Highly scalable multiprocessing algorithms for preference-based database retrieval

  • Authors:

  • Joachim Selke;Christoph Lofi;Wolf-Tilo Balke

  • Affiliations:

  • Institut für Informationssysteme, Technische Universität Braunschweig, Braunschweig, Germany;Institut für Informationssysteme, Technische Universität Braunschweig, Braunschweig, Germany;Institut für Informationssysteme, Technische Universität Braunschweig, Braunschweig, Germany

  • Venue:
  • DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
  • Year:
  • 2010

Quantified Score

Hi-index 0.01

Visualization

Abstract

Until recently algorithms continuously gained free performance improvements due to ever increasing processor speeds. Unfortunately, this development has reached its limit. Nowadays, new generations of CPUs focus on increasing the number of processing cores instead of simply increasing the performance of a single core. Thus, sequential algorithms will be excluded from future technological advances. Instead, highly scalable parallel algorithms are needed to fully tap new hardware potentials. In this paper we establish a design space for parallel algorithms in the domain of personalized database retrieval, taking skyline algorithms as a representative example. We will investigate the spectrum of base operations of different retrieval algorithms and various parallelization techniques to develop a set of highly scalable and high-performing skyline algorithms for different retrieval scenarios. Finally, we extensively evaluate these algorithms to showcase their superior characteristics.