Dr. Raouf Boutaba
Keynote Tile: Self-driving Networks: Challenges and Opportunities
Abstract: Automated management has been the holy grail of network management research for decades; it aims at achieving autonomous networks, i.e., networks capable to autonomously monitor their status, analyze problems, make decisions, and execute corrective actions. Despite several attempts to achieve autonomous networks in the past, their practical deployments have largely remained unrealized. Several factors are attributed to this, including the existence of many stakeholders with conflicting goals, reliance on proprietary solutions, the inability to process network monitoring data at scale, and the lack of global visibility restricting network-wide optimizations. The stars are now aligned to realize the vision of autonomous networks thanks to (i) advances in network softwarization; (ii) recent breakthroughs in machine learning; and (iii) the availability of large-scale data processing platforms. However, a number of challenges must be addressed in order to create the synergy between these different technology domains and achieve autonomous (a.k.a., self-driving networks) networks. This talk will discuss some of these challenges with particular focus on programmable network monitoring leveraging network softwarization, predictive machine learning for automated management decision making, and on-demand orchestration of network services.