Research Statement

As companies continue to offload their computing and network management into third party, cloud environments, multitenant datacenters are now becoming common place. With clients sharing processing power, bandwidth, and memory in the cloud, managing, securing, and elastically scaling client resources on demand is becoming a daunting task. To make matters more complicated, datacenter clients are requiring custom and high performance network analytics and secure computing environments. As a result, cloud providers are scrambling to meet these client demands in a secure and scalable manner. While SDN and NFV have both improved network management and provisioning, cloud providers still suffer from the lack of both fine-grained visibility into the network to meet security demands and the efficient scaling needed to meet constantly changing loads.

My goal is to efficiently and securely operate and elastically scale cloud computing in multitenant environments. As a result, my research focuses on developing systems that sit at the intersection of security and analytics on a cloud scale. My current work utilizes the recent emergence of highly programmable, hardware switches to design custom, cloud-scale, per-packet network analytic applications.

As I continue my work in the area of custom analytics and security in the cloud, I am beginning to dive into cloud elasticity and management, focusing on developing disaggregated and flexible serverless environments. By combining fine-grained network analytics and on demand resource allocation through serverless environments, we can achieve custom, elastic, and secure computing environments.