then device complexity is reduced, but network performance (latency and throughput) cannot be optimized for different applications
Solution Approach 1:
A traffic multiplexing agent is introduced as an intermediary component that sits between applications and network interfaces. This agent intelligently routes traffic from different applications to appropriate networks (Wi-Fi, LTE, 5G) based on application requirements and network conditions, optimizing performance without requiring applications themselves to be complex
Solution Approach 2:
Network traffic is segmented by application, with each application's traffic handled independently based on its specific requirements. The system divides traffic into different streams and routes each stream through the most suitable network, allowing simultaneous optimization of multiple applications with different performance characteristics
2Reliability
If traffic is multiplexed across multiple networks, then application-specific performance is improved, but device complexity increases
Solution Approach 1:
Applications provide self-service by declaring their traffic requirements and performance preferences to the traffic multiplexing agent. The agent then autonomously manages routing decisions based on this information and real-time network conditions, reducing the need for complex centralized control while improving reliability
Solution Approach 2:
The system implements feedback mechanisms where network performance metrics are continuously monitored and fed back to the traffic multiplexing agent. This feedback loop enables dynamic adjustment of routing decisions to maintain optimal quality of experience, with the agent adapting to changing network conditions in real-time
3Speed
If network traffic is dynamically routed, then latency and throughput are optimized, but measurement and control difficulty increases
Solution Approach 1:
The traffic multiplexing agent serves multiple functions simultaneously: it monitors network performance, measures traffic characteristics, makes routing decisions, and manages multiple network interfaces. This multi-functionality consolidates complex measurement and control tasks into a single component, reducing overall system complexity while optimizing speed
Data Source
AI summary
A system may be configured to multiplex traffic, on a per-application basis, over multiple networks. The traffic may be multiplexed based on weights, associated with each application, and key performance indicators (“KPIs”) associated with the networks. The system may output a first proportion of traffic, associated with the application, via a first network, and may output a second proportion of traffic, associated the application, via the second network.