Quick Links

Conferences

  • SIGMETRICS is the flagship conference of the SIGMETRICS community.
  • Performance is the flagship conference of IFIP WG 7.3 and occurs jointly with SIGMETRICS once every three years.
  • IMC is at the intersection between SIGCOMM and SIGMETRICS, focusing on Internet measurement.
  • SenSys focuses on the design, implementation, and application of sensor networks.
  • ICPE (formerly WOSP/SIPEW) focuses on the intersection of software design and performance evaluation.

SIGMETRICS Awards

ACM SIGMETRICS currently sponsors several major awards to recognize important contributions in the area of performance evaluation:


The SIGMETRICS Achievement Award

The 2025 SIGMETRICS Achievement Award: Call for Nominations

The ACM SIGMETRICS Achievement Award is given annually to an individual who has made long-lasting, influential contributions to the analysis and evaluation of computer/communication system performance. The contributions may be theoretical advances that have influenced the techniques used to predict, control and optimize the performance of computer/communication systems, practical procedures or software tools that have been used widely to manage system performance, or innovative applications of performance evaluation models that have impacted the design of computer/communication systems.

The SIGMETRICS Achievement Award recipient is selected by an Awards Committee comprised of five individuals appointed by the SIGMETRICS Executive Committee. In selecting the achievement award recipient, the Awards Committee will place particular emphasis on seminal contributions and a sustained record of high-impact in the field.

The award includes a plaque and a $2500 award. The recipient is also invited to give a technical presentation at the conference.

The nomination rules disallow self-nominations, and do not require that the nominee be a member of SIGMETRICS.

Past nominations that did not result in an award can be resubmitted.

The nomination should include:

  • A two-page description of just those accomplishments which qualify the nominee as a candidate for the award. The description should draw particular attention to the contributions that merit the award and explain their significance.
  • A curriculum vitae of the nominee.
  • Five endorsements, of at most 300 words each, from other scientists in the field supporting the nomination. At least three of the five endorsers should be SIGMETRICS members. Members of the selection committee are not eligible to serve as nominator or endorser.
    • To emphasize the commitment of SIGMETRICS to diversity and inclusivity in all activities, endorsers are invited to comment in their letter on how the nominee exemplifies these core values.
  • A concise statement of the nominee's achievements to be inscribed on the award plaque.

The nomination materials must be e-mailed by March 15, 2025 to the committee chair Leandros Tassiulas at: leandros.tassiulas@yale.edu with SIGMETRICS in the subject line.

The 2025 Achievement Award committee comprises Leandros Tassiulas (chair), Marco Ajmone Marsan, Laurent Massoulié, Balaji Prabhakar, and R. Srikant . Questions should be sent to the committee chair.

Past winners

2024: Prof. Marco Ajmone Marsan (press release)
2023: Dr. Laurent Massoulié (press release)
2022: Prof. Balaji Prabhakar (press release)
2021: Prof. R. Srikant (press release)
2020: Dr. Leandros Tassiulas (press release)
2019: Prof. Mary Vernon (press release)
2018: Dr. Jim Dai (press release)
2017: Dr. Sem Borst (press release)
2016: Dr. John Tsitsiklis (press release)
2015: Dr. Bruce Hajek (press release)
2014: Prof. François Baccelli (press release)
2013: Dr. Jean Walrand (press release)
2012: Dr. Debasis Mitra (press release)
2011: Dr. Onno J. Boxma (press release)
2010: Dr. Jeffrey P. Buzen (press release)
2009: Dr. Frank Kelly (press release)
2008: Dr. Erol Gelenbe (press release)
2007: Dr. Don F. Towsley (press release)
2006: Dr. Richard R. Muntz (press release)
2005: Dr. Stephen S. Lavenberg (press release)
2004: Dr. Ken C. Sevcik (press release)
2003: Dr. Ed G. Coffman (press release)


Go back to top.

The SIGMETRICS Rising Star Research Award

CALL FOR NOMINATIONS: 2025 ACM SIGMETRICS Rising Star Research Award

The ACM SIGMETRICS Rising Star Research Award is given annually to recognize a rising star in our community who demonstrates outstanding potential for research in the field of computer and communication performance. The selection is based on the impact of the candidate's work in the field in creating promising new ideas, paradigms, and tools related to the performance analysis of computer and communication systems, which may be analytical or empirical in nature. Depth and impact are valued over breadth of contribution for this award. The recipient of the ACM SIGMETRICS Rising Star Research award is selected by a committee consisting of five individuals appointed by the SIGMETRICS Executive Committee. The award includes a plaque and a $1500 honorarium or expenses for travel to attend the conference where the award is presented.

