Springer Handbook of Optical Networks (Springer Handbooks)

This handbook is an authoritative, comprehensive reference on optical networks, the backbone of today’s communication and information society. The book reviews the many underlying technologies that enable the global optical communications infrastructure, but also explains current research trends targeted towards continued capacity scaling and enhanced networking flexibility in support of an unabated traffic growth fueled by ever-emerging new applications.

The book is divided into four parts: Optical Subsystems for Transmission and Switching, Core Networks, Datacenter and Super-Computer Networking, and Optical Access and Wireless Networks.

Each chapter is written by world-renown experts that represent academia, industry, and international government and regulatory agencies. Every chapter provides a complete picture of its field, from entry-level information to a snapshot of the respective state-of-the-art technologies to emerging research trends, providing something useful for the novice who wants to get familiar with the field to the expert who wants to get a concise view of future trends.

Biswanath Mukherjee is a Distinguished Professor Emeritus at University of California, Davis, CA, USA.  He holds a PhD from the University of Washington, Seattle, (1987) and a B.Tech (Hons) from Indian Institute of Technology, Kharagpur, (1980). He is also Distinguished Professor and Founding Director of the Institute for Broadband Research and Innovation (IBRI) at Soochow University in China.   He has been involved in several successful optical startups, including Ennetix, a SBIR-funded company specializing in AI-powered, application-centric, network analytics for optimal user experience. Biswanath Mukherjee served as program chair for several OFC, IEEE INFOCOM and IEEE Advanced Networks and Telecom Systems (ANTS) Conference, the latter he co-founded. He is the editor of Springer’s Optical Networks Book Series and served on several journal editorial boards, including IEEE/ACM Transactions on Networking and IEEE Network.   He received multiple awards for his scholarly and educational achievements and is the winner of the IEEE Communications Society's inaugural (2015) Outstanding Technical Achievement Award "for pioneering work on shaping the optical networking area". He was made an IEEE Fellow in 2006.

Ioannis Tomkos is a Professor of Optical Communications at the Department of Electrical and Computer Engineering at the University of Patras, Greece. His current research focuses on the use of optical communications systems for 5G/6G and datacenter networks. In the past he held numerous positions in both industry and academia positions in various countries around the world (e.g. USA, Spain, Cyprus, Italy and Greece). His research group is involved in over 25 EU-funded research projects with a consortium-wide leading role and he serves as Technical Manager for 10 major EU projects. His published work has received about 10.000 citations (h-factor=47).  In 2018, Dr. Tomkos was elected a Fellow of IEEE “forcontributions in Dynamic Optical Networks”. He is also a Fellow of the IET (2010) and a Fellow of the Optical Society (2012). 

Massimo Tornatore is currently an Associate Professor in the Department of Electronics, Information, and Bioengineering at Politecnico di Milano, where he received a Ph.D. degree in 2006.  He also holds an appointment as Adjunct Professor at University of California, Davis, USA and as visiting professor at University of Waterloo, Canada. His research interests include performance evaluation, optimization and design of communication networks (with an emphasis on the application of optical networking technologies), cloud computing, and machine learning application for network management. He has participated in several EU R&D projects as well as in several other projects in US, Canada and Italy.  Massimo Tornatore is a member of the Editorial Board of IEEE Communication Surveys and Tutorials, IEEE Communication Letters,  Springer Photonic Network Communications, and Elsevier’s Optical Switching and Networking.  He is an active member of the technical program committee of various networking conferences and a senior member of the IEEE.

Peter J. Winzer received his Ph.D. in electrical engineering from the Technical University of Vienna, Austria, in 1998. Supported by the European Space Agency, he investigated space-borne Doppler lidar and laser communications. From 2000 to 2019 he was at Bell Labs in NJ, where he focused on fiber-optic communication systems and networks and contributed to many high-speed optical transmission records and field trials up to 1 Tbit/s per carrier. Before leaving Bell Labs in 2019, he led its global optical communications research. Peter Winzer is actively involved with the IEEE Photonics Society and the Optical Society (OSA). He served as Editor-in-Chief of the IEEE/OSA Journal of Lightwave Technology and was Program Chair of both ECOC and OFC. Dr. Winzer is a Highly Cited Researcher, a Bell Labs Fellow, a Fellow of the IEEE and the OSA, and an elected member of the US National Academy of Engineering. He received multiple awards, including the John Tyndall Award.

Yongli Zhao is a full professor of State Key Laboratory of Information Photonics and Optical Communications at Beijing University of Posts and Telecommunications (BUPT). He is a senior member of IEEE and MIET member of IET. Yongli Zhao received his Ph.D. from BUPT in 2010. He received support within the Youth Talent Plan Beijing City (2013), as well as the National Science Fund for Excellent Young Scholars in China (2018). In the past five years, he has chaired and participated in more than 30 research projects, including the National High Technology Research and Development Program in China, the National Basic Research Program of China, and National Natural Science Foundation of China (NSFC) projects. He was a visiting associate professor at UC Davis (2016-2017).  His current research focuses on software defined optical networks, elastic optical networks, datacenter networking, machine learning in optical networks, optical network security, and quantum key distribution networking.