Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/74053
Title: Experimental analysis of the application of the gsketch partitioning method onto the gmatrix graph-stream sketch
Authors: Lim, Eric Leonardo
Keywords: DRNTU::Engineering::Computer science and engineering::Data::Data structures
Issue Date: 2018
Abstract: This report presents a final year project that is about an experimental analysis of applying the gSketch partitioning method onto the gMatrix graph-stream sketch. The report first introduces how the gSketch partitioning method can be applied onto the gMatrix sketch and proposes optimizations for the method, and then analyzes how the gSketch partitioning method changes how gMatrix answers various query types, such as edge frequency, heavy-hitter edges, and node aggregate-frequency queries, and how the performance and probabilistic accuracy guarantees change, and after that, shows experimental results with metrics that each evaluates differently how partitioning affects gMatrix's accuracy for answering the different query types on up to three different graph-stream datasets. Finally, the report concludes that the gSketch partitioning method successfully improves the accuracy of gMatrix in query types such as edge frequency estimation and source-node aggregate-frequency estimation, although fails to bring the same improvements onto the destination-node aggregate-frequency estimation and heavy-hitter edge queries.
URI: http://hdl.handle.net/10356/74053
Schools: School of Computer Science and Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
fyp.pdf
  Restricted Access
398.8 kBAdobe PDFView/Open

Page view(s)

360
Updated on Mar 20, 2025

Download(s)

13
Updated on Mar 20, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.