Problem Formulation

There is too much downtime when network nodes fail due to circumstances such as:

• Bugs being present in code that cause a system failure

• Physical Damage to network devices

• Overloaded Servers due to large amounts of network traffic

• Networks being taken down for maintenance and updates

Differences between Artificial Intelligence, Machine Learning, and Deep Learning (IBM)

Differences between Artificial Intelligence, Machine Learning, and Deep Learning (TechTarget)

Timing (how urgent is the problem?): The problem is moderately urgent. There are current ways to mitigate network downtimes such as overprovisioning servers and extra network redundancy. However this can cost businesses large amounts of money. It is typically worth it to do this because of the amount of money that can be lost due to network downtime. According to Information Technology Intelligence Consulting, “For one-third of enterprises, the cost of an hour-long outage can top $1 million USD.” AI/ML technologies are advanced enough to be able to tackle this problem more effectively than previous strategies.

Trend (what is the problem's potential for growth?): The problem is trend-worthy and has potential for growth as society has been interconnected with the internet and computer networks. Attacks on these critical systems will result in major disruptions to our core services. Also, as networks become larger and more complex, reconfiguring due to a node outage might take longer.

Impact (how serious is the problem?): The problem has a serious impact as network downtime means that core systems are down. Current IT personnel may not know what in particular to fix.