Ganesh Ananthanarayanan



I am a Researcher in the Mobility and Networking group at Microsoft Research.

I finished my Ph.D. in the AMP Lab at Berkeley in Dec 2013, advised by Ion Stoica.

Email: ga@microsoft.com


Research

I'm interested in all aspects of systems and networking. My current research focus:

  • Video Processing: Cameras are everywhere! Large-scale video processing is a grand challenge representing an important frontier. With the rising popularity of Internet of Things videos from factory floors, traffic and police, and retail shops, cameras represent the most challenging of the "things" in terms of data volume, (vision) processing algorithms, response latencies, and security sensitivities. [NSDI’17]

  • Internet Performance - Bringing Big Data to Networking: Companies like Microsoft have multiple services with worldwide clients that continuously measure performance. Using this large scale data, orders of magnitude more than prior studies, we seek to better understand network performance and create a continuous performance map of the Internet. [SIGCOMM’16][PinDrop]

  • Geo-distributed Analytics: The next generation of big data analytics will no longer be confined to one datacenter but happen across multiple datacenters, edge clusters etc. How will the infrastructure for geo-distributed analytics look like? [OSDI’16-a] [SIGCOMM’15-a]

  • Datacenter Resource Management: Resource management is critical for large scale clusters executing complex computations. We design scheduling solutions - straggler mitigation, fairness, packing, etc. - based on theoretically-founded principles while considering multiple resources (CPU, memory, disk, network). [OSDI’16-b][SIGCOMM’15-b][OSDI’14][SIGCOMM’14][NSDI’14]

Selected Publications: (Full List)

  • Live Video Analytics at Scale with Approximate and Delay-Tolerant Processing
    H. Zhang, G. Ananthanarayanan, P. Bodik, M. Philipose, P. Bahl, M. J. Freedman
    USENIX NSDI, Boston, MA, Mar 2017.

  • Via: Improving Internet Telephony Call Quality Using Predictive Relay Selection
    J. Jiang, R. Das, G. Ananthanarayanan, P. A. Chou, V. N. Padmanabhan, V. Sekar, E. Dominique, M. Goliszewski, D. Kukoleca, R. Vafin, H. Zhang
    ACM SIGCOMM, Florianopolis, Brazil, Aug 2016.

  • Low Latency Geo-distributed Data Analytics
    Q. Pu, G. Ananthanarayanan, P. Bodik, S. Kandula, A. Akella, P. Bahl, I. Stoica
    ACM SIGCOMM, London, UK, Aug 2015.

Please see my Ph.D. thesis (Dec 2013) and statement (Apr 2013) for my graduate research.

Selected Talks:

  • Geo-distributed Data Analytics [pptx]
    Univ. of Wisconsin, Madison, Oct 2015.
  • Big Data Analytics with Parallel Jobs [pptx]
    Univ. of Illinois, Urbana-Champaign, Mar 2013.
  • Effective Straggler Mitigation: Attack of the Clones [pptx] [pdf]
    AMPLab Summer Retreat, May 2012 and Hortonworks Inc., Nov 2012.
  • PACMan: Coordinated Memory Caching for Parallel Jobs [pptx] [pdf]
    Intel ISTC-CC Retreat, Nov 2012, and VMWare Inc., May 2012.
  • Coordinated In-Memory Caching for Data Intensive Clusters [pptx] [pdf]
    Yahoo! Research, Jun 2011 and Huawei Technologies Co. Ltd., Jul 2011.
  • Disk-Locality in Datacenter Computing Considered Irrelevant [pptx] [pdf]
    USENIX HotOS, May 2011 and Berkeley Cloud Seminar, Feb 2011.
  • Scarlett: Coping with Skewed Popularity Content in MapReduce Clusters [pptx] [pdf]
    Hortonworks Inc., Jul 2011, Cloudera Inc., Apr 2011, and Facebook Inc., Nov 2010.
  • Reining in the Outliers in MapReduce Clusters using Mantri [pptx] [pdf]
    Yahoo! Research, Nov 2010.