Migration of a Vehicle Tracking System Running on Relational Database to Big Data Environment

Ferhat Koçer; Selim Bayraklı

Makale detayları

Migration of a Vehicle Tracking System Running on Relational Database to Big Data Environment

Yazarlar:

Ferhat Koçer | Selim Bayraklı

Yayıncı:

Fırat University

Ana Başlıklar:

Big Data

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.161-168

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309698

pISSN:

1308-9080

Anahtar kelimeler:

Özet:

 Building a high-performance and scalable system has always been a challenge in tracking systems. At the root of this problem lies the excessive and real-time data overload. This paper aims to replace traditional approaches with big data approaches. In this study, a new big data ecosystem design for vehicle tracking system architecture is presented. The aim is to process real-time and extremely fast-generated locationtracking data very fast and increase the overall system performance. The process speed performance of the newly developed big data ecosystem is compared with the table query speed performance of a relational database. As a result of the comparison, the query speed of the big data ecosystem was found to be much faster than that of the relational database management system.

 Building a high-performance and scalable system has always been a challenge in tracking systems. At the root of this problem lies the excessive and real-time data overload. This paper aims to replace traditional approaches with big data approaches. In this study, a new big data ecosystem design for vehicle tracking system architecture is presented. The aim is to process real-time and extremely fast-generated locationtracking data very fast and increase the overall system performance. The process speed performance of the newly developed big data ecosystem is compared with the table query speed performance of a relational database. As a result of the comparison, the query speed of the big data ecosystem was found to be much faster than that of the relational database management system.

 Building a high-performance and scalable system has always been a challenge in tracking systems. At the root of this problem lies the excessive and real-time data overload. This paper aims to replace traditional approaches with big data approaches. In this study, a new big data ecosystem design for vehicle tracking system architecture is presented. The aim is to process real-time and extremely fast-generated locationtracking data very fast and increase the overall system performance. The process speed performance of the newly developed big data ecosystem is compared with the table query speed performance of a relational database. As a result of the comparison, the query speed of the big data ecosystem was found to be much faster than that of the relational database management system.

 Yüksek performanslı ve ölçeklenebilir bir sistem oluşturmak, takip sistemlerinde her zaman bir sorun olmuştur. Bu sorunun temelinde aşırı ve gerçek zamanlı veri yoğunluğu yatmaktadır. Bu makale geleneksel yaklaşımların yerine büyük veri yaklaşımlarını uygulamayı amaçlamaktadır. Bu çalışmada araç takip sistemi mimarisi için geleneksel yöntemlerin dışına çıkarak yeni bir büyük veri ekosistem tasarım ortaya koyulmuştur. Bunu yapmadaki amaç; gerçek zamanlı ve aşırı hızlı üretilen konumtakip verilerinin çok hızlı işlenmesi ve genel sistem performansının arttırılmasıdır. Yeni geliştirilen büyük veri ekosisteminin hız performansı, ilişkisel veri tabanın tablo sorgulama hız performansıyla karşılaştırılmıştır. Karşılaştırma sonucunda büyük veri ekosisteminin sorgulama hızının ilişkisel veri tabanı yönetim sistemine kıyasla çok daha hızlı olduğu görülmüştür.

Makale detayları

Migration of a Vehicle Tracking System Running on Relational Database to Big Data Environment

Yazarlar:

Ferhat Koçer | Selim Bayraklı

Yayıncı:

Fırat University

Ana Başlıklar:

Big Data

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.161-168

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309698

pISSN:

1308-9080

vehicle tracking system

satellite tracking system architecture

big data

cassandra

kafkaaraç takip sistemi

uydu takip sistemi mimarisi

büyük veri

cassandra

kafka

Sayı

Makale detayları

Yazarlar: Ferhat Koçer | Selim Bayraklı

Yayıncı: Fırat University

Ana Başlıklar: Big Data

Dergi: Turkish Journal of Science and Technology Vol.19 Issue 1, pp.161-168

Belge Tipi: Makale

Yayın Tarihi: 3/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001309698

pISSN: 1308-9080

Sayı

Yazarlar:

Ferhat Koçer | Selim Bayraklı

Yayıncı:

Fırat University

Ana Başlıklar:

Big Data

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.161-168

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309698

pISSN:

1308-9080