Research

Stochastic systems with applications in data centers and cloud computing

I am interested in characterizing fundamental limits of large-scale computing systems that address emerging demands from big-data analytics, and designing algorithms with optimality on throughput and latency performance. My research in this area focuses on the following aspects.

  • Latency characterization. Latency is a crucial performance metric in technologies nowadays, especially in interactive applications such as real-time machine learning, online transactions, and video streaming. Amazon has calculated that a page load slowdown of just one second can cost $1.6 billion in sales each year. My research in this area provides tight characterizations of latency in large-scale computing systems, enabling identification of performance bottlenecks and informing optimal designs of scheduling and resource allocation algorithms.

  • Coordination of data and computation. Big-data analytics has led to a paradigm shift from computation-centric computing systems to systems where data plays an equally, if not more, important role. Data and computation are closely correlated in present computing systems. For example, data-parallel frameworks such as MapReduce/Hadoop and Spark associate a computing task with a chunk of data, where the computation can be executed only when both the associated data and a computation slot on servers are available. My research takes the lead in addressing the coordination of data and computation, and designs scheduling algorithms with rigorous theoretical guarantees on performance optimality.

  • Large-scale regimes. To accommodate the growing computational demand, modern data centers are scaled up in size, consisting of tens of thousands of servers. Such large-scale systems have attracted great attention both from practice and from theoretical research. My research investigates the scaling behavior of performance with respect to the size of system infrastructures, including the number of servers, the number of communication links, etc. My research further explores new large-scale regimes to capture the large volume of data. In particular, I study jobs whose sizes expand as the system scales, which models the trend that computational jobs are processing larger and larger volumes of data.

Data privacy

I work on data privacy and its intersection with other areas including game theory, information theory and statistics. Our recent focus is a new, market model that we envisage for collecting private data where data subjects (individuals) retain full control of their privacy. I aim to understand the economic fundamentals of collecting private data and design optimal incentive mechanisms.

Publications Preprints

[Stochastic systems] [Data privacy] [Graph statistics] [Systems]

Stochastic systems

  • The M/M/k with deterministic setup times
    Jalani K. Williams, Mor Harchol-Balter, Weina Wang
    ACM SIGMETRICS, 2023. [pdf]

  • Maximizing utilization under time-varying resource requirements
    Yige Hong, Qiaomin Xie, Weina Wang
    Preprint, 2022. [arXiv]

  • Sharp waiting-time bounds for multiserver jobs
    Yige Hong, Weina Wang
    ACM MobiHoc, 2022. [arXiv]

  • Tackling heterogeneous traffic in multi-access systems via erasure coded servers
    Tuhinangshu Choudhury, Weina Wang, Gauri Joshi
    ACM MobiHoc, 2022. [arXiv]

  • On low-complexity quickest intervention of mutated diffusion processes through local approximation
    Qining Zhang, Honghao Wei, Weina Wang, Lei Ying
    ACM MobiHoc, 2022. [arXiv]

  • Beyond response time: scheduling to speed up convergence in machine learning
    Weina Wang
    ‘100 views on queues’, Volume 100 of Queueing Systems, 2022. [DOI]

  • Probing to minimize
    Weina Wang, Anupam Gupta, Jalani K. Williams (random author order)
    ITCS, 2022. [DOI] [pdf]

  • The case for phase-aware scheduling of parallelizable jobs
    Benjamin Berg, Justin Whitehouse, Benjamin Moseley, Weina Wang, Mor Harchol-Balter
    IFIP Performance, 2021. [pdf]

  • Job dispatching policies for queueing systems with unknown service rates
    Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai
    ACM MobiHoc, Jul. 2021. [DOI] [arXiv]

  • Zero queueing for multi-server jobs
    Weina Wang, Qiaomin Xie, Mor Harchol-Balter
    ACM SIGMETRICS, Jun. 2021. [DOI] [arXiv]

  • Achieving zero asymptotic queueing delay for parallel jobs
    Wentao Weng, Weina Wang
    ACM SIGMETRICS, Jun. 2021. [DOI] [arXiv]

  • Optimal resource allocation for elastic and inelastic jobs
    Benjamin Berg, Mor Harchol-Balter, Benjamin Moseley, Weina Wang, Justin Whitehouse
    ACM SPAA, Jul. 2020. [DOI] [pdf]

  • QuickStop: A Markov optimal stopping approach for quickest misinformation detection
    Honghao Wei, Xiaohan Kang, Weina Wang, Lei Ying
    ACM SIGMETRICS, Phoenix, AZ, Jun. 2019. [DOI] [pdf]

  • Delay asymptotics and bounds for multi-task parallel jobs
    Weina Wang, Mor Harchol-Balter, Haotian Jiang, Alan Scheller-Wolf, R. Srikant
    Queueing Systems Jan. 2019. [DOI] [QUESTA pdf]
    International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP Performance), Toulouse, France, Dec. 2018. [DOI]

  • Heavy-traffic insensitive bounds for weighted proportionally fair bandwidth sharing policies
    Weina Wang, Siva Theja Maguluri, R. Srikant, Lei Ying
    Mathematics of Operations Research, 2022. [DOI][arXiv]
    Heavy-traffic delay insensitivity in connection-level models of data transfer with proportionally fair bandwidth sharing
    Weina Wang, Siva Theja Maguluri, R. Srikant, Lei Ying
    International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP Performance), New York City, NY, Dec. 2017. [DOI]

