Abstract:

Peer-to-peer (P2P) computing has received a lot of attention due 
to the popularity of applications such as SETI, Napster, Gnutella, 
Morpheus and BitTorrent. For a P2P system holding massive amount
of data, efficient search for resources (such as data or services) 
is a key determinant to its scalability. In the pervasive data 
access (PDA) researc group of Penn State, we are developing data
management techniques in support of complex queries and 
applications on P2P networks. In this talk, I will briefly review 
some techniques we developed and present the design of an overlay 
network, called semantic small world (SSW), that facilitates 
efficient multi-dimensional search in P2P systems. SSW is based on 
three innovative ideas: 1) small world network; 2) semantic 
clustering; and 3) dimension reduction. It achieves a very 
competitive trade-off between the search latencies/traffic and 
maintenance overheads in large-scale network. In addition, SSW
is adaptive to distribution of data and locality of interest; is
very resilient to failures; and has good load balancing property.


Biography:

Wang-Chien Lee received his Ph.D. degree from Ohio State 
University. 
He is currently an Associate Professor of Computer Science and 
Engineering at Pennsylvania State University, where he leads the 
Pervasive Data Access (PDA) Research Group to pursue cross-area 
research in database systems, pervasive/mobile computing, and 
networking. He is particularly interested in developing data 
management techniques (including accessing, routing, 
indexing, caching, aggregation, dissemination, and query 
processing) for supporting complex queries and location-based 
services in a wide spectrum of networking and mobile environments 
such as peer-to-peer networks, mobile ad-hoc networks, wireless 
sensor networks, and wireless broadcast systems. Meanwhile, he also 
works on XML, security, information integration/retrieval, and 
object-oriented databases. He has published more than 140 technical 
papers on these topics. Dr. Lee's research has been supported by 
multiple NSF grants.