Periodic Reporting for period 2 - FAST-STREAM (Solving the ‘last-mile delivery challenge’ for quality Over-The-Top (OTT) streaming content)
Reporting period: 2023-02-01 to 2024-09-30
The root cause of these problems is the "the last mile network". To reach its destination, content must often traverse volatile network segments (such as mobile and Wi-Fi networks) and must compete with traffic from other services over scarce network bandwidth. Bad user-experience results in customer churn, decreased user engagement, and loss of income for service providers. It also harms the ability to effectively work and study from home and has a negative impact on the economy.
Compira Labs' solution is utilizing Performance-oriented Congestion Control (PCC) algorithmic framework, data analysis and machine learning methodologies. While it requires no changes to the network or applications, it offers better utilization of the existing networks thus reducing the digital divide by providing better access to Internet services to wider communities.
The goals of this project were focused on scaling up our technical solution to support successful large-scale field trials for a diverse set of customer use cases, followed by successful qualification and validation of our technology under operational conditions.
1. Qualification and validation of solution in operational environments: We conducted pilots with Telefonica (Spain, Chile, Peru), Lumen (USA, Mexico), Conversant Solutions Pte Ltd. (Vietnam. Malaysia), and Medianova (Europe and Middle East). In these pilots, we were able to effectively qualify and validate our CompiraEdge software for HTTP/TCP and QUIC/UDP delivery, as well as its integration with our CompiraCloud data platform and SaaS dashboard, in a variety of use-cases and networks.
2. Technology improvements and development: Scale up of our technical solution for a commercially viable product. This included performance improvement of pre-commercial PCC module plug-ins (HTTP/TCP, QUIC, WebRTC), increasing protocol resiliency, scaling data collection and analytics engine, enabling automated PCC configuration updates (using machine learning techniques), and improving and extending our testing capabilities to cover all primary transport platforms as well as additional network scenarios (mobile, fixed networks, etc.).
In the lab, our solution achieved better user experience metrics than the state-of-the-art alternatives for both HTTP3/QUIC and webRTC implementations.