The Impact of the COVID-19 Pandemic on Data Usage Rate in Enterprise Networks

Aykut Yılmaz; Zafer Aslan

Article Details

The Impact of the COVID-19 Pandemic on Data Usage Rate in Enterprise Networks

Authors:

Aykut Yılmaz | Zafer Aslan

Publisher:

Istanbul Aydin University

Main Topics:

Mühendislik

Journal:

Anadolu Bil Meslek Yüksekokulu Dergisi Vol.17 Issue 66, pp.95-115

Document Type:

Article

Publication Date:

4/2023

Document Language:

Turkish

Document ID (Org No.):

2001288075

pISSN:

1306-3375

Keywords:

Abstract:

 The importance of using and processing data in corporate networks is increasing day by day in the developing global world. Due to the nature of the systems, the use of data increases the network traffic density from the connected roads. The increase in data density is one of the most important factors affecting system infrastructures and performance values. Measuring and evaluating the effect of data usage amounts before the start of COVID-19 on the usage density rates of network traffic in corporate networks and the effect of network traffic density that develops with the onset of the pandemic process provides a better understanding of this structure. By using Wavelet Transform and Continuous Wavelet Transform, the temporal variation of data density was analyzed with an application based on the data set obtained from the system. The graphical data created after the analysis of the signal data Mbps or Gbps processed before and after the COVID-19 by using Wavelet Transform were examined and interpreted. a specific results, statistical magnitudes and different scale effects were analized. While there were 8791 data before COVID-19, 16167 data were taken into account after COVID-19. In addition, when the network traffic was examined after the pandemic period, it increased 141 times, higher thans the speed recorded before pandemic period similarly the average network traffic speed is 79 times.

 The importance of using and processing data in corporate networks is increasing day by day in the developing global world. Due to the nature of the systems, the use of data increases the network traffic density from the connected roads. The increase in data density is one of the most important factors affecting system infrastructures and performance values. Measuring and evaluating the effect of data usage amounts before the start of COVID-19 on the usage density rates of network traffic in corporate networks and the effect of network traffic density that develops with the onset of the pandemic process provides a better understanding of this structure. By using Wavelet Transform and Continuous Wavelet Transform, the temporal variation of data density was analyzed with an application based on the data set obtained from the system. The graphical data created after the analysis of the signal data Mbps or Gbps processed before and after the COVID-19 by using Wavelet Transform were examined and interpreted. a specific results, statistical magnitudes and different scale effects were analized. While there were 8791 data before COVID-19, 16167 data were taken into account after COVID-19. In addition, when the network traffic was examined after the pandemic period, it increased 141 times, higher thans the speed recorded before pandemic period similarly the average network traffic speed is 79 times.

 The importance of using and processing data in corporate networks is increasing day by day in the developing global world. Due to the nature of the systems, the use of data increases the network traffic density from the connected roads. The increase in data density is one of the most important factors affecting system infrastructures and performance values. Measuring and evaluating the effect of data usage amounts before the start of COVID-19 on the usage density rates of network traffic in corporate networks and the effect of network traffic density that develops with the onset of the pandemic process provides a better understanding of this structure. By using Wavelet Transform and Continuous Wavelet Transform, the temporal variation of data density was analyzed with an application based on the data set obtained from the system. The graphical data created after the analysis of the signal data Mbps or Gbps processed before and after the COVID-19 by using Wavelet Transform were examined and interpreted. a specific results, statistical magnitudes and different scale effects were analized. While there were 8791 data before COVID-19, 16167 data were taken into account after COVID-19. In addition, when the network traffic was examined after the pandemic period, it increased 141 times, higher thans the speed recorded before pandemic period similarly the average network traffic speed is 79 times.

 Kurumsal ağlarda verinin kullanılması ve işlenmesi konusunun önemi gelişen global dünyada her geçen gün artmaktadır. Sistemlerin yapıları gereği veri kullanımı, bağlantılı yollardan ağ trafik yoğunluğunu arttırmaktadır. Verinin yoğunluğundaki artış, sistem altyapıları ve performans değerlerine etki eden en önemli faktörlerden biridir. COVID-19 başlamadan önceki veri kullanım miktarlarının kurumsal ağlardaki, ağ trafiğinin kullanım yoğunluk oranlarına olan etkisi ve pandemi sürecinin başlamasıyla gelişen ağ trafik yoğunluğunun etkisinin ölçülmesi ve değerlendirilmesi bu yapının daha iyi anlaşılmasını sağlamaktadır. Wavelet Transform Dalgacık Dönüşümü ve Continuous Wavelet Transform Sürekli Dalgacık Dönüşümü kullanılarak, sistemden elde edilen veri setine dayalı yapılan bir uygulama ile veri yoğunluğunun zamansal değişimi analiz edilmiştir. Wavelet Transform uygulanan COVID-19 öncesi ve sonrasında işlenen sinyal verilerinin Mbps veya Gbps analiz çalışması sonrası oluşturulan grafiksel veriler incelenip, yorumlanmıştır. COVID-19 öncesinde 8791 veri varken, COVID-19 sonrasında ise 16167 veri göz önüne alınmış bulunmaktadır. Ayrıca, ağ trafiği incelendiğinde, pandemi döneminde arasında 141 kadar artmışken, ortalamada gözlemlenen ağ trafik hızı ise 79 artmıştır.

Article Details

The Impact of the COVID-19 Pandemic on Data Usage Rate in Enterprise Networks

Authors:

Aykut Yılmaz | Zafer Aslan

Publisher:

Istanbul Aydin University

Main Topics:

Mühendislik

Journal:

Anadolu Bil Meslek Yüksekokulu Dergisi Vol.17 Issue 66, pp.95-115

Document Type:

Article

Publication Date:

4/2023

Document Language:

Turkish

Document ID (Org No.):

2001288075

pISSN:

1306-3375

Covid-19

Enterprise Network

Wavelet Transform

Mbps and Gbps

Digital SignalCovid-19

Kurumsal Ağ

Dalgacık Dönüşüm

Mbps ve Gpbs

Dijital Sinyal

Issues

Article Details

Authors: Aykut Yılmaz | Zafer Aslan

Publisher: Istanbul Aydin University

Main Topics: Mühendislik

Journal: Anadolu Bil Meslek Yüksekokulu Dergisi Vol.17 Issue 66, pp.95-115

Document Type: Article

Publication Date: 4/2023

Document Language: Turkish

Document ID (Org No.): 2001288075

pISSN: 1306-3375

Issues

Authors:

Aykut Yılmaz | Zafer Aslan

Publisher:

Istanbul Aydin University

Main Topics:

Mühendislik

Journal:

Anadolu Bil Meslek Yüksekokulu Dergisi Vol.17 Issue 66, pp.95-115

Document Type:

Article

Publication Date:

4/2023

Document Language:

Turkish

Document ID (Org No.):

2001288075

pISSN:

1306-3375