Campus traffic and e-Learning during COVID-19 pandemic.

Area of Science:

• Computer Science
• Network Engineering
• Information Technology

Background:

• The COVID-19 pandemic necessitated widespread lockdowns and social distancing, altering daily habits and increasing reliance on internet services.
• The surge in remote working, e-teaching, online collaboration, and entertainment placed unprecedented stress on network infrastructure globally.

Purpose of the Study:

• To analyze the impact of COVID-19 lockdown measures on the network traffic at Politecnico di Torino (PoliTO).
• To characterize the network footprint and user behavior associated with PoliTO's in-house virtual teaching solution.

Main Methods:

• Monitoring and analysis of campus network traffic before and during the COVID-19 lockdown.
• Focus on the usage patterns of remote working, collaboration platforms, and the in-house virtual teaching system.
• Characterization of audience demographics and network resource consumption for the online teaching solution.

Main Results:

• Significant shifts in network traffic patterns were observed due to the pandemic.
• PoliTO's in-house virtual teaching solution successfully supported approximately 600 daily classes for over 16,000 students.
• Analysis provided insights into the usage of remote working tools and the specific demands of the university's online education platform.

Conclusions:

• The internet infrastructure proved robust in handling the challenges posed by the pandemic.
• University operations were successfully maintained through adaptive network management and the deployment of effective online solutions.
• The study highlights the critical role of resilient network systems in sustaining academic activities during crises.