New Jersey Chapter

Date:
Wednesday March 5, 2014
Agenda:
6:00-6:30 Mixer
6:30-7:15 Dinner
7:15-7:30 Business Meeting
7:30-9:00 Presentation
Location:
100 Rockafeller Road, Piscataway, NJ 08854
Room 5110, Rutgers Business School, Livingston Campus, Rutgers University
Enter starting address to get directions: http://rumaps.rutgers.edu/location/lot-scarlet-lot-rac
Please click here for parking permit

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When less is more - Internet topology research and Big Data

Walter Willinger
Niksun, Inc., Princeton NJ

Dr. Willinger is Chief Scientist at Niksun, Inc., the world leader in real-time monitoring and cyber forensics solutions. Before joining Niksun, he worked at AT&T Labs-Research in Florham Park, NJ from 1996 to 2013 and at Bellcore Applied Research from 1986 to 1996. Dr. Willinger received his Dipl. Math. from the ETH Zurich and his M.S. and Ph.D. in Operations Research and Industrial Engineering from Cornell University. He is a Fellow of ACM (2005), Fellow of IEEE (2005), AT&T Fellow (2007), and Fellow of SIAM (2009), and co-recipient of the 1995 IEEE Communications Society W.R. Bennett Prize Paper Award, the 1996 IEEE W.R.G. Baker Prize Award, and the 2005 ACM/Sigcomm Test-of-Time Paper Award. His paper "On the Self-Similar Nature of Ethernet Traffic" is featured in "The Best of the Best - Fifty Years of Communications and Networking Research," a 2007 IEEE Communications Society book compiling the most outstanding papers published in the communications and networking field in the last half century.

Abstract

Internet topology research is concerned with the study of the various types of connectivity structures that are enabled by the layered architecture of the Internet. It has been largely driven by publicly available large datasets that have resulted from different Internet-wide measurement studies. Examples of such "big data" include the hundreds of millions of traceroute measurements that have been collected for the last two decades and the similarly huge volumes of control plane measurements in the form of BGP data. While collecting, processing, mining, and modeling these data has fascinated researchers for more than a decade, the actual value of the data for accurately discerning the Internet's physical connectivity structure (i.e., router-level topology) or logical graph abstraction known as Autonomous System or AS-level topology, has only recently come under intense scrutiny.

I will illustrate in this talk why despite all the available "big data", we still lack a basic view of the physical Internet and are only now realizing that the much-researched and popular Internet AS-level graphs miss a majority of links. In this sense, the much-heralded big data approach to Internet topology research has not led to insights that are consistent with Internet reality. I will use these examples to motivate new Internet research efforts that favor quality over quantity in future Internet measurement studies and that show why less can be more in the context of "big" Internet data.


2014 chapter dues of $10 for INFORMS National Member or $11 for Non-member may be paid at the door. Student or retiree dues: $3.00. Mixer and dinner (alter among pizza, Chinese, ... from meeting to meeting) cost is $10.00 ($3.00 for students) to be paid at the door.

Further information can be obtained by contacting Keh-Wei Lih at lih@att.com. Visit NJ INFORMS Chapter home page at http://rutcor.rutgers.edu/~lih/informs/njchap.html

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