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master's thesis
Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu
2019. urn:nbn:hr:200:997775
Roguljić, Luka
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Communications
Chair of Multimedia Systems and Digital Television

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Roguljić, L. (2019). Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:997775

Roguljić, Luka. "Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2019. https://urn.nsk.hr/urn:nbn:hr:200:997775

Roguljić, Luka. "Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2019. https://urn.nsk.hr/urn:nbn:hr:200:997775

Roguljić, L. (2019). 'Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 22 April 2024, https://urn.nsk.hr/urn:nbn:hr:200:997775

Roguljić L. Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2019 [cited 2024 April 22] Available at: https://urn.nsk.hr/urn:nbn:hr:200:997775

L. Roguljić, "Filtriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:200:997775

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Metadata
TitleFiltriranje i klasifikacija prometa s pronalaženjem grešaka u automotiv podatkovnom prometu
Title (english)Traffic filtering and classifying with finding of errors in automotive data traffic
AuthorLuka Roguljić
MentorMario Vranješ (mentor)
Committee memberMario Vranješ (predsjednik povjerenstva)
Committee memberRatko Grbić (član povjerenstva)
Committee memberMarijan Herceg (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Communications)
(Chair of Multimedia Systems and Digital Television)
Osijek
Defense date and country2019-09-18, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Data Processing
Abstract
Ovaj diplomski rad bavi se tematikom pronalaženja grešaka i izguljenih poruka u mreži zasnovanoj na CAN komunikacijskom protokolu. U sklopu zadatka rada kreiran je novi algoritam za filtriranje, klasifikaciju podatkovnog prometa i detekciju pogrešaka i izgubljenih poruka koji obrađuje .asc log i scenarij usmjeravanja poruka u mreži zasnovanoj na CAN protokolu. Kreirano vlastito rješenje u sebi analizira 16 vrsta usmjeravanja u mreži sa 4 čvora. Algoritam služi za otkrivanje izgubljenih poruka i poruka s neispravnim podatkovnim blokom. Kao rezultat algoritma dobije se izvještaj u obliku .xlsx datoteke kako bi se moglo proučiti na kojim kanalima se stvaraju najveću problemi i koje poruke se najviše gube. Na temelju tog izvještaja moguće je analizirati komunikaciju i poduzeti korake prema poboljšanju komunikacije. Algoritam je kreiran u Python skriptom jeziku u PyCharm razvojnom okruženju. Kreirani algoritam ima značajke modularnosti i nadogradivosti jer je kreiran u dijelovima koji mogu biti izmijenjeni neovisno o drugim modulima. Verifikacija je provedena unutar programskog rješenja tako da su se kreirali slučajevi unošenjem anomalija u .asc (ručno promijenjeni podaci) datoteku. Rezultati verifikacije su pozitivni i udovoljavaju zahtjevima postavljenim prije izrade samog rješenja.
Abstract (english)
This thesis deals with the topic of fault finding and lost messages in a network based on CAN communication protocol. As part of the assignment, a new algorithm for filtering, classifying data traffic and detecting errors and lost messages has been created, that processes the .asc log and the message routing scenario in a network based on the CAN protocol. Created own solution analyzes 16 types of routing in a 4 node network. The algorithm serves to detect lost messages and messages with faulty data block. As a result of the algorithm, a report is given in form of .xlsx file so we could find out which channels are biggest problem and which messages are most losing ones. Based on this report, it is possible to analyze communication and take steps to improve communication. The algorithm is created in the Python script language in PyCharm development environment. The created algorithm has features of modularity and upgradability because it is created in parts that can be modified independently of other modules. Verification was carried out within the software solution so that cases were created by entering anomalies into the .asc (manually modified data) file. The results of the verification are positive and correspond to the set requirements before making the solution itself.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:997775
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-11-14 10:22:39