The OSI Model in Practice: How Surfmeter Measures the End-User Layer

Adding Layer 8 to the OSI model

The ISO/OSI model is the invisible backbone of our daily internet use. It’s an abstract framework that organizes the complex process of digital communication into seven distinct layers: Physical, Data Link, Network, Transport, Session, Presentation, and Application. However, the complexity of this stack leads to two important issues when it comes to measuring end-user experience:

  1. Many network measurement tools focus on metrics from a single layer, providing only a partial view – measuring or optimizing one layer in isolation doesn’t guarantee a better overall user experience. In other words: problems experienced by users often stem from complex interactions between these layers.
  2. The highest ISO/OSI layer still does not tell you what the user really experienced. While it gives you important information about what was transmitted on the network, knowing what happened on the screen is the most crucial aspect for the final Quality of Experience.

At AVEQ, our Surfmeter platform is built on a cross-layer measurement methodology. This means Surfmeter doesn’t just look at one piece of the puzzle; it analyzes how the different layers work together to deliver services to your end-users

And while over the course of time some layers have become less important, there is something new on the horizon: Layer 8 – the end-user layer. This is where the actual customer experience happens. In the current research discussions, Layer 8 is becoming increasingly talked about, even though there is no standardized definition of that yet.

Stakeholders across the entertainment and networking industries realize that this holistic approach is crucial for truly understanding and improving Quality of Experience (QoE). Let’s explore this top-most layer in conjunction with the ISO/OSI layers to see why this matters.

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New Research: ITU-T P.1203 Validated on Real-World Satellite Streaming Data

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We’re pleased to share new research that has been published in IEEE Access. The findings validate the accuracy of QoE prediction models such as ITU-T Rec. P.1203 against real-world streaming conditions. The peer-reviewed paper, titled “Satellite Streaming Video QoE Prediction: A Real-World Subjective Database and Network-Level Prediction Models,” represents a collaboration between researchers at the University of Texas at Austin (LIVE), Viasat Inc., TU Ilmenau (Audiovisual Technology Group), and AVEQ. As the title indicates, it tackles the challenge of predicting video Quality of Experience (QoE) over satellite networks using real user data.

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VideoAnalyzer — AVEQ’s High-Performance C++ Toolkit for No-Reference Video Metrics

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At AVEQ, a significant part of our work involves the deep analysis of video streams to understand and quantify quality. While our flagship product Surfmeter uses a client-side approach to measure delivery QoE (i.e., how well does the network support streaming?), we also needed a solution to understand video quality at the source. Think, for example, ingesting video streams that might be affected by blockiness or frozen frames. Or verifying encoder output. To address this, we built the AVEQ VideoAnalyzer — and in this post we’re going to give you a sneak preview of it.

Our new video analyzer in use
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Stop Believing Ping Tests Are Sufficient: Why ping tests are no longer enough for a great QoE

Are you providing Internet services, and  your customers complain about buffering screens and broken movie nights? Are you perhaps telling them that the problem might be their local WiFi, because in your own network monitoring tools, ping tests show that the video CDN was available within a few milliseconds? Of course, ping tests are, and will remain, an essential tool for basic network diagnostics. But when your customers complain about buffering, broken conferences, etc., are they still the only tool you should be reaching for? In this post, we’ll explain how modern application-layer monitoring is the key to enable a great QoE to your customers. Read on to find out more!

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What does a MOS of x mean…? Interpreting the MOS in real-world terms

Illustration: Know what your users see.

Networks can behave like humans: Sometimes they have a shiny great day and everything works like a charm – and sometimes they feel tired and are soooo slow. Usually when humans get tired, they need a rest from the hard work they did. Networks don’t have that luxury. Under stress, they greet us with loading spinners, rotating hourglasses or just a simple “the service you are calling is not available” message in the browser. How can you, as a network operator, make the right decisions and make networks more resilient against packet loss or jitter, inefficient routing and transmission delays. And how do you pre-emptively solve customer complaints? The answer is: continuous quality monitoring. For video, web browsing, or other OTT apps like conferencing services.

But all the best data is not useful if you can’t make sense of the numbers you’re seeing. So in this article, we want to go deeper and explain how you can understand the data from the monitoring itself. In particular, the Mean Opinion Score.

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Measuring CDN Performance with Surfmeter’s New CDN Analysis Tool

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Seamless web browsing isn’t just a convenience; it’s a fundamental expectation by end-users in our connected world. For Internet Service Providers (ISPs) and network operators, delivering a fast, responsive online experience is important to customer satisfaction and retention. When web pages lag or videos buffer endlessly, subscribers don’t just get frustrated—they start looking for alternatives.

But here’s the challenge: a modern webpage is rarely a single, monolithic entity. It’s a complex set of content delivered by multiple sources. Your favorite news sites, shopping platform, or streaming service likely pulls in text, images, scripts, and video from various Content Delivery Networks (CDNs), each optimized for different types of content or geographic regions. The overall loading performance and the perceived user experience depend on the coordinated delivery from all these CDNs. If even one of them fails, the entire experience can suffer.

At AVEQ, we’re constantly pushing the R&D envelope to give you deeper, more actionable insights into this aspect. That’s why we’re thrilled to roll out a powerful new CDN analysis feature within our Surfmeter platform, designed to help you diagnose and tackle these very challenges head-on. Read on to find out more!

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AVEQ Opens Up: Surfmeter Documentation Now Public

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We’re happy to announce that we’ve taken a significant step forward in our transparency and ease-of-use by opening up our Surfmeter documentation to the public. We want to provide comprehensive, accessible information about our video streaming (and network performance) monitoring solutions, and you should be able to read it without signing a non-disclosure agreement or going through multiple sales calls. Read on to find out more.

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Modernizing Our Video Analytics Stack: From Rails to Node.js

We recently completed a significant migration of our Surfmeter Client Analytics backend from Ruby on Rails and Postgres to a modern Node.js-based architecture based on Express and BullMQ. Here’s how we approached this migration and what we learned along the way. We hope this blog post will be useful to others who are considering a similar migration!

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How Does WiFi Energy Use Affect Streaming Quality?

If you are using somewhat modern WiFi equipment, you will probably have an option to turn on an “eco” mode. These settings promise to save power at the expense of network speed. But how much does that affect the actual speed and application performance? Luckily, we have our Surfmeter probes to find out. Turns out that the impact can be quite significant. Read on to see how we can accurately measure the impact of power-saving settings on the end user experience!

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