The Passive and Active Measurement (PAM) conference brings together researchers and operators to discuss novel and emerging work in the area of network measurement and analysis. PAM is inclusive of all areas of network measurement, but focuses on systems-based research and real-world data. Indeed, measurement technology is needed at all layers of the network stack, ranging from power profiling of hardware components to virtualization in data centers to application profiling and even user experience. Work with operational impact or relevance to the broader network research community is especially welcome, as is early and promising measurement technique. Original contributions that advance the state-of-the-art in the following areas are invited:
Although PAM traditionally attracts early stage contributions, works that are a reappraisal or independent validation of previous results, or which enhance the reproducibility of network measurement research, for instance by publishing new datasets on an existing topic, are explicitly included in PAM's scope.
Authors should only submit original work that has not been published before and is not under submission to any other venue. All submissions must satisfy the following requirements:
Following the standard set by the Internet Measurement Conference (from which we base this section), papers describing experiments with users or sensitive user data (e.g., network traffic, passwords, social network information) must follow basic precepts of ethical research and subscribe to community norms. These include: respect for privacy, secure storage of sensitive data, voluntary and informed consent if users are placed at risk, avoiding deceptive practices when not essential, beneficence (maximizing the benefits to an individual or to society while minimizing harm to the individual), and risk mitigation.
When appropriate, authors are encouraged to include a subsection (in the main paper, not in the Appendix) describing these issues.
Authors may want to consult the Menlo Report (here) for further information on ethical principles and the Allman/Paxson IMC 07 paper ( here ) for guidance on ethical data sharing.
Note that submitting research for approval by each author's institutional ethics review body is necessary, but not sufficient -- in cases where the PC has concerns about the ethics of the work in a submission, the PC will consider the ethical soundness and justification of any paper, just as it does its technical soundness. Authors unsure about ethical issues are welcome to contact the program committee co-chairs.
There will be two awards for papers of exceptional merit. The Best Paper award will recognize the paper that is deemed by the committee to have the highest merit of all the submissions. The Best Dataset Award will be given to the best paper that makes datasets and corresponding code available to the public by the time the camera-ready is submitted. These artifacts must be sufficiently documented such that any researcher can use them to repeat the results described in the paper, and they must be placed in a sufficiently long-lived archival repository (e.g., Github, Bitbucket, or CRAWDAD).