5G Network Slicing
The 5th generation of mobile networks (5G) is on the horizon to revolutionize the communication landscape. 5G will provide the communication infrastructure to realize emerging technologies, including smart city, industry automation, e-health, internet of things, autonomous vehicles among others. These technologies will enable a wide variety of services and applications with diverse quality of service (QoS) requirements in terms of bandwidth, latency, jitter, reliability, energy efficiency, and mobility. Satisfying diverse requirements imposed by various applications and services poses a challenge to 5G network operators. Network virtualization has been proposed to cope with this challenge. 5G mobile network operators can use virtualization technologies to partition their network resources into multiple network slices, each of which is customized to a specific purpose, and lease them to service providers. Service providers use network slices to offer services with specific QoS requirements (e.g., eMBB, uRLLC, and mMTC). The goal of this project is to develop a closed-loop network slice life-cycle management system for 5G mobile networks. To achieve this, I plan to focus my research in four related but separate thrusts: i) develop slice orchestration algorithms; ii) design intelligent monitoring schemes; iii) devise mechanisms to support seamless slice operation and maintenance; and iv) develop slice adaptation and consolidation approaches. Machine Learning (ML), Artificial Intelligence (AI), and Big Data Analytics will play a pivotal role in this project.