Nominations for the award must include:

  • Summary of the candidate's research accomplishments (1 page, 11pt font).
  • Description of the significance of the candidate’s work and justification for the nomination (2 pages, 11pt font).
  • Curriculum vitae of the nominee, including list of publications.
  • Three endorsement letters from researchers in the field supporting the nomination. The nominator may write one of these three endorsement letters.
  • Copies of up to three of the candidate’s most significant papers.
  • A concise statement (one sentence) of the achievement(s) for which the award is being sought.

Rules for Nomination:

  • At least one of the three endorsers should be an ACM SIGMETRICS member.
  • The nominee must be within 7 years of having attained their PhD (counted with respect to the official award date of the degree, as opposed to the day of the defense).
  • The nominee cannot be any of the following: nominator, member of the ACM SIGMETRICS Executive Committee, or a member of the Rising Star Research Award Committee.

Nominations that do not result in an award can be resubmitted in subsequent years.

Please submit all nominations via email by March 4, 2025 to the committee chair, Kuang Xu, at kuangxu@stanford.edu. Please use “SIGMETRICS Rising Star nomination” as the subject header. The nominator must collect all materials and send them in a single e-mail.

The 2025 Rising Star Research Award committee comprises Kuang Xu (chair), Giulia Fanti, Leana Golubchik, Christina Lee Yu, Laurent Massoulie, Vishal Misra, and Weina Wang. Questions should be sent to the committee chair.

Past Winners

2024: Dr. Christina Lee Yu (press release)
2023: Dr. Weina Wang (press release)
2022: Dr. Giulia Fanti (press release)
2021: Dr. Zhenhua Liu (press release)
2020: Dr. Kuang Xu (press release)
2019: Prof. Anshul Gandhi (press release)
2018: Prof. Longbo Huang (press release)
2017: Prof. Sewoong Oh (press release)
2016: Prof. Yi Lu (press release)
2015: Prof. Jinwoo Shin (press release)
2014: Dr. Florian Simatos (press release)
2013: Prof. Augustin Chaintreau (press release)
2012: Dr. Marc Lelarge (press release)
2011: Prof. Adam Wierman (press release)
2010: Dr. Milan Vojnovic (press release)
2009: Prof. Alexandre Proutiere (press release)
2008: Prof. Devavrat Shah (press release)

Go back to top.

The SIGMETRICS Test of Time Award

The ACM SIGMETRICS Test of Time Award recognizes an influential paper from the ACM SIGMETRICS conference proceedings 10-12 years prior, based on the criterion of identifying the paper that has had the most impact (research, methodology, application, transfer) over the intervening period.

In each year, the author(s) of the winning paper will receive a recognition plaque and a $1500 honorarium, to be presented at the annual ACM SIGMETRICS conference. At least one author of the Test of Time Award paper must be present at the conference to receive the award.

The 2025 Test of Time Award committee chair is Devavrat Shah.

Past Winners

2024:
Nicolas Viennot, Edward Garcia, Jason Nieh, "A Measurement Study of Google Play" In Proceedings of ACM SIGMETRICS 2014.
This work presents PlayDrone, the first scalable crawler for the Google Play store, used to index and analyze over 1,100,000 Android applications daily, creating the largest index of its kind. The study uses PlayDrone to address four key issues: characterizing Google Play content and its evolution, examining library usage and its impact on portability, identifying duplicative content, and exposing vulnerabilities in OAuth and related authentication mechanisms that allow unauthorized access to user data and resources on platforms like Amazon Web Services and Facebook.
2023:
Myunghwan Kim, Roshan Sumbaly, Sam Shah, "Root Cause Detection in a Service-Oriented Architecture" In Proceedings of ACM SIGMETRICS 2013.
This work proposes MonitorRank, a system for identifying the root causes of anomalies in service-oriented architectures (e.g. LinkedIn). When called upon to investigate an anomaly, MonitorRank provides in real-time a rank-ordered list of its possible root causes. To this end, MonitorRank performs a weighted PageRank algorithm on an API call graph (linking together anomaly sensors) whose edge weights are learned offline in an unsupervised manner from historical anomaly sensor data.

2022:
Berk Atikoglu, Yuehai Xu, Eitan Frachtenberg, Song Jiang, Mike Paleczny, "Workload Analysis of a Large-Scale Key-Value Store" In Proceedings of ACM SIGMETRICS/Performance 2012.
This work provides a workload characterization of key-value stores using a large-scale dataset from Facebook's Memcached deployment consisting of over 284 billion requests. The study contributes to the scientific understanding of caching workloads in production, shedding light on request composition, sizes, rates, and temporal patterns, together with several other dimensions.

