Conference Information
SIGMETRICS 2023: International Conference on Measurement and Modeling of Computer Systems
https://www.sigmetrics.org/sigmetrics2023/index.html
Submission Date:
2023-01-25
Notification Date:
2023-03-28
Conference Date:
2023-06-19
Location:
Orlando, Florida, USA
Years:
49
CCF: b   CORE: a*   QUALIS: a1   Viewed: 52085   Tracked: 162   Attend: 15

Call For Papers
 The 2023 ACM SIGMETRICS conference will be held in Orlando, Florida, USA, on June 19-23, 2023.

We solicit papers on the development and application of state-of-the-art, broadly applicable analytic, simulation and measurement-based performance evaluation techniques. The conference provides a high-quality forum for presenting results and discussing ideas that further our knowledge and understanding of the measurement, modeling, analysis, and design of computing systems and networks. Of particular interest is work that presents new performance evaluation methods, or that creatively applies previously developed methods to make predictions about, or gain insights into key design trade-offs in a variety of computing, networked, and cyber-physical systems, ranging from mobile devices and Internet-of-Things (IoT) applications to large-scale cloud computing systems and the smart grid. The conference presents papers that have been accepted to appear in the Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS). There are multiple deadlines to submit your work in time for a presentation at the conference (see below). A panel of reviewers will consider all accepted and eligible papers, for the Best Paper Award and the Kenneth C. Sevcik Outstanding Student Paper Award. Additionally, a selection of the accepted papers, as identified by a panel of reviewers, may be nominated for publication as Research Highlights in the Communications of the ACM (CACM).
A note on the ongoing COVID-19 situation

The SIGMETRICS 2023 conference organizers are monitoring the COVID-19 situation from local authorities and the World Health Organization. The conference is several months away, and we hope that the event will be held as planned. It is expected that authors will be required to present their papers in person. Only in the case of major outbreaks near the conference dates alternative solutions will be considered. Regardless of the mode of presentation, all accepted papers will be published in the Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS).

Topics

We solicit papers describing original and previously unpublished research. Specific topics of interest include, but are not limited to, the following.

Quantitative measurement, design and evaluation studies of:

    Computer and communication networks, protocols and algorithms
    Wireless, mobile, ad-hoc and sensor networks, IoT applications
    Computer architectures, hardware accelerators, multi-core processors, memory systems and storage networks
    High Performance Computing
    Operating systems, file systems and databases
    Virtualization, data centers, distributed and cloud computing, fog and edge computing
    Mobile and personal computing systems
    Energy-efficient computing systems
    Real-time and fault-tolerant systems
    Security and privacy of computing and networked systems
    Software systems and services, and enterprise applications
    Social networks, multimedia systems, Web services
    Cyber-physical systems, including the smart grid

Methodologies, formalisms, metrics, solution techniques and algorithms for:

    Analytical modeling techniques and model validation
    Workload characterization and benchmarking
    Performance, scalability, power and reliability analysis
    Sustainability analysis and power management
    System measurement, performance monitoring and forecasting
    Anomaly detection, problem diagnosis and troubleshooting
    Capacity planning, resource allocation, run time management and scheduling
    Experimental design, statistical analysis, simulation
    Game theory, network economics, and platform design
    Big data, machine learning, AI, data mining, graph analysis, optimization
Last updated by Dou Sun in 2022-07-17
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
2021841416.7%
20202864415.4%
20193175015.8%
20182705420%
20172032713.3%
20162082813.5%
20152393213.4%
20142374016.9%
20131962613.3%
20122033115.3%
20111772916.4%
20101842915.8%
20091802715%
20082013617.9%
20071702917.1%
20062173013.8%
20052373113.1%
20042653312.5%
20032222611.7%
20021702313.5%
20012333012.9%
20001652817%
1999921819.6%
19981362518.4%
19971302519.2%
19961102421.8%
19951232722%
19941102522.7%
19921082018.5%
19901022322.5%
19891362216.2%
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