  • Resource allocation for data-parallel computing in networks with data locality
    Weina Wang, Lei Ying
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2016. [DOI] [Allerton pdf]

  • Decentralized scheduling with data locality for data-parallel computation on Peer-to-Peer networks
    Weina Wang, Matthew Barnard, Lei Ying
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2015. [DOI] [Allerton pdf]

  • Data locality in MapReduce: A network perspective
    Weina Wang, Lei Ying
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2014. [DOI]
    Performance Evaluation, Feb. 2016. [DOI] [PEVA pdf]
    [technical report]

  • MapTask scheduling in MapReduce with data locality: throughput and heavy-traffic optimality
    Weina Wang, Kai Zhu, Lei Ying, Jian Tan, Li Zhang
    IEEE/ACM Transactions on Networking, Feb. 2016. [DOI] [ToN pdf]
    Map task scheduling in MapReduce with data locality: throughput and heavy-traffic optimality
    Weina Wang, Kai Zhu, Lei Ying, Jian Tan, Li Zhang
    IEEE International Conference on Computer Communications (INFOCOM), Turin, Italy, Apr. 2013. [DOI] [INFOCOM pdf]
    A throughput optimal algorithm for map task scheduling in mapreduce with data locality
    Weina Wang, Kai Zhu, Lei Ying, Jian Tan, Li Zhang
    ACM SIGMETRICS Performance Evaluation Review, Mar. 2013. [DOI]
    [poster]

  • On the performance of largest-deficit-first for scheduling real-time traffic in wireless networks
    Xiaohan Kang, Weina Wang, Juan José Jaramillo, Lei Ying
    IEEE/ACM Transactions on Networking, Feb. 2016. [DOI] [ToN pdf] [supplementary]
    ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), Bangalore, India, Jul. 2013. [DOI] [MobiHoc pdf]

Data privacy

  • Privacy-utility tradeoffs in routing cryptocurrency over payment channel networks
    Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh
    ACM SIGMETRICS, Jun. 2020. [DOI] [pdf]

  • Data collection from privacy-aware users in the presence of social learning
    Abdullah Basar Akbay, Weina Wang, Junshan Zhang
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2019. [DOI]

  • A winners-take-all incentive mechanism for crowd-powered systems
    Pengfei Jiang, Weina Wang, Yao Zhu, Jingrui He, Lei Ying
    Workshop on Economics of Networks, Systems and Computation (NetEcon), Jun. 2018. [DOI]

  • Buying data from privacy-aware individuals: The effect of negative payments
    Weina Wang, Lei Ying, Junshan Zhang
    Conference on Web and Internet Economics (WINE), Montreal, Canada, Dec. 2016. [DOI] [WINE pdf]
    [technical report]

  • The value of privacy: Strategic data subjects, incentive mechanisms and fundamental limits
    Weina Wang, Lei Ying, Junshan Zhang
    ACM Transactions on Economics and Computation, Aug. 2018. [DOI] [TEAC pdf]
    ACM SIGMETRICS, Antibes Juan-les-Pins, France, Jun. 2016. [DOI] [SIGMETRICS pdf]
    Kenneth C. Sevcik Outstanding Student Paper Award

  • A game-theoretic approach to quality control for collecting privacy-preserving data
    Weina Wang, Lei Ying, Junshan Zhang
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2015. [DOI] [Allerton pdf]
    [technical report]

  • A minimax distortion view of differentially private query release
    Weina Wang, Lei Ying, Junshan Zhang
    Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Nov. 2015. [DOI] [Asilomar pdf] [technical report]

  • On the relation between identifiability, differential privacy, and mutual-information privacy
    Weina Wang, Lei Ying, Junshan Zhang
    IEEE Transactions on Information Theory, Sep. 2016. [DOI] [TIT pdf]
    Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, Sep. 2014. [DOI]
    Poster presented at IEEE North American School of Information Theory, Toronto, Canada, Jun. 2014. [poster]

Graph statistics

  • On the Feasible Region of Efficient Algorithms for Attributed Graph Alignment
    Ziao Wang, Ning Zhang, Weina Wang, Lele Wang
    preprint, 2022. [arXiv]

  • Attributed graph alignment
    Ning Zhang, Weina Wang, Lele Wang
    IEEE ISIT, Jul. 2021. [arXiv]

Systems

  • SurgeProtector: Mitigating temporal algorithmic complexity attacks using adversarial scheduling
    Nirav Atre, Hugo Sadok, Erica Chiang, Weina Wang, Justine Sherry
    *ACM SIGCOMM, Aug. 2022. [DOI] [pdf]

  • Caching with delayed hits
    Nirav Atre, Justine Sherry, Weina Wang, Daniel Berger
    ACM SIGCOMM, Aug. 2020. [DOI] [pdf]

Machine learning

  • Almost Boltzmann exploration
    Harsh Gupta, Seo Taek Kong, Weina Wang, R. Srikant
    ArXiv, Jan. 2019. [link]

People

Faculty

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Weina Wang

Assistant Professor

PhD Students

Jalani Williams

PhD Student

Tuhinangshu Choudhury

PhD Student

Yige Hong

PhD Student

Alumni

Administration

Matt McMonagle

Administration

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