2021:
Zhenhua Liu, Minghong Lin, Adam Wierman, Steven Low, Lachlan L.H. Andrew, "Greening Geographical Load Balancing" In Proceedings of ACM SIGMETRICS 2011.
This paper explores whether the geographical diversity of Internet-scale systems can encourage use of "green" renewable energy and reduce use of "brown" fossil fuel energy. The paper defines two distributed algorithms for achieving optimal geographical load balancing and characterizes achievable reductions in brown energy use resulting from dynamical energy pricing schemes.

2020:
Devavrat Shah and Tauhid Zaman "Detecting Sources of Computer Viruses in Networks: Theory and Experiment" In Proceedings of ACM SIGMETRICS 2010.
This work provides a systematic study of the problem of finding virus sources in networks. The paper introduces the new notion of rumor centrality and shows it to outperform other network centrality notions in finding rumor sources in networks which are not tree-like.

2019:
Shreevatsa Rajagopalan, Devavrat Shah, and Jinwoo Shin "Network adiabatic theorem: an efficient randomized protocol for contention resolution" In Proceedings of ACM SIGMETRICS 2009.
This paper designs an algorithm building upon a Metropolis-Hastings sampling mechanism along with selection of 'weight' as an appropriate function of the queue-size. The key ingredient in establishing the efficiency of the algorithm is a novel adiabatic-like theorem for the underlying queueing network, which may be of general interest in the context of dynamical systems.

2018:
Yi Lu, Andrea Montanari, Balaji Prabhakar, Sarang Dharmapurikar, and Abdul Kabbani "Counter braids: a novel counter architecture for per-flow measurement" ACM SIGMETRICS Performance Evaluation Review 36.1 (2008): 121-132
This work revisits the problem of accurate per-flow measurement.It solves the central problems (counter space and flow-to-counter association) of per-flow measurement by "braiding" a hierarchy of counters with random graphs. Braiding results in drastic space reduction by sharing counters among flows; and using random graphs generated on-the-fly with hash functions avoids the storage of flow-to-counter association.

2017:
Bairavasundaram, Lakshmi N., Garth R. Goodson, Shankar Pasupathy, and Jiri Schindler. "An analysis of latent sector errors in disk drives" In ACM SIGMETRICS Performance Evaluation Review, vol. 35, no. 1, pp. 289-300. ACM, 2007.
This paper is a pioneering work about the incidence of latent sector errors i.e., errors that go undetected until the corresponding disk sectors are accessed. The study analyze factors that impact latent sector errors, observe trends, and explore their implications on the design of reliability mechanisms in storage systems.

2016:
Bhuvan Urgaonkar, Giovanni Pacifici, Prashant Shenoy, Mike Spreitzer, and Asser Tantawi. "An analytical model for multi-tier internet services and its applications." In Proceedings of ACM SIGMETRICS 2005.
This paper focuses on the problem of analytically modeling the behavior of such applications. It presents a model based on a network of queues, where the queues represent different tiers of the application.

2015:
Andrew W. Moore and Denis Zuev. "Internet Traffic Classification Using Bayesian Analysis Techniques." In Proceedings of ACM SIGMETRICS 2005.
This paper was one of the first to bring Bayesian techniques to bear on traffic classification, spawning a whole new research area that has continued to increase in activity and importance every year. Additionally, the techniques proposed in the paper were independently a valuable contribution to the field of machine learning.

2014:
Stephen Blackburn, Perry Cheng, and Kathryn McKinley. "Myths and Realities: the Performance Impact of Garbage Collection." In Proceedings of ACM SIGMETRICS '04/PERFORMANCE '04.
This paper explores and quantifies garbage collection behavior for three canonical algorithms which encompass the key mechanisms and policies from which essentially all garbage collectors are composed. The study is unique in its breadth of garbage collection algorithms and its depth of analysis, and its observations are still resonating a decade after its publication.

2013:
Yin Zhang, Matthew Roughan, Nick Duffield, and Albert Greenberg. "Fast Accurate Computation of Large-Scale IP Traffic Matrices from Link Loads." In Proceedings of ACM SIGMETRICS 2003.
The paper presented a novel, remarkably fast, and accurate method for practical and rapid inference of traffic matrices in IP networks from link load measurements, augmented by readily available network and routing configuration information.

