Log analysis technique: Picviz
| dc.contributor | Hong, Xiaoyan | |
| dc.contributor | Vrbsky, Susan V. | |
| dc.contributor | Li, Shuhui | |
| dc.contributor.advisor | Xiao, Yang | |
| dc.contributor.author | Sen, Shraddha Pradip | |
| dc.contributor.other | University of Alabama Tuscaloosa | |
| dc.date.accessioned | 2017-03-01T14:46:07Z | |
| dc.date.available | 2017-03-01T14:46:07Z | |
| dc.date.issued | 2011 | |
| dc.description | Electronic Thesis or Dissertation | en_US |
| dc.description.abstract | Log 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.extent | 73 p. | |
| dc.format.medium | electronic | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | u0015_0000001_0000692 | |
| dc.identifier.other | Sen_alatus_0004M_10748 | |
| dc.identifier.uri | https://ir.ua.edu/handle/123456789/1197 | |
| dc.language | English | |
| dc.language.iso | en_US | |
| dc.publisher | University of Alabama Libraries | |
| dc.relation.hasversion | born digital | |
| dc.relation.ispartof | The University of Alabama Electronic Theses and Dissertations | |
| dc.relation.ispartof | The University of Alabama Libraries Digital Collections | |
| dc.rights | All rights reserved by the author unless otherwise indicated. | en_US |
| dc.subject | Computer science | |
| dc.title | Log analysis technique: Picviz | en_US |
| dc.type | thesis | |
| dc.type | text | |
| etdms.degree.department | University of Alabama. Department of Computer Science | |
| etdms.degree.discipline | Computer Science | |
| etdms.degree.grantor | The University of Alabama | |
| etdms.degree.level | master's | |
| etdms.degree.name | M.S. |
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