ABSTRACT
The last 30 years of networking has been based on reactive networking protocols and recovery mechanisms. This paper explores the shift of this network paradigm towards predictive networks which apply AI/ML techniques to predict network performance degradation and make proactive recommendations to switch paths before the issue arises. Ultimately, predictive networks combined with trusted automation will automatically resolve issues, evolving towards self-configuring and self-healing capabilities. Predictive analytics engines will improve network resiliency, help IT teams prevent issues and elevate the user experience. Predictive networks will augment traditional routing and recovery mechanisms to provide businesses with higher availability. This presentation will provide an overview of predictive networks and the importance to improving network resilience and user experience in the Defence environment.

BIOGRAPHY
Angelo Puglielli is a Business Solutions Architect in the ANZ Defence team at Cisco Systems Inc. He has been with Cisco for over 17 years in a variety of technical and advisory service delivery roles and projects working with customers throughout the Asia Pacific. In the last 8 years he has primarily focused on Defence where he has been architecture and technical lead on several strategic Defence engagements including the PINs infrastructure architecture and Army Cyber programs. He holds CISSP and TOGAF certifications, a Bachelor of Applied Science from Charles Sturt University, an MBA in Technology Management from Deakin University, and a Master of Engineering Science from UNSW Canberra at the Australian Defence Force Academy (ADFA) where he was awarded the BAE Systems MEngSc prize.