[DB Seminar] Summer 2018: Nikos R. Katsipoulakis

The increasing need for real-time data processing has triggered the rapid evolution of distributed Stream Processing Engines (dSPEs). In a dSPE, data are processed as soon as they become available and queries execute continuously. Low operational cost and timely processing can become a challenge for a dSPE, considering the volatile and uncharted nature of input streams. This calls for adaptable dSPEs, which can react to fluctuations in processing demands. In this talk, I will present work done on dSPEs’ adaptability, focusing on the techniques of stream partitioning, load shedding, and dSPE elasticity.

Bio:
Nikos is a fifth-year Ph.D. Candidate at the University of Pittsburgh. He is a member of the Advanced Data Management Technologies Lab, working with Alexandros Labrinidis and Panos K. Chrysanthis. In his dissertation work, he investigated the adaptability of distributed stream processing engines. Prior to his Ph.D. Studies, he earned a M.S. Degree from the University of Pittsburgh and a B.S. Degree from the University of Athens, Greece.