In 1956, a small group of researchers came together for the Dartmouth Summer Research Project on Artificial Intelligence, led by Professor John McCarthy. McCarthy coined the term “artificial intelligence,” and the conference is widely known as the inception of AI as a field of research. In the following decades, AI evolved from a hypothetical field of research to a powerful tool that’s making its mark on the world. From self-driving cars to intelligent home speakers, AI is already changing our lives—and it’s only the beginning. But one place you may not expect to use AI is in your internet.
The typical network on college campuses across the country is based on an architecture designed more than a decade ago, before the advent of ubiquitous wireless devices, social media, and streaming services that have drastically increased what users ask of and expect from the campus internet.
Today, students and faculty expect Wi-Fi everywhere on campus, and they expect it to work seamlessly—in the classroom, the dorm, wherever they may be—whether it’s to email a paper due the next day or stream Game of Thrones. Outstanding digital service has become a crucial factor in our students’ learning experiences and their satisfaction.
Dartmouth also envisions a highly automated campus where AI works in conjunction with other wireless technologies, like Bluetooth LE, to personalize the wireless experience across campus. Students, faculty, staff, and guests can interact with wireless beacons for location-based services, such as turn-by-turn directions in the student union, notifications for free flu shots when passing the clinic, or self-guided tours across campus. Such applications will only keep raising the stakes for wireless network quality.
In addition, we see AI as being critical to troubleshooting problems across our whole IT infrastructure. Events can be correlated across wireless and wired domains, for example, and cross-referenced with states pulled from devices in real-time to troubleshoot problems quickly, rapidly identify anomalies, and predict issues before users even know they exist.
"As AI continues to change how we live and work for the better, any university should consider the implementation of an AI-powered network as part of a broader digital transformation initiative to better serve the university community in the digital age"
Improving the campus Wi-Fi experience
Dartmouth, like so many other universities, was saddled with an aging network infrastructure that practically guaranteed a lousy experience for students, faculty, staff, and guests.
With thousands of users connecting multiple devices to the network, we struggled to provide easy access and fast internet that our students and faculty have come to expect using our outdated infrastructure. It couldn’t provide visibility into the service levels that users were experiencing and forced administrators into the slow, painful task of manually sifting through a plethora of computer-generated logs scattered across the IT stack to determine where and why problems were occurring before they could fix it.
A variety of vendor tools have become available through the years to try to attack the problem, but they tend to be hard to use, require a great deal of specialized knowledge and, in the end, still take too much time and effort to pinpoint the root cause of wireless issues. Being a network engineer, I want us to be able to know that it took eight seconds for the user to connect because the DHCP server had a problem, without jumping through four intermediate systems and a central log collector to figure it all out.
How next-generation networks work
We’ve learned at Dartmouth that a new generation of a network—one powered by AI and the cloud—can help us diagnose issues across campus at a radically quicker pace and greater scale than was possible with our old manually-driven wired and wireless networks.
We purchased an AI-driven network from Mist / Juniper, which does what a human couldn’t possibly do: collect real-time information about what every Wi-Fi and the wired user is experiencing, analyze that data in the cloud, and get actionable insight to solve problems before they impact the user experience.
This advanced level of troubleshooting allows us to do something unheard of in the old architecture: establish network service-level baselines for key satisfaction metrics, like time to connect, roaming time, throughput, and more. For example, we can delineate that it should take no more than two seconds for a smartphone user in our Wheeler residence hall to access the Wi-Fi, know right away if it took longer, and see in a clear, easy-to-read format what exactly in the network went wrong.
The system is true AI in that it learns over time and can predict issues even before they happen, which adds a self-healing element to the network. The technology we acquired even has an Alexa-like “virtual network assistant” that uses natural language processing to provide network administrators with answers to questions such as, “How are the Wi-Fi access points in Baker-Berry Library performing?”
Since the new AI-driven network came online, complaints to the help desk have plummeted. And when complaints do come in, help desk reps are able to handle them quickly and independently of the network services team.
As AI continues to change how we live and work for the better, any university should consider the implementation of an AI-powered network as part of a broader digital transformation initiative to better serve the university community in the digital age.