Research and education networks are rapidly evolving
to meet the changing demands of students, faculty, staff, and guests. These users bring with them numerous different devices and applications for on-campus and remote learning and collaboration, global research projects, eSports, cloud gaming, and video streaming. As a result, there is a continuous need to manage petabytes of traffic, and to differentiate critical educational and research applications from casual applications, all while protecting devices and users from malicious traffic.
To meet these challenges, education IT and network administrators need intelligent traffic management tools that enable them to identify, classify, and actively manage traffic based on application priority, source (e.g. student, faculty, department, location) and network conditions. Moreover, solutions need machine learning and automation to support real-time response to network events.
