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Warianty tytułu
Języki publikacji
Abstrakty
Electric vehicles are increasingly popular means of transport. One of the most important problems of their operation is to optimize the use of a battery pack. It requires to analyze the operational characteristics of a vehicle in motion, which are stored in a database. If the measurement data are collected from many vehicles, the efficiency of their analysis is important. The objective of this article is to study the possibilities of using modern column-oriented databases in order to increase the efficiency of the analysis of selected operational characteristics of an electric vehicle. The research problem is a comparative analysis of the processing efficiency of selected measurement characteristics of an electric vehicle in relational and column-oriented data structures. Important analytical functions were formulated and recorded in the form of database queries. An experiment consisting in multiple execution of functions packages on various database structures, including a column-oriented one, was carried out. The execution time of packages and the IT system load were collected and analyzed. The analysis of the experiment results allows to conclude that the use of the column-oriented data structures made it possible to shorten the time of executing the functions analyzing the energy consumption by the electric vehicle’s drive system. Depending on the type of the analyzed characteristics of the vehicle and its method of representation in the database, a significant reduction of the analysis time compared to the relational structure was obtained. Also, a decrease in the load on the computer system during data processing on the column-oriented structures was noted. The use of the column-oriented databases in the processing and analysis of measurement operational characteristics of electric vehicles is justified and it can bring measurable effects. It should be considered that the effectiveness of solving depends on the number of the analyzed characteristics and the format of their representation in the computer.
Czasopismo
Rocznik
Tom
Strony
77--84
Opis fizyczny
Bibliogr. 14 poz., tab., wykr.
Twórcy
autor
- Warsaw University of Technology, Faculty of Transport, Warsaw, Poland
Bibliografia
- [1] ABRAMOVA, V., BERNARDINO, J. & FURTADO, P., 2014. Which NoSQL Database? A Performance Overview. Open Journal of Data-bases, 1(2), 17-24.
- [2] CHOROMAŃSKI, W., DASZCZUK, W., DYDUCH, J. et. al., 2014. PRT (Personal Rapid Transit) Network Simulation. In: Proceedings of the 13th World Conference on Transportation Research, Rio de Janeiro, July 2013, arXiv:1711.07325.
- [3] CZEREPICKI, A., 2016. Application of graph databases for transport purposes. Bulletin of the Polish Academy of Sciences. Technical Sciences, 64 (3), 457-466, DOI: 10.1515/bpasts-2016-0051.
- [4] DETTI, A., ORRU, M., PAOLILLO, R. et al., 2017. Application of Information Centric Net-working to NoSQL databases: The spatio-temporal use case. In: 2017 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), Osaka, 2017, 1-6, DOI: 10.1109/LANMAN.2017.7972131.
- [5] IDREOS, S., GROFFEN, F., NES, N., MANEGOLD, S., MULLENDER, S. & KERSTEN, M., 2012. MonetDB: Two Decades of Research in Column-oriented Database Architectures. IEEE Data Engineering Bulletin, 35 (1), 40-45.
- [6] JACHIMOWSKI, R., GOŁĘBIOWSKI, P., IZDEBSKI, M., PYZA, D. & SZCZEPAŃSKI, E., 2017. Designing and efficiency of database for simulation of processes in systems. Case study for the simulation of warehouse processes. Archives of Transport, 41(1), DOI: 10.5604/01.3001.0009.7380.
- [7] JING, H., 2011. Survey on NOSQL Databases. In: Proceedings 6th International Conference on Pervasive Computing and Applications, Port Elizabeth, 363-366, DOI:10.1109/ICPCA.2011.6106531.
- [8] KEMP, G., VARGAS-SOLAR, G., FERREIRA DA SILVA, G., GHODOUS, P., COLLET, C. & AMALYA, P., 2016. Cloud big data application for transport. International Journal of Agile Systems and Management, 9, 232-250, DOI: 10.1504/IJASM.2016.079940.
- [9] LARSON, P., HANSON, E. & PRICE, S., 2012. Columnar Storage in SQL Server 2012. IEEE Data Engineering Bulletin, 35(1), 15-20.
- [10] SUN, S. & LIU, C., 2016. Application of improved storage technology in Intelligent Transportation System. Advances in Transportation Studies, 3, 51-60, DOI: 10.4399/978885489937705.
- [11] TOMCZUK, P., CZEREPICKI, A., KONIAK, M. & JASKOWSKI, P., 2017. The Design of the Telemetric System for Recording Operating Parameters of Electric Vehicles. Logistics and Transport, 1, 47-54.
- [12] THOMAS, G., ALEXANDER, G., SASI, P.M., 2017. Design of high performance cluster based map for vehicle tracking of public transport vehicles in smart city. In: 2017 IEEE Region 10 Symposium (TENSYMP), Cochin, 1-5, DOI: 10.1109/TENCONSpring.2017.8070027.
- [13] VELA, B., CAVERO, J. M., CÁCERES, P., SIERRA, A. & CUESTA, C. E., 2017. Defining a NoSQL Document Database of Accessible Transport Routes. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Exeter, 1125-1129, DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.172.
- [14] ŻOCHOWSKA, R. & SOCZÓWKA, P., 2018. Analysis of selected transportation network structures based on graph measures. Scientific Journal of Silesian University of Technology. Series Transport, 98, 223-233. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2018.98.21.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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