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Workload performance evaluation of large spatial database for DSS based disaster management

Workload performance evaluation can be implemented during Disaster Management and especially at the response phase to handle large spatial data in the event of an eruption and in this study it is involves the merapi volcano of Indonesia. Merapi volcano is known for its biggest eruption in the world....

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Main Author: Rohman, Muhammad Syaifur
Format: Thesis
Language:English
English
Published: 2017
Subjects:
Q Science (General)
QA76 Computer software
Online Access:http://eprints.utem.edu.my/id/eprint/20760/1/Workload%20Performance%20Evaluation%20Of%20Large%20Spatial%20Database%20For%20DSS%20Based%20Disaster%20Management%20-%20Muhammad%20Syaifur%20Rohman%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/20760/2/Workload%20performance%20evaluation%20of%20large%20spatial%20database%20for%20DSS%20based%20disaster%20management.pdf
http://eprints.utem.edu.my/id/eprint/20760/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106001
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spelling my.utem.eprints.207602022-06-13T16:02:19Z http://eprints.utem.edu.my/id/eprint/20760/ Workload performance evaluation of large spatial database for DSS based disaster management Rohman, Muhammad Syaifur Q Science (General) QA76 Computer software Workload performance evaluation can be implemented during Disaster Management and especially at the response phase to handle large spatial data in the event of an eruption and in this study it is involves the merapi volcano of Indonesia. Merapi volcano is known for its biggest eruption in the world. After the occurrence of an eruption, the affected areas are isolated, and thus it is difficult to be accessed by the rescuers. It is indeed very difficult to reach the isolated area as well as to rescue the victims from the affected areas. Although specific researches have resulted in solutions to the issue, other aspects that include the sending of workload to the database needs to be taken into consideration and it is viable to result in an effective and efficient process. Besides, the shortest route could be defined timely and accurately hence enabling the victims to leave the isolated area and to reach the evacuation point safely. This research intends to study on workload performance which is crucial to support the working mechanism of Database Management System (DBMS). Literature on recent studies has made it clear that research in this particular area of interest is scarce. Therefore, the general objective of this research is to evaluate and predict workload performance of spatial DBMS associated with PostgreSQL which is different from MySQL. Based on incoming workload, this research is able to predict the associated workload into OLTP and DSS workload performance types. From the SQL statements it is clear that the DBMS is able to obtain and record the process, measure the analyzed performances and the workload classifier in the form of snapshots from the DBMS. For example, it has been proven that Dijkstra Algorithm is able to determine the shortest and the safest path. Then, all the workload that are obtained to determine the processes are recorded into one excel file. The Case Based Reasoning (CBR) optimized with Hash Search Technique has been adopted in this study for the purpose of evaluating and predicting the workload performance of PostgreSQL DBMS. Data recorded in the shortest path analysis process reveals that the evaluation and the prediction on workload performance of shortest path analysis using Dijkstra algorithm has been well implemented. It has been proven that the proposed CBR using Hash Search technique has resulted in an excellent prediction of the accuracy measurement. Besides, the results of the evaluation using confusion matrix has resulted in excellent accuracy as well as improvement in execution time. Additionally, the results of the study indicated that the prediction model for workload performance evaluation using CBR that is optimized with Hash Search technique for determining workload data on Shortest Path analysis via the employment of Dijkstra algorithm can be useful for the prediction of incoming workload based on the status of the DBMS parameters. In this way, information is delivered to DBMS hence ensuring incoming workload information is very crucial for the purpose of determining the smooth works of PostgreSQL DBMS. 2017 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/20760/1/Workload%20Performance%20Evaluation%20Of%20Large%20Spatial%20Database%20For%20DSS%20Based%20Disaster%20Management%20-%20Muhammad%20Syaifur%20Rohman%20-%2024%20Pages.pdf text en http://eprints.utem.edu.my/id/eprint/20760/2/Workload%20performance%20evaluation%20of%20large%20spatial%20database%20for%20DSS%20based%20disaster%20management.pdf Rohman, Muhammad Syaifur (2017) Workload performance evaluation of large spatial database for DSS based disaster management. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106001
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
English
topic Q Science (General)
QA76 Computer software
spellingShingle Q Science (General)
QA76 Computer software
Rohman, Muhammad Syaifur
Workload performance evaluation of large spatial database for DSS based disaster management
description Workload performance evaluation can be implemented during Disaster Management and especially at the response phase to handle large spatial data in the event of an eruption and in this study it is involves the merapi volcano of Indonesia. Merapi volcano is known for its biggest eruption in the world. After the occurrence of an eruption, the affected areas are isolated, and thus it is difficult to be accessed by the rescuers. It is indeed very difficult to reach the isolated area as well as to rescue the victims from the affected areas. Although specific researches have resulted in solutions to the issue, other aspects that include the sending of workload to the database needs to be taken into consideration and it is viable to result in an effective and efficient process. Besides, the shortest route could be defined timely and accurately hence enabling the victims to leave the isolated area and to reach the evacuation point safely. This research intends to study on workload performance which is crucial to support the working mechanism of Database Management System (DBMS). Literature on recent studies has made it clear that research in this particular area of interest is scarce. Therefore, the general objective of this research is to evaluate and predict workload performance of spatial DBMS associated with PostgreSQL which is different from MySQL. Based on incoming workload, this research is able to predict the associated workload into OLTP and DSS workload performance types. From the SQL statements it is clear that the DBMS is able to obtain and record the process, measure the analyzed performances and the workload classifier in the form of snapshots from the DBMS. For example, it has been proven that Dijkstra Algorithm is able to determine the shortest and the safest path. Then, all the workload that are obtained to determine the processes are recorded into one excel file. The Case Based Reasoning (CBR) optimized with Hash Search Technique has been adopted in this study for the purpose of evaluating and predicting the workload performance of PostgreSQL DBMS. Data recorded in the shortest path analysis process reveals that the evaluation and the prediction on workload performance of shortest path analysis using Dijkstra algorithm has been well implemented. It has been proven that the proposed CBR using Hash Search technique has resulted in an excellent prediction of the accuracy measurement. Besides, the results of the evaluation using confusion matrix has resulted in excellent accuracy as well as improvement in execution time. Additionally, the results of the study indicated that the prediction model for workload performance evaluation using CBR that is optimized with Hash Search technique for determining workload data on Shortest Path analysis via the employment of Dijkstra algorithm can be useful for the prediction of incoming workload based on the status of the DBMS parameters. In this way, information is delivered to DBMS hence ensuring incoming workload information is very crucial for the purpose of determining the smooth works of PostgreSQL DBMS.
format Thesis
author Rohman, Muhammad Syaifur
author_facet Rohman, Muhammad Syaifur
author_sort Rohman, Muhammad Syaifur
title Workload performance evaluation of large spatial database for DSS based disaster management
title_short Workload performance evaluation of large spatial database for DSS based disaster management
title_full Workload performance evaluation of large spatial database for DSS based disaster management
title_fullStr Workload performance evaluation of large spatial database for DSS based disaster management
title_full_unstemmed Workload performance evaluation of large spatial database for DSS based disaster management
title_sort workload performance evaluation of large spatial database for dss based disaster management
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/20760/1/Workload%20Performance%20Evaluation%20Of%20Large%20Spatial%20Database%20For%20DSS%20Based%20Disaster%20Management%20-%20Muhammad%20Syaifur%20Rohman%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/20760/2/Workload%20performance%20evaluation%20of%20large%20spatial%20database%20for%20DSS%20based%20disaster%20management.pdf
http://eprints.utem.edu.my/id/eprint/20760/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106001
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score 13.211869

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