Md Nooruzzaman

GreenCloud:Design and Implementation of Reconfigurable Converged Optical-Wireless Networks Comprising ROADMs towards Greener 5G Cloud RAN.

Several demanding applications drive the global traffic growth, including high definition video and cloud services. Some of the new bandwidth-hungry applications, such as immersive reality over the augmented social media and holographic video might come in future. As the video contents are gradually being distributed inside the metro networks and end users’ requests are served from the metro networks, the traffic load on the metro and access networks are growing at a rate higher than that of the core networks. To address these new challenges, augmenting the transmission systems’ capacity is no longer sufficient as it will increase the cost and energy consumption linearly.
Since a major portion of the mobile Internet users move during the day, networks (optical and 5G wireless) operators are looking forward to the solutions that can match the dynamic nature of the traffic load and help them reduce cost, save energy and share resources. With the advancement of cloud/centralized radio access networks (C-RANs), the optical metro and access networks experience more pressure to transport more mobile data content. Optical networks in the xHaul (fronthaul and backhaul) are expected to meet this demand of C-RANs. In order to address this, the development of advanced programmable and flexible converged optical-wireless networks will be necessary for future 5G C-RAN.

In this work, we will focus on the convergence of optical-wireless networks by enabling open reconfigurable optical add/drop multiplexer (ROADM) and implementing control plane based on software-defined networking (SDN) for achieving 5G wireless with high capacity, low cost and power per bit. The SDN controller will be used for fast reconfigurability of ROADMs in the xHaul and switching on/off the radio equipment for savings the network resources and power consumption. Its objective is twofold: i) to minimize the power consumption, and ii) to minimize end-to-end cloud service delay.