##### 12:45 PM, Thursday, November 15th, 2001

Room 104, Gates Computer Science Building

## Global Network
Positioning: A New Approach to Internet Network Distance
Prediction

T.S. Eugene Ng

Carnegie Mellon
University

**Slides:** [PPT]

**About the talk:**

To optimize the performance of large-scale distributed applications
such as Napster or Gnutella file sharing and end system multicast, one
must know the performance of a large number of underlying network
paths. Although active network measurement can accurately determine
network performance, it suffers from scalability and timeliness
limitations. We believe the ability to accurately predict network
distance (round-trip transmission and propagation delay) without
active measurement is a fundamental building block in enabling
scalable, fast, and effective performance optimization in such
large-scale distributed applications.

In this talk, I will present a new approach to predict Internet
network distance called Global Network Positioning (GNP). The key idea
is to model the Internet as a geometric space (e.g. a 3-dimensional
Euclidean space) and distributedly compute geometric coordinates to
characterize the positions of hosts in the Internet. The modeled
geometric distances between hosts are then used to predict the network
distances. I will contrast GNP to the state-of-the-art network
distance prediction approach called IDMaps and argue that GNP is more
scalable and more nimble. I will also discuss a variety of technical
issues in GNP such as what geometric space model fits the Internet
well. Through Internet experiments, I will show that the geometric
distances implied by the GNP host coordinates can accurately predict
Internet network distances.

**About the speaker:**

T.S. Eugene Ng is a Ph.D. student in Computer Science at Carnegie
Mellon University. His current research focuses on scalable Internet
network performance prediction and studying its benefits to a variety
of applications.