XIA, Carnegie Mellon University
Srini Seshan and Peter Steenkiste
I work under the umbrella of the eXpressive
Internet Architecture (XIA) project, a large-scale
research project funded by the National Science Foundation (NSF) to effectively design, implement, and
evaluate a clean-slate redesign of core internet functionality. XIA seeks
to mainly improve the evolvability of the network by providing a simple framework to
allow deployment of future means of communication, in addition to providing incredibly
flexible routing and intrinsic security.
Video Delivery Network (VDN), Carnegie Mellon University
Srini Seshan, Dongsu Han, and Hui Zhang
It's becoming more and more apparent that video delivery is the major use case of the Internet.
Content delivery networks (CDNs) have been mainly focused on providing good quality
video on demand (VoD), but live video delivery is often retrofitted to
VoD control systems as an after-thought, or ignored entirely. We design and evaluate a system that treats delivering high-quality,
highly-scalable, responsive live video as its primary goal; a Video Delivery Network (VDN). VDN
uses integer programming at a centralized controller to deliver high-quality video, while
simultaneously leveraging intelligence at individual server clusters to make real-time decisions
based on local information. This split of intelligence between global control and local control
(which we dub hybrid control) allows VDN to be highly responsive to failures and user events. We evaluate this work on
real traces as well as on Amazon's EC2 cloud, showing that VDN can delivery high-quality, highly-scalable,
responsive live video streams.
Publication: in submission...
Understanding Incremental Deployment, Carnegie Mellon University
Srini Seshan and Peter Steenkiste
The focus of this work is building a fundamental understanding of incremental
deployability of new network architectures. Although IPv6 has been around for decades,
ease of deployment over IPv4 is still a major concern. My work focused on distilling down
four key problems that network architectures need to solve in order to be deployable. We
further examine a variety of specific mechanisms that solve these problems, creating a design space of
options. We evaluate a select few of these options (modeling current IPv6 deployment
techniques as well as XIA) across the US using PlanetLab as a testbed. We find that certain
mechanisms prominently featured in XIA (multiple discrete identifiers and fallbacks in
forwarding) as well as control plane centralization can help aid in virtually seamless
deployment of new network architectures.
Matthew K. Mukerjee, Dongsu Han, Srinivasan Seshan, and Peter Steenkiste.
2013. Understanding tradeoffs in incremental deployment of new network architectures. CoNEXT '13,
BiFocals, Cornell University
Daniel Freedman and Ken Birman
I worked with members of the BiFocals project to research into the cause and effect of
high-speed 10 GbE fiber-optic wide-area network burstiness. The burstiness in question
happens at a timescale so small (order of microseconds) that conventional computer
science techniques (userland software, kernel time-stamping, NIC level time-stamping,
etc.) are entirely unable to see these bursts. We thus used high-precision physics
equipment to measure the packets in-flight on the actual fiber. These bursts provide
an instantaneous data rate of 10 Gbps, potentially overwhelming commodity endpoint
servers. We show through experimentation that various common endpoint configurations can
provide radically different loss for the same bursty stream.
NeuroPhone, Dartmouth College
Andrew Campbell, Tanzeem Choudhury, Rajeev Raizada
This work focused on probing the intersections of neuroscience and
mobile. Given the existence of commodity ("toy") electroencephalography (EEG) headsets ($<300) what are possible
applications in the space of mobile? Our system (NeuroPhone) provides a cursory glance
at a possible applications in that space, a "brain-powered" address book. The mobile
phone presents pictures of contacts on the display and the EEG headset recognizes which
contact the user wished to call, due to the contact they expect to appear eliciting a specific
brain response ("P300"). This work eventually lead to an NSF EAGER grant.
Campbell, A. T., T. Choudhury, S. Hu, H. Lu, M. K. Mukerjee, M. Rabbi,
R. D. S Raizada. NeuroPhone: Brain-Mobile Phone Interface using a Wireless
EEG Headset. SIGCOMM 2010 - MobiHeld 2010, August 2010.