Conference Information
SIGMETRICS 2021: International Conference on Measurement and Modeling of Computer Systems
https://www.sigmetrics.org/sigmetrics2021/
Submission Date:
2021-01-29
Notification Date:
2021-03-30
Conference Date:
2021-06-14
Location:
Beijing, China
Years:
47
CCF: b   CORE: a*   QUALIS: a1   Viewed: 31860   Tracked: 123   Attend: 8

Conference Location
Call For Papers
Overview

The 2021 ACM SIGMETRICS conference will be held in Beijing, China, June 14-18, 2021.

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.

Papers that are accepted to present at the conference will appear in the Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS). All accepted and eligible papers will be considered, by a panel of reviewers, 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 2021 conference organizers are monitoring the COVID-19 situation from local authorities and the World Health Organization. The well-being of members of our community, and their families and friends, is an important concern for us. The conference is several months away, and we hope that the COVID-19 emergency will subside and the conference will be held as planned. However, alternative solutions, such as a virtual format, remote presentations, or others, will be considered as needed. 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 2020-11-22
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
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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