2012:
Tian Bu, N Duffield, FL Presti, and D. Towsley. "Network Tomography on General Topologies." In Proceedings of ACM SIGMETRICS 2002.
This paper is a pioneering work in network tomography and it presented novel and formal approaches to perform tomography on networks under general setting, from which various performance, e.g., delay, packet lost,..etc., can be estimated.

2011:
Yang-hua Chu, Sanjay Rao, and Hui Zhang. "A Case for End System Multicast." In Proceedings of ACM SIGMETRICS 2000.
This paper demonstrated that multicast functionality could be provided at end systems using an overlay network, with only modest performance penalties.

Lixin Gao and Jennifer Rexford. "Stable Internet Routing without Global Coordination." In Proceedings of ACM SIGMETRICS 2000.
This paper provided a formal analysis of BGP routing policies, and showed how to ensure convergence to stable Internet routes without requiring routers to divulge their BGP configurations.

2010:
Jeffrey P. Buzen. "Fundamental Laws of Computer System Performance." In Proceedings of ACM SIGMETRICS 1976.
This paper laid the groundwork for operational analysis.

Derek Eager, Ed Lazowska, and John Zahorjan. "A Comparison of Receiver-initiated and Sender-initiated Adaptive Load Sharing." In Proceedings of ACM SIGMETRICS 1985.
This paper provided fundamental results for practical load balancing strategies across a large number of servers in a distributed system.

Mark E. Crovella and Azer Bestavros. "Self-similarity in World Wide Web Traffic: Evidence and Possible Causes." In Proceedings of ACM SIGMETRICS 1996.
This paper explained the impact of the distribution of WWW document sizes on the buildup of self-similar traffic in the Internet.

Go back to top.

ACM SIGMETRICS Doctoral Dissertation Award

The SIGMETRICS Doctoral Dissertation award recognizes excellent thesis research by doctoral candidates in the field of performance evaluation analysis of computer systems. The award winner will receive a plaque, a $1,000 honorarium, and a complimentary registration to the ACM SIGMETRICS conference. The SIGMETRICS Doctoral Dissertation Award winner and up to two honorable mentions will be recognized at the annual ACM SIGMETRICS conference.

Eligibility:

  • The final dissertation defense should take place at the nominee’s host institution during the 12 months prior to the submission deadline and not earlier than the previous submission deadline. Each submitted doctoral dissertation must be on a topic related to the measurement, modeling, analysis, and/or design of computing systems and networks. Of particular interest is work that presents new performance evaluation methods or that creatively applied previously developed methods to make predictions about, or gain insights into, key design tradeoffs in a variety of computing, networked, and cyber-physical systems. The determination of whether a thesis is in scope for the award will be made by the SIGMETRICS Doctoral Dissertation Award Committee.
  • An English-language version of the dissertation must be submitted with the nomination.
  • A dissertation can be nominated for both the SIGMETRICS Doctoral Dissertation Award and the ACM Doctoral Dissertation Award.
  • A supervisor can nominate a maximum of two PhD students in the same year.

Important dates:

  • Submission deadline: September 15, 2024.
  • Notification: November 15, 2024.

Submission procedure:

All nomination materials must be submitted electronically by the supervisor to the 2024 committee chair, Urtzi Ayesta (urtzi.ayesta@irit.fr). Please include "SIGMETRICS DDA 2024" in the title. Nominations must be received by the submission deadline and must be submitted in English. Late submissions will not be considered. Supervisors of co-supervised candidates should coordinate to ensure that only one nomination per candidate is submitted to the committee.

Nominations for the award must include:

  • A statement summarizing the candidate’s PhD thesis contributions and potential impact, and justification of the nomination. Please address the candidate's involvement and contributions with the SIGMETRICS or Performance community. No more than two pages;
  • A list of papers published within the candidate's thesis;
  • A copy of the PhD thesis itself;
  • Two endorsement letters supporting the nomination including the significant PhD thesis contributions of the candidate. Each endorsement should be no longer than 2 pages with a clear specification of the nominee’s PhD thesis contributions and potential impact;
  • A concise statement (one sentence) of the PhD thesis contribution for which the award is being given. This statement will appear on the plaque and on the SIGMETRICS website.

PDF format is required for all materials. ACM's conflict-of-interest guidelines apply to all award nominations.

The 2024 Doctoral Dissertation Award committee comprises Urtzi Ayesta (chair), Giuliano Casale, Weina Wang, Bo Jiang, and Daniel Sadoc Menasche. Questions should be sent to the committee chair.

