Data Engineering deals with the use of engineering techniques and methodologies in the design, development and assessment of information systems for different computing platforms and application environments. The 24th IEEE International Conference on Data Engineering will continue in its tradition of being a premier forum for presentation of research results and advanced data-intensive applications and discussion of issues on data and knowledge engineering. The mission of the conference is to share research solutions to problems of today's information society and to identify new issues and directions for future research and development work.
We are both interested in analyzing and to characterize aggregate Internet traffic and the traffic generated by specific applications (games, http, peer-to-peer,..).Our measurement approach is multi-level (sessions, connections, flows, packets, ..) but with a major focus on packet-level analysis. With a packet-level analysis we mean an approach in terms of packet size and inter-packet time. Such modeling approach is simple and at the same time offers the lowest/deepest point of view of network traffic. Network devices (Routers, Switches, Access Points) often operate on a packet-by-packet basis (i.e. buffer management), and network problems (Loss, Delay, Jitter) happen at packet level. Other advantages of studying traffic by observing IPT and PS are the avoidance of any assumption regarding the application-layer protocol characteristics, and the possibility to study, in the same manner, different kind of sources and even mixes of them.
This is the DCCP-TP Wiki. DCCP-TP is a fresh-start implementation of the Datagram Congestion Control Protocol (DCCP) optimized for portability. This site provides source code downloads and documentation for DCCP-TP.
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic. Minho Sung, Abhishek Kumar, Li Li, Jia Wang, Jun Xu. To appear in the Proc. of 2nd IEEE International Workshop on Networking Meets Databases (NetDB'06), April 2006. Sketch Guided Sampling -- Using On-Line Estimates of Flow Size for Adaptive Data Collection. Abhishek Kumar, Jun (Jim) Xu. To appear in the proceedings of IEEE Infocom'06, Barcelona, Spain, April 2006.
B. Gold, A. Ailamaki, L. Huston, and B. Falsafi. DaMoN '05: Proceedings of the 1st international workshop on Data management on new hardware, page 1. New York, NY, USA, ACM, (2005)
S. Das, D. Agrawal, and A. Abbadi. DaMoN '08: Proceedings of the 4th international workshop on Data management on new hardware, page 1--10. New York, NY, USA, ACM, (2008)
N. Bandi, A. Metwally, D. Agrawal, and A. Abbadi. SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, page 247--256. New York, NY, USA, ACM, (2007)
C. Cranor, T. Johnson, O. Spataschek, and V. Shkapenyuk. SIGMOD '03: Proceedings of the 2003 ACM SIGMOD international conference on Management of data, page 647--651. New York, NY, USA, ACM, (2003)
D. Agrawal, and A. Abbadi. DaMoN '05: Proceedings of the 1st international workshop on Data management on new hardware, page 1. New York, NY, USA, ACM, (2005)