Software Defined Networking (SDN) is a new network technology that separates the data plane from the control plane. Forwarding devices are stripped of their intelligence which is given to one or multiple controllers. This separation eases the management of the network and the deployment of network-wide applications independently of the underlying equipment.
In parallel, energy consumption of networking infrastructures is becoming a growing concern. For instance, networking devices represent 10 to 20% of the total energy cost of data centers. In most cases, proposed solutions for energy efficiency suggest to shutdown unused devices to reduce the consumption of energy in the network.
During my thesis, I worked to leverage SDN features to implement green policies while taking into consideration limitations such as forwarding table sizes of SDN switches. I also looked at progressive deployment of SDN devices on existing legacy wired and optical networks. Furthermore, I studied the effects of Network Function Virtualization on energy savings. At the same time, on another theme, I also worked on structured distributed peer-to-peer systems for live video streaming.
During my postdoc at Concordia University, I continued my work on network virtualization and studied multi-layer network planning and resource and spectrum assignment (RSA) using classic optimization tools such as column generation.
Currently, as a research engineer at Huawei Technologies, I study 5G network optimization problems. I work on network slicing algorithms for hard isolation, multi-slice optimization and I’m also interested in leveraging machine learning tools and in integrating them with linear programming methods.