Past winners

2023:
Isaac Grosof (winner)
Carnegie Melon University
Advisor: Mor Harchol-Balter
Optimal Scheduling in Multiserver Queues
Press release

Prakirt Raj Jhunjhunwala (honorable mention)
Georgia Institute of Technology
Advisor: Siva Theja Maguluri
Design and Analysis of Stochastic Processing and Matching Networks

Sean Sinclair (honorable mention)
Cornell University
Advisors: Christina Lee Yu and Siddartha Banerjee
Adaptivity, Structure, and Objectives in Sequential Decision-Making

2022:
Ziv Scully (winner)
Carnegie Melon University
Advisor: Mor Harchol-Balter
A New Toolbox for Scheduling Theory
Press release

Anish Agarwal (honorable mention)
Massachusetts Institute of Technology
Advisors: Alberto Abadie, Munther Dahleh, and Devavrat Shah
Causal Inference for Social and Engineering Systems

Zaiwei Chen (honorable mention)
Georgia Institute of Technology
Advisors: Siva Theja Maguluri and John Paul Clarke
A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms


Go back to top.

Paper awards

This list is incomplete. Please notify the SIG Chair, Mor Harchol-Balter (harchol@cs.cmu.edu) if you have information on missing entries.

2024:

2023:

2022:

  • Best paper award:
    "WISEFUSE: Workload Characterization and DAG Transformation for Serverless Workflows" by Ashraf Mahgoub (Purdue University), Edgardo Barsallo Yi (Purdue University), Karthick Shankar (Carnegie Mellon University), Eshaan Minocha (Purdue University), Somali Chaterji (Purdue University), Sameh Elnikety (Microsoft Research), and Saurabh Bagchi (Purdue University).
  • Stephen S. Lavenberg and Kenneth C. Sevcik Best Student Paper Award:
    "Offline and Online Algorithms for SSD Management" by Tomer Lange (Technion - Israel Institute of Technology), Joseph (Seffi) Naor (Technion - Israel Institute of Technology), and Gala Yadgar (Technion - Israel Institute of Technology).

2021:

  • Best paper award:
    "Nudge: Stochastically Improving upon FCFS" by Isaac Grosof (Carnegie Mellon University), Kunhe Yang (Tsinghua University), Ziv Scully (Carnegie Mellon University), Mor Harchol-Balter (Carnegie Mellon University).
  • Kenneth C. Sevcik Best Student Paper Award:
    "A Look Behind the Curtain: Traffic Classification in an Increasingly Encrypted Web" by Iman Akbari (University of Waterloo), Mohammad A. Salahuddin (University of Waterloo), Shi-Han Wen (University of Waterloo), Noura Limam (University of Waterloo), Raouf Boutaba (University of Waterloo), Bertrand Mathieu (Orange Labs), Stephanie Moteau (Orange Labs), Stephane Tuffin (Orange Labs).

2020:

2019:

2018:

2017:

2016:

2015:

  • Best Paper Award:
    "Spy vs. Spy: Rumor Source Obfuscation" by Giulia Fanti (University of California Berkeley); Peter Kairouz (University of Illinois at Urbana-Champaign); Sewoong Oh (University of Illinois at Urbana-Champaign); Pramod Viswanath (University of Illinois at Urbana-Champaign)
  • Kenneth C. Sevcik Outstanding Student Paper Award:
    "Fisher Information-based Experiment Design for Network Tomography" by Ting He (IBM T. J. Watson Research Center); Chang Liu (University of Massachusetts Amherst); Ananthram Swami (Army Research Lab); Don Towsley (University of Massachusetts Amherst); Theodoros Salonidis (IBM T. J. Watson Research Center); Andrei Iu. Bejan (University of Cambridge); Paul Yu (Army Research Lab)

2014:

2013:

2012:

2011:

2010:

2009:

2008:

2007:

  • Best Paper Award:
    "Modeling the relative fitness of storage" by Michael Mesnier (Intel and Carnegie Mellon University); Matthew Wachs (Carnegie Mellon University), Raja R. Sambasivan (Carnegie Mellon University), Alice Zheng (Carnegie Mellon University), Gregory R. Ganger (Carnegie Mellon University).
  • Kenneth C. Sevcik Outstanding Student Paper Award:
    "An Analysis of Latent Sector Errors in Disk Drives" by Lakshmi Bairavasundaram (University of Wisconsin-Madison, US); Garth Goodson (Network Appliance, Inc); Shankar Pasupathy (Network Appliance, Inc); Jiri Schindler (Network Appliance, Inc).

2006:

2005:

2004:

2003:

2002:

2001

2000

1999

1998

1997

1996

1995