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Please submit your papers via this link:

Authors are invited to submit original unpublished manuscripts that demonstrate current research on distributed sensor systems related to DCOSS-IoT topics of interest. Standard IEEE conference templates for LaTeX formats can be found here:
Please use a 10pt font, i.e., the default behavior when specifying \documentclass[conference]{IEEEtran}.

All submissions should be written in English with a maximum of eight (8) printed pages including figures and references. Authors may add at most two (2) pages, but only for an appendix, i.e. these two pages contain supplementary material only (such as theorems, proofs, implementation details). The additional two pages will incur overlength charges at $100/page.

For any questions related to paper submissions and the peer review process please feel free to contact the TPC Chairs.

Note that this year DCOSS-IoT is following a double-blind review policy. As a result, authors must make a good faith effort to anonymize their submissions. Please adhere to the following checklist:

  • Omit authors’ names and institutions from your title page.
  • When you cite your own work, refer to it in the third person. For example, if your name is Smith and you have worked on automated bug repair, instead of saying “We extend our work on information retrieval for finding and removing earwigs [0],” you should say “We extend Smith’s [0] work on information retrieval for finding and removing earwigs.”
  • There may be cases in which the current submission is clear follow up of one of your previous work, and despite what recommended in the previous point, reviewers will clearly associate authorship of such a previous work to the current submission. In this case, you may decide to anonymize the reference itself at submission time. For example: “based on previous results [10]” .. where the reference is reported as “[10] Anonymous Authors. Omitted per double blind reviewing.” In doing so, however, please make sure that your new submission is self-contained and its content can be reviewed and understood without accessing the previous paper.
  • Do not include acknowledgements of people, grants, organizations, etc. that would give away your identity. You may, of course, add these acknowledgements in the camera-ready version.
  • In general, aim to reduce the risk of accidental unblinding. For example, if you use an identifiable naming convention for your work, such as a project name, use a different name for your submission, which you may indicate has been changed for the purposes of double-blind reviewing. This includes names that may unblind individual authors and their institutions. For example, if your project is called “GoogleDeveloperHelper,” which makes it clear the work was done at Google, for the submission version, use the name “DeveloperHelper” or “BigCompanyDeveloperHelper” instead.
  • Avoid revealing the institution affiliations of authors or at which the work was performed. For example, if the evaluation includes a user study conducted with undergraduates from the CS 101 class that you teach, you might say “The study participants consist of 200 students in an introductory CS course.” You can of course add the institutional information in the camera-ready. Similar suggestions apply for work conducted in specific organizations (e.g., industrial studies). In such cases, avoid to mention the organization’s name. Instead, you may just refer the organization as “Org” or “Company,” etc. When appropriate and when this does not help too much in revealing the company’s name, you might mention the context (e.g., financial organization, video game development company, etc.).
  • Avoid linking directly to code repositories or tool deployments which can reveal your identity. You may post anonymized links (with a warning that following said link may reveal authors’ identities), include links to anonymized code or deployments. When creating such repositories, a good practice can be asking somebody in your team to test the anonymization of the repository and of its content. In case anonymization is difficult to be achieved and you still want to provide availability of data/tools, you can simply state that you will link to the code or deployment in the camera-ready version.