Atayero Aderemi A, Popoola Segun I, Adeyemi Oluwaseun J, Afolayan David G, Akanle Matthew B, Adetola Victor, Adetiba Emmanuel
IoT-enabled Smart and Connected Communities (SmartCU) Research Cluster, Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria.
Center for Systems and Information Services, Covenant University, Ota, Nigeria.
Data Brief. 2019 Feb 2;23:103705. doi: 10.1016/j.dib.2019.103705. eCollection 2019 Apr.
Efficient broadband Internet access is required for optimal productivity in smart campuses. Besides access to broadband Internet, delivery of high speed and good Quality of Service (QoS) are pivotal to achieving a sustainable development in the area of education. In this data article, trends and patterns of the speed of broadband Internet provided in a Nigerian private university campus are largely explored. Data transmission speed and data reception speed were monitored and recorded on daily basis at Covenant University, Nigeria for a period of twelve months (January-December, 2017). The continuous data collection and logging were performed at the Network Operating Center (NOC) of the university using SolarWinds Orion software. Descriptive statistics, correlation and regression analyses, Probability Density Functions (PDFs), Cumulative Distribution Functions (CDFs), Analysis of Variance (ANOVA) test, and multiple comparison post-hoc test are performed using MATLAB 2016a. Extensive statistical visualizations of the results obtained are presented in tables, graphs, and plots. Availability of these data will help network administrators to determine optimal network latency towards efficient deployment of high-speed broadband communication networks in smart campuses.
高效的宽带互联网接入是智能校园实现最佳生产力所必需的。除了接入宽带互联网外，高速和良好的服务质量（QoS）对于在教育领域实现可持续发展至关重要。在这篇数据文章中，主要探讨了尼日利亚一所私立大学校园提供的宽带互联网速度的趋势和模式。在尼日利亚的圣约大学，对数据传输速度和数据接收速度进行了为期十二个月（2017年1月至12月）的每日监测和记录。使用SolarWinds Orion软件在大学的网络运营中心（NOC）进行持续的数据收集和记录。使用MATLAB 2016a进行描述性统计、相关性和回归分析、概率密度函数（PDF）、累积分布函数（CDF）、方差分析（ANOVA）测试以及多重比较事后检验。以表格、图表和绘图的形式对获得的结果进行了广泛的统计可视化展示。这些数据的可用性将有助于网络管理员确定最佳网络延迟，以便在智能校园中高效部署高速宽带通信网络。
