Log analysis technique: Picviz

dc.contributorHong, Xiaoyan
dc.contributorVrbsky, Susan V.
dc.contributorLi, Shuhui
dc.contributor.advisorXiao, Yang
dc.contributor.authorSen, Shraddha Pradip
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2017-03-01T14:46:07Z
dc.date.available2017-03-01T14:46:07Z
dc.date.issued2011
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractLog data that is generated during a number of processes such as Networking, Web surfing, Failures, etc. is quite large. Such log data are supposed to be processed and analyzed so that it can be used to improve the quality of the software, improve its performance, proactive fault detection and handling. There are a number of log analysis techniques that have been presented over the years. Picviz is one such technique. Picviz is a parallel co-ordinate plot which is used to display huge amounts of data for security purposes. The data can be displayed in multiple dimensions using the parallel coordinate system. The primary goal of this software is to ease the analysis of data and finding correlation among the various variables. Since the software deals with huge amounts of data, representing the information all at once creates an image with congested or clustered lines. This makes it difficult to distinguish between lines and obtain any kind of information from the image, which is the main objective of the software. The image that is generated is not clear enough to find or detect any kind of correlation among the various variables. This research work describes two methods (plugins) to solve this problem; the idea is to group lines into sets and represent each set as a single line. This reduces the total number of lines in the figure and makes it easily readable and understandable. The two methods described below are: Grouping based on Comparison of data and Grouping Consecutive data.en_US
dc.format.extent73 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0000692
dc.identifier.otherSen_alatus_0004M_10748
dc.identifier.urihttps://ir.ua.edu/handle/123456789/1197
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectComputer science
dc.titleLog analysis technique: Picvizen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Computer Science
etdms.degree.disciplineComputer Science
etdms.degree.grantorThe University of Alabama
etdms.degree.levelmaster's
etdms.degree.nameM.S.
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