Remote Session FEC Adaptation for Packet Loss and Latency
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Solution Overview
Problem
Current desktop virtualization systems face challenges in delivering high-quality, responsive virtual computing sessions over networks with high latency and packet loss, particularly with high-resolution displays and mobile devices, leading to laggy user experiences in office, 3D Pro, and Virtual Reality (VR) use cases.
Innovation Solution
The system employs a processor to generate forward error correction (FEC) data based on a ratio of graphical content bandwidth to FEC bandwidth, adjusting this ratio based on Quality of Service (QoS) parameters like packet loss rate, latency, and server load, and sends graphical content and FEC data over virtual channels for improved rendering and user input delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If forward error correction (FEC) data is generated and transmitted over virtual channels, then reliability of graphical content delivery is improved, but bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts the ratio of graphical content bandwidth to FEC bandwidth based on QoS parameters such as packet loss rate, latency, and server load. When packet loss increases, the system increases FEC bandwidth allocation to maintain reliability, and when conditions improve, it reduces FEC overhead to optimize bandwidth utilization.
Solution Approach 2:
The patent implements dynamic adaptation of FEC strategies by monitoring network conditions and adjusting the level of error correction applied to different virtual channels. The system can selectively apply FEC to specific channels based on their reliability requirements and current network state, rather than uniformly applying FEC to all traffic.
2Quantity of substance
If the ratio of graphical content bandwidth to FEC bandwidth is increased to reduce bandwidth consumption, then bandwidth efficiency is improved, but reliability deteriorates in high packet loss environments
Solution Approach 1:
The system monitors QoS parameters including packet loss rate and dynamically adjusts the FEC bandwidth ratio accordingly. In high packet loss environments, the system increases FEC allocation to maintain reliable delivery, while in good network conditions, it reduces FEC overhead to maximize bandwidth efficiency for graphical content.
Solution Approach 2:
The patent implements feedback mechanisms that monitor network conditions and delivery performance, then adjust FEC strategies in response. The system uses QoS parameter feedback to continuously optimize the balance between bandwidth efficiency and delivery reliability, adapting to changing network conditions in real-time.
3Reliability
If FEC bandwidth is increased to improve delivery reliability, then packet loss resistance is improved, but overall system throughput decreases
Solution Approach 1:
The system applies FEC selectively to specific virtual channels based on their individual reliability requirements and the current network conditions affecting each channel. Rather than uniformly applying FEC to all traffic, the system optimizes FEC allocation for each channel, ensuring reliable delivery where needed while minimizing overhead elsewhere to preserve overall throughput.
Solution Approach 2:
The patent implements dynamic adjustment of FEC bandwidth allocation based on real-time monitoring of packet loss rates and network conditions. The system can increase FEC bandwidth when packet loss is high to maintain reliability, and decrease FEC bandwidth when conditions improve to maximize throughput, creating a dynamic balance between these competing objectives.
4Adaptability or versatility
If QoS parameters are monitored and FEC bandwidth ratio is dynamically adjusted, then adaptability to network conditions is improved, but system complexity increases
Solution Approach 1:
The system implements feedback loops that monitor QoS parameters such as packet loss rate, latency, and server load, then automatically adjust FEC bandwidth allocation in response. This feedback-driven approach enables the system to adapt to changing network conditions without manual intervention, managing complexity through automated control mechanisms.
Solution Approach 2:
The patent enables the system to self-adjust FEC strategies based on monitored network conditions, reducing the need for external configuration or manual management. The system autonomously monitors QoS parameters and modifies its FEC allocation to optimize performance, effectively managing its own adaptability to changing conditions.
Data Source
AI summary
A server may include a memory and a processor cooperating with the memory to host virtual computing sessions to be remotely displayed at a client device via a frame buffer, where the client device is configured to render the virtual computing sessions via a graphical user interface (GUI). The processor may further generate forward error correction (FEC) data for graphical content within the frame buffer based upon a ratio of graphical content bandwidth to FEC bandwidth, and determine a Quality of Service (QoS) parameter associated with the at least one virtual channel. The processor may further adjust the ratio of graphical content bandwidth to FEC bandwidth based upon changes in the QoS parameter, and send the graphical content and associated FEC data to the client device over at least one virtual channel for display within the GUI.