会议信息
IMC 2025: Internet Measurement Conference
https://conferences.sigcomm.org/imc/2025/
截稿日期:
2025-05-08
通知日期:
2025-08-18
会议日期:
2025-10-28
会议地点:
Madison, Wisconsin, USA
届数:
26
CCF: b   CORE: a   QUALIS: a1   浏览: 71915   关注: 106   参加: 8

征稿
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 2025 will focus on advancing the state of the art in the collection, usage, analysis, 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, 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
    experimental networks, prototype networks, and future internetworks
最后更新 Dou Sun 在 2025-03-02
录取率
时间提交数录取数录取率(%)
20202165324.5%
20191973919.8%
20181744324.7%
20171794223.5%
20161824625.3%
20151694426%
20141884322.9%
20131784223.6%
20121834524.6%
20112204219.1%
20102114722.3%
20091834122.4%
20081853217.3%
2007862124.4%
20061553421.9%
20051483624.3%
20041573924.8%
20031093229.4%
2002933941.9%
2001531426.4%
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