Ryan Huebsch and Shawn Ryan Jeffery

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-04-1339
July 2004

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2004/CSD-04-1339.pdf

In response to the ever increasing scale, distribution, and complexity of data processing, database research in the past few years has focused on adaptive query processing. However, many of these solutions, although aimed at processing wide-area data, remain centralized solutions. In this paper, we present FREddies, an extension of the centralized Eddy operator for use in a P2P query processing system. FREddies operate within the framework of PIER, a DHT-based P2P query processor. FREddies optimize the query during runtime and require no global knowledge. We show that FREddies using rudimentary routing policies can perform competitively with a traditional static query optimization approach. Furthermore, we validate our simulation results in the real world environment of PlanetLab.

BibTeX citation:

@techreport{Huebsch:CSD-04-1339,
    Author = {Huebsch, Ryan and Jeffery, Shawn Ryan},
    Title = {FREddies: DHT-Based Adaptive Query Processing via FedeRated Eddies},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2004},
    Month = {Jul},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2004/5466.html},
    Number = {UCB/CSD-04-1339},
    Abstract = {In response to the ever increasing scale, distribution, and complexity of data processing, database research in the past few years has focused on adaptive query processing. However, many of these solutions, although aimed at processing wide-area data, remain centralized solutions. In this paper, we present FREddies, an extension of the centralized Eddy operator for use in a P2P query processing system. FREddies operate within the framework of PIER, a DHT-based P2P query processor. FREddies optimize the query during runtime and require no global knowledge. We show that FREddies using rudimentary routing policies can perform competitively with a traditional static query optimization approach. Furthermore, we validate our simulation results in the real world environment of PlanetLab.}
}

EndNote citation:

%0 Report
%A Huebsch, Ryan
%A Jeffery, Shawn Ryan
%T FREddies: DHT-Based Adaptive Query Processing via FedeRated Eddies
%I EECS Department, University of California, Berkeley
%D 2004
%@ UCB/CSD-04-1339
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2004/5466.html
%F Huebsch:CSD-04-1339