The Internet Measurement Conference (IMC) is a highly selective venue for the presentation of measurement-based research in data communications. As we are in the era of data-driven research, IMC 2024 will focus on improving the standard in the collection, usage, and sharing of network measurements for the research community. Despite the efforts in stimulating reproducibility of research as well as sharing of data, little progress has been made in our community to make research data open. Therefore, without fundamentally changing the topics in scope compared to previous years, our attention when assessing contributions will be particularly on the willingness of the authors to share their data and make their work reproducible.

To encourage data sharing and reproducibility, authors will be required to make a declaration on artifact availability (full, partial, or no availability) for the submitted work. Since legitimate reasons (such as proprietary and privacy reasons) may prevent authors from sharing artifacts, papers will be assessed based on whether the contributions warrant acceptance despite the lack of artifact availability. In the case of no availability of artifacts, the authors are expected to explain why this is the case in a specific section. Artifact submission is not required at the paper submission time. All papers accepted to the program will be shepherded to ensure that the artifacts promised have been made available.

IMC takes a broad view of contributions that are considered in scope for improving the practice of network measurement, including, but not limited to:

    collection and analysis of data that yield new insights about network structure and network performance (e.g., traffic, topology, routing, energy utilization, performance)
    collection and analysis of data that yield new insights about application and end-user behavior (e.g., economics, privacy, security, application interaction with protocols)
    measurement-based modeling (e.g., workloads, scaling behavior, assessment of performance bottlenecks, causality)
    methods and tools to monitor and visualize network-based phenomena
    systems and algorithms that build on measurement-based findings
    theoretical analysis and modeling of networked-systems and measurement techniques
    novel methods for data collection, analysis, and storage (e.g., anonymization, querying, sharing)
    reappraisal of previous empirical network measurements and measurement-based conclusions
    descriptions of challenges and future directions the measurement community should pursue

Networks of interest include:

    Internet transit networks
    edge networks, including home networks, broadband access networks (e.g., cable, fiber), and cellular networks
    data center networks and cloud computing infrastructure
    peer-to-peer, overlay, and content distribution networks
    software-defined networks
    online social networks
    online services, platforms, and content providers