The vision for next generation communication systems sets an extraordinarily high bar for networks. These are expected to become general-purpose platforms, and connect a plethora of extremely heterogeneous terminals, all while catering to a surging demand for bandwidth and to diverse applications. Emerging paradigms based on the softwarization, cloudification and native AI support of the network infrastructures are fostering exciting changes in the ways we build and manage such systems. In particular, they force us to re-think traffic measurement and analysis across the whole stack, from the physical layer up to applications in the Cloud.

The Network Traffic Measurement and Analysis Conference (TMA) aims at being a highly selective venue for presenting both mature and early-stage research – as well as controversial work – on all aspects of both measurement and analysis of network traffic. TMA conference has a strong tradition of open and lively interaction among scientists and engineers in academia and industry, and serves as a premier forum to exchange ideas, and present advances over the state-of-the-art.

TMA 2023 invites submissions presenting concepts, experiences, and of course results in collection, processing, analysis and visualization of network traffic data, which may address performance enhancement, monitoring, management, security, privacy or other uses of network data. The focus is on improving the practice or application of network measurements across the entire network stack up to application layers, with an emphasis on diverse areas of network communication such as Network Function Virtualization, Software-Defined Networks, Cloud Services, Data Centers or Content Distribution Networks, so as to support innovative services and applications. We also welcome more traditional measurement topics, such as traffic classification, anomaly detection, network performance evaluation and traffic analysis.

To further encourage the results’ faithfulness and avoid publication bias, the conference will particularly encourage negative results revealed by novel measurement methods or vantage points.

When starting a research work, researchers often have a desired outcome in mind, e.g. that their new measurement method will be the most performing, or that this new vantage point will reveal breath-taking discoveries. Reality is often disappointing, and some of our tryouts do not yield the expected (hoped-for) output. Yet, there is a value for other researchers to know what did not work.

All regular papers are hence encouraged to discuss limitations of the presented approaches and also mention which experiments did not work. When facing papers of equal technical merit, we will use the above aspects as a tie breaker. By explicitly encouraging this, we wish to create a virtuous circle in which we present all our results including those going against our initial “wishes” and intentions.

TMA will also be open to accepting papers that exclusively deal with negative results, especially when new measurement methods or perspectives offer insight into the limitations and challenges of network measurement in practice. Depending on received submissions, a dedicated session on negative results may be included in the conference program. Negative results will be evaluated based on their impact (e.g. revealed in realistic production networks) as well as the novelty of the vantage points (e.g. scarce data source) or measurement techniques that revealed them.

Topics of interest include, but are not limited to:

  • Traffic measurement, analysis, characterization, visualization and classification

  • Use of data analytics, data mining, artificial intelligence and machine learning in network measurement and analysis

  • Novel representation learning methods for traffic measurements

  • Use of big data, high-rate processing, sketches and data reduction in network measurement, analysis and visualization

  • Measurements of data centers or cloud-based systems

  • Measurements of Software-Defined Networks (SDN) and Virtual Network Functions (VNF)

  • Measurements of home, mobile and wireless traffic including devices with multiple network paths

  • Application-layer measurements, including web services, social networks, mobile applications

  • Measurements of quality of service and quality of experience, for network services using audio, video, virtual/augmented reality and gaming

  • Measurements of network performance and network structure

  • Measurement of traditional and new protocols (e.g. TCP, MPTCP, IPv6, HTTP/2, QUIC) and modes of communication (e.g. NFC and IoT)

  • Measurements on testbeds, experimental networks or prototype networks

  • Platforms for measurement, troubleshooting, management, and control of operational networks

  • Simulation and modeling for network measurements, analysis and visualization

  • Identification and classification of traffic, including encrypted and proprietary protocols

  • Techniques for and implications of privacy preservation, enhancement and anonymization in the context of traffic measurements

  • Applications of traffic analysis for security, anomaly/vulnerability/attack detection and user profiling/privacy

  • Current and emerging regulatory frameworks for measurement, analysis and privacy

  • Validation and repeatability of measurements, shared datasets, collaborative platforms

  • Negative results revealed by novel traffic measurements