Use this to audit novelty and eligibility. SIGMETRICS reviewers are close to the performance-evaluation literature and expect to see where your paper sits relative to the nearest prior model, bound, or measurement — stated as a delta, not a list. Reopen the current call for the simultaneous-submission and prior-publication rules (a paper under one-shot revision counts as under submission) before advising authors.
| Lane | Typical venues | What SIGMETRICS reviewers check |
|---|---|---|
| Core performance evaluation | SIGMETRICS/POMACS, Performance Evaluation, QUESTA | Whether the nearest model/bound/measurement is compared or distinguished |
| Systems (when you claim a systems payoff) | NSDI, OSDI, SIGCOMM, ATC | Whether the system you improve/measure is credited and fairly baselined |
| Measurement | IMC, PAM, INFOCOM | Whether prior measurements of the same system/workload are engaged |
| Learning (Learning track) | NeurIPS, ICML, COLT | Whether the learning-theoretic predecessor (regret bounds, algorithms) is cited to its origin |
| Networking/queueing journals | IEEE/ACM TON, QUESTA, Stochastic Models | Whether deeper journal-length analyses of the model are engaged |
A bibliography that cites only your own subarea tells a reviewer the delta may be smaller than claimed; one that reaches the neighboring theory, systems, and measurement venues signals command of the field.
Suppose the paper proves a tail-latency bound for a rank-based scheduler. Its nearest neighbors: a prior analysis of a single age-based policy (one policy, mean latency), a general scheduling framework (broad class, but no tail bound), and a measurement study of the target system (data, no policy analysis). The novelty sentence should name all three contrasts — a tail bound where the single-policy analysis gave only mean, a provable tail guarantee where the framework gave none, and a policy with analysis where the measurement gave only characterization.
[Concurrent arXiv work] cite neutrally, state the technical difference (tighter bound? weaker
assumption? newer measurement?), avoid unverifiable priority claims;
keep the citation double-anonymous
[Your workshop version] usually non-archival and citable, but confirm against the current call
wording and phrase so anonymity survives
[Prior short version] declare the overlap and state what the full paper adds (proofs, validation)
[Paper under one-shot revision] it is under submission to SIGMETRICS -- do not submit it elsewhere
before withdrawing
[Eligibility] clear / needs declaration / risky
[Lanes covered] <performance-eval / systems / measurement / learning / journals>
[Nearest 3 works] <work -> one-line delta (tighter bound / weaker assumption / broader class / newer data)>
[Archival-overlap risk] <none / declare: what>
[Novelty sentence] <SIGMETRICS-ready contribution contrast against the nearest prior work>