Profile of Prof. Timos Sellis

Prof. Timos Sellis received his diploma degree in Electrical Engineering in 1982 from the  National Technical University of Athens (NTUA), Greece. In 1983 he received the M.Sc. degree  from Harvard University and in 1986 the Ph.D. degree from the University of California  at Berkeley, where he was a member of the INGRES group, both in Computer Science.  In 1986, he joined the Department of Computer Science of the University of Maryland, College Park as an Assistant Professor, and became an Associate Professor in 1992.  Between 1992 and 1996 he was an Associate Professor at the Computer Science Division  of NTUA, where he is currently a Full Professor.  Prof. Sellis is also the head of the  Knowledge and Database Systems Laboratory at NTUA. His research interests include peer-to-peer database systems, data warehouses, the integration of Web and databases, and spatial database systems.  He has published over 140 articles in refereed journals and international conferences in the above areas and has been invited speaker in major international events..Prof. Sellis is a recipient of the prestigious Presidential Young Investigator (PYI) award  given by the President of USA to the most talented new researchers (1990), and of the VLDB 1997 10-Year Paper Award for his work on spatial databases.  He was the president of the National Council for Research and Technology of Greece (2001-2003) and a member of the VLDB Endowment (1996-2000).  He also serves as a member of the ACM SIGMOD Advisory Board.ABSTRACTPeer-to-peer (P2P) computing has attracted a lot of attention both in academia and industry. In P2P systems, autonomous peers (computers) are all treated in a uniform way, they can join and leave the system at any time, and essentially they form a large distributed system.  Although keyword searching and routing in such networks has received a lot of activity in the last few years, only a few researchers have addressed the case where peers hold non-traditional types of information or even complete (say relational) database management systems.  On the other hand, research in distributed, heterogeneous database systems has been around for many years; however, the database community has only recently started working on enhancing P2P systems with data management capabilities. In this talk we will focus on two major problems that deal with these issues: first, we describe problems and challenges in query processing on P2P networks. In such networks, peers hold structured databases and each peer holds some mappings with some other peers; such mappings allow peers to exchange information by translating (according to these mappings) attributes so as to fit their schemas. The standard practice of answering a query, is to consecutively re-write it along the propagation  path, which often results in significant loss of information. We will present an adaptive and bandwidth-efficient solution to the problem in the context of an unstructured, purely decentralized  system. Our method allows peers to individually choose which rewritten version of a query to answer, and discover information-rich sources left hidden otherwise. The second problem deals with extending searching and routing algorithms in the case where peers hold spatial information. Until recently, research has focused mostly on P2P systems that host one-dimensional data (i.e. strings, numbers, etc).  However, the need for P2P applications with multi-dimensional data is emerging. Yet, existing indexing and search techniques are not suitable for such applications: most indices for multi-dimensional data have been developed for centralized environments.  Our focus is on structured P2P systems that share spatial information. We present a totally decentralized indexing and routing technique that is suitable for spatial data, i.e. it handles P2P applications in which spatial information of various sizes can be dynamically inserted or deleted, and peers can join or leave. The proposed technique preserves well locality, and supports efficient routing especially for popular and/or close areas.