Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Preprocessing unbounded data for use in real time visualization: Building a visualization data cube of unbounded data
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis evaluates the viability of a data cube as a basis for visualization of unbounded data. A cube designed for use with visualization of static data was adapted to allow for point-by-point insertions. The new cube was evaluated by measuring the time it took to insert different numbers of data points. The results indicate that the cube can keep up with data streams with a velocity of up to approximately 100 000 data points per second. The conclusion is that the cube is useful if the velocity of the data stream is within this bound, and if the granularity of the represented dimensions is sufficiently low.

Abstract [sv]

Det här exjobbet utvärderar dugligheten av en datakub som bas för visualisering av obegränsad data. En kub designad för användning till visualisering av statisk data anpassades till att medge insättning punkt för punkt. Den nya kuben evaluerades genom att mäta tiden det tog att sätta in olika antal datapunkter. Resultaten indikerade att kuben kan hantera dataströmmar med en hastighet på upp till 100 000 punkter per sekund. Slutsatsen är att kuben är användbar om hastigheten av dataströmmen är inom denna gräns, och om grovheten av de representerade dimensionerna är tillräckligt hög.

Place, publisher, year, edition, pages
2019. , p. 16
Series
TRITA-EECS-EX ; 2019:477
Keywords [en]
unbounded data; visualization; data cube
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-260349OAI: oai:DiVA.org:kth-260349DiVA, id: diva2:1355337
Supervisors
Examiners
Available from: 2019-10-17 Created: 2019-09-27 Last updated: 2019-10-17Bibliographically approved

Open Access in DiVA

fulltext(681 kB)10 downloads
File information
File name FULLTEXT01.pdfFile size 681 kBChecksum SHA-512
43b02c0e6b91da62d47a22ae063ece404d1855c50276ad2b915f0fbfbbee3e492d288df7c0b4fab90e9e191b20deb90073b4085beb9f14d8c5349f151f1653b0
Type fulltextMimetype application/pdf

By organisation
School of Electrical Engineering and Computer Science (EECS)
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 10 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 19 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf