Ian F. Akyildiz
Ken Byers Chair Professor of Georgia Institute of Technology,
IEEE Fellow, ACM Fellow
Ian F. AKYILDIZ is the Ken Byers Chair Professor with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Director of the Broadband Wireless Networking Laboratory and Chair of the Telecommunications Group. He is an Honorary Professor with School of Electrical Engineering at the Universitat Politecnica de Catalunya, and Director of N3Cat (NaNoNetworking Center in Catalunya) in Barcelona, Spain, since June 2008. Dr. Akyildiz is also the Finnish Distinguished Professor with Tampere University of Technology, Tampere, Finland since January 2013.
He is the Editor-in-Chief of Computer Networks (Elsevier) Journal since 2000, the founding Editor-in-Chiefs of the Ad Hoc Networks Journal (2003), Physical Communication (PHYCOM) Journal (2008), and Nano Communication Networks (NANOCOMNET) Journal (2010) all published by Elsevier.
Dr. Akyildiz is an IEEE FELLOW (1996) and an ACM FELLOW (1997). He received the 1997 IEEE Leonard G. Abraham Prize award and the 2003 Best Tutorial Paper Award and the Best Paper Awards at IEEE ICC, June 2009 and IEEE Globecom 2010 conferences.
He served as a National Lecturer for ACM from 1989 until 1998 and received the ACM Outstanding Distinguished Lecturer Award for 1994. Dr. Akyildiz received the 2002 IEEE Harry M. Goode Memorial award and the 2003 ACM SIGMOBILE Outstanding Contribution Award.
Dr. Akyildiz received the 2004 Georgia Tech Faculty Research Author Award. He also received the 2005 Distinguished Faculty Achievement Award from School of ECE, Georgia Tech, and the Georgia Tech Outstanding Doctoral Thesis Advisor Award. He also received the 2009 ECE Distinguished Mentor Award by the School of ECE at Georgia Tech.
Dr. Akyildiz received the 2010 IEEE Communications Society Ad Hoc and Sensor Networks Technical Committee (AHSN TC) Technical Recognition Award with the citation: "For pioneering contributions to wireless sensor networks and wireless mesh networks", in December 2010. He received the 2011 IEEE W. Wallace McDowell Award for pioneering contributions to wireless sensor network architectures and communication protocols and the 2011 TUBITAK (Turkish National Science Foundation) Exclusive Award for outstanding contributions to the advancement of scholarship/research at international level.
He is the author of two textbooks on "Wireless Sensor Networks" and on "Wireless Mesh Networks" published by John Wiley & Sons in 2010 and 2007, respectively. Due to Google scholar, his papers received over 75+K citations and his h-index is 93 as of November 2015.
His current research interests are in 5G Cellular Systems, Nanonetworks, Cognitive Radio Networks and Wireless Sensor Networks.
Title: SoftAir: Software Defined Networking for 5G Cellular Systems
Speaker: Ian. F. Akyildiz
In order to meet the ever-growing need for wireless data and services, 5G cellular systems are advocating fundamental advances in both utilizing the radio access spectrum efficiently and providing efficient data and service delivery through new system architectures. New research pillars are set for 5G cellular systems spanning over the next 15 years. In particular, the objectives for 5G cellular systems are achieving the ultra high capacity (1000x capacity/km2), ultra high data rates (100x), always connected to best networks, high mobile cyber security, energy savings (90%) and enormous cost reduction, reduced latency (RAN latency less than 1ms), flexible network architectures (software defined networking) and connection of Billions of Things and People (7 billion people and 7 trillion things). In this talk these research pillars are explained in detail and open research challenges are presented.
One of the main building blocks and major challenges for 5G cellular systems is the design of flexible network architectures which can be realized by the software defined networking paradigm. Existing commercial cellular systems rely on closed and inflexible hardware-based architectures both at the radio frontend and in the core network. These problems significantly delay the adoption and deployment of new standards, impose significant challenges in implementing and innovation of new techniques to maximize the network capacity and accordingly the coverage, and prevent provisioning of truly- differentiated services which are able to adapt to growing and uneven and highly variable traffic patterns.
In this talk, a new software-defined architecture, called SoftAir, for next generation (5G) wireless systems, is introduced. Specifically, the novel ideas of network function cloudification and network virtualization are exploited to provide a scalable, flexible and resilient network architecture. Moreover, the essential enabling technologies to support and manage the proposed architecture are discussed in detail, including fine-grained base station decomposition, seamless incorporation of Open-flow, mobility-aware control traffic balancing, resource-efficient network virtualization, and distributed and collaborative traffic classification. Furthermore, the major benefits of SoftAir architecture with its enabling technologies are showcased by introducing software- definedtraffic engineering solutions. The challenging issues for realizing SoftAir are also discussed in detail.
University of California, Davis
Biswanath Mukherjee is Distinguished Professor at University of California, Davis, where he has been a faculty member since 1987 and was Chairman of Computer Science during 1997-2000. He received the BTech degree from Indian Institute of Technology, Kharagpur (1980) and PhD from University of Washington, Seattle (1987). He was General Co-Chair of the IEEE/OSA Optical Fiber Communications (OFC) Conference 2011, Technical Program Co-Chair of OFC'2009, and Technical Program Chair of the IEEE INFOCOM'96 conference. He is Editor of Springer's Optical Networks Book Series. He has served on eight journal editorial boards, most notably IEEE/ACM Transactions on Networking and IEEE Network. In addition, he has Guest-Edited Special Issues of Proceedings of the IEEE, IEEE/OSA Journal of Lightwave Technology, IEEE Journal on Selected Areas in Communications, and IEEE Communications.
To date, he has supervised 64 PhDs to completion and currently mentors 18 advisees, mainly PhD students. He is winner of the 2004 Distinguished Graduate Mentoring Award and the 2009 College of Engineering Outstanding Senior Faculty Award at UC Davis. He is co-winner of ten Best Paper Awards from various conferences, including Optical Networking Symposium Best Paper Awards at IEEE Globecom 2007 and 2008. He is author of the graduate-level textbook Optical WDM Networks (Springer, January 2006). He served a 5-year term on Board of Directors of IPLocks, a Silicon Valley startup company (acquired by Fortinet). He has served on Technical Advisory Board of several startup companies, including Teknovus (acquired by Broadcom). He is founder of Ennetix and Skydoot, two startup companies incubated at UC Davis. He is winner of the IEEE Communications Society's inaugural (2015) Outstanding Technical Achievement Award "for pioneering work on shaping the optical networking area". He is an IEEE Fellow.
Title: Disaster Resilience of Telecom Infrastructure
Speaker: Biswanath Mukherjee
To combat the rising risk of disasters (e.g., hurricanes, earthquakes, tornados, flooding, etc.) against our national/global interests and economic wellbeing - events which could lead to a domino effect of catastrophic failures of telecommunications, power, transportation, financial, and other critical infrastructures - novel methods are needed to provide protection in our information and communication networks. Topics such as the following will be discussed in this talk: normal preparedness, enhanced preparedness, degraded service under resource crunch, content connectivity (vs. network connectivity) due to the increasing deployment of cloud services, correlated cascading failures in interdependent networks, etc.
Zhi-Quan Tom Luo
Vice President (Academic) at the Chinese University of Hong Kong, Shenzhen Professor of University of Minnesota
IEEE Fellow, SIAM Fellow
Luo Zhi-Quan (Tom) received his B.Sc. degree in Applied Mathematics in 1984 from Peking University, Beijing, China. Subsequently, he was selected by a joint committee of American Mathematical Society and the Society of Industrial and Applied Mathematics to pursue Ph.D. study in the United States. After an one-year intensive training in mathematics and English at the Nankai Institute of Mathematics, Tianjin, China, he studied in the Operations Research Center and the Department of Electrical Engineering and Computer Science at MIT, where he received a Ph.D. degree in Operations Research in 1989. From 1989 to 2003, Dr. Luo held a faculty position with the Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada, where he eventually became the department head and held a Canada Research Chair in Information Processing. Since April of 2003, he has been with the Department of Electrical and Computer Engineering at the University of Minnesota (Twin Cities) as a full professor and holds an endowed ADC Chair in digital technology. His research interests include optimization algorithms, signal processing and digital communication. He is currently serving as the Vice President (Academic) at the Chinese University of Hong Kong, Shenzhen.
Dr. Luo is a fellow of SIAM and IEEE, and serves as the past chair of the IEEE Signal Processing Society Technical Committee on the Signal Processing for Communications (SPCOM). He is a recipient of the 2004, 2009 and 2011 IEEE Signal Processing Society's Best Paper Awards, the 2015 IEEE Signal Processing Magazine Best Paper Award, the 2010 Farkas Prize from the INFORMS Optimization Society, the 2010 EURASIP Best Paper Award and the 2011 ICC Best Paper Award. He has held editorial positions for several international journals including the Journal of Optimization Theory and Applications, SIAM Journal on Optimization, and Mathematics of Computation. He served as the Editor-in-Chief for the journal IEEE Transactions on Signal Processing from 2012-2014. He currently serves on the editorial boards of several journals including Management Science, IEEE Journal of Special Topics on Signal Processing and Mathematics of Operations Research. He was elected to the Royal Society of Canada in 2014.
Title: Dynamic Resource Allocation for Energy Efficient Transmission in Digital Subscriber Lines
Speaker: Zhi-Quan Tom Luo
Linear matrix precoding, also known as vectoring, is a well-known technique to mitigate multiuser interference in the downlink Digital Subscriber Line (DSL) transmission. While effective in canceling interference, vectoring does incur major computational overhead in terms of a matrix vector multiplication at each data frame, resulting in significant energy consumption when the number of lines is large. To facilitate energy efficient transmission, it has been recently proposed (in the G.fast standard) that each data frame is divided into a normal operating interval (NOI) and a discontinuous interval (DOI). In the NOI, all lines (or users) are involved in a common vectoring group, which requires a large matrix precoder, while in a DOI, the lines are subdivided into multiple small non-overlapping vectoring subgroups, which are transmitted in a TDMA manner within the data frame. Because of the use of small matrix precoders for the small vectoring subgroups in DOI, the energy efficiency can be significantly improved. In this paper, we consider several key dynamic resource allocation (DRA) problems in DSL: given the instantaneous buffer state, determine the number of transmission opportunities allocated to each line, the optimal NOI and DOI size in each data frame as well as the optimal grouping in DOI. We formulate these optimal DRA problems and propose efficient real-time algorithms for three main tasks: given a data frame, allocate transmission opportunities for all lines, design grouping strategy in DOI, and optimally adjust the durations of the NOI and the vectoring subgroups in the DOI. The simulation results show the efficiency and the effectiveness of our algorithms.
Professor, University of Washington
Dr. Jenq-Neng Hwang received the BS and MS degrees, both in electrical engineering (EE) from the National Taiwan University, Taipei, Taiwan, in 1981 and 1983 separately. He then received his Ph.D. degree from the University of Southern California. In the summer of 1989, Dr. Hwang joined the Department of Electrical Engineering of the University of Washington in Seattle, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research from 2011 to 2015 and is currently the Associate Chair for Global Affairs in the EE Department. He has written more than 300 journal, conference papers and book chapters in the areas of multimedia signal processing, and multimedia system integration and networking, including a textbook on “Multimedia Networking: from Theory to Practice,” published by Cambridge University Press. Dr. Hwang has close working relationship with the industry on multimedia signal processing and multimedia networking.
Dr. Hwang received the 1995 IEEE Signal Processing Society's Best Journal Paper Award. He is a founding member of Multimedia Signal Processing Technical Committee of IEEE Signal Processing Society and was the Society's representative to IEEE Neural Network Council from 1996 to 2000. He is currently an advisory member of Multimedia Technical Committee (MMTC) of IEEE Communication Society and also a member of Multimedia Signal Processing (MMSP) and Internet of Things (IoT) of IEEE Signal Processing Society. He served as an associate editor for IEEE T-SP, T-NN, T-CSVT, IEEE T-IP, and IEEE Signal Processing Magazine, as well as an Editor for JISE, ETRI, JSPS, and IJDMB. He was the Program Co-Chair of ICASSP 1998 and ISCAS 2009, and is the Program Co-Chair for ICME 2016. Dr. Hwang is a fellow of IEEE since 2001.
Title: Cross-Layer QoE and QoC Optimization for Wireless Video Networking
Speaker: Jenq-Neng Hwang
With the huge amount of networked fixed or mobile video cameras installed everywhere nowadays, there is an urgent need of effective networking to collect and disseminate these big visual data, so as to perform intelligent data analytics in the server side and/or to provide best streaming services in the client side. In this talk, taking advantage of the quality of experience (QoE) and quality of content (QoC) criteria, I will present several cross-layer mobile video networking techniques, based on MIMO or Multi-RAT scheme, over 4G wireless infrastructures among an array of networked cameras.
Professor, University of Electronic Science and Technology of China (UESTC), China
Dr Ying-Chang Liang (F’11) is a “National Thousand Talent Program” Professor in the University of Electronic Science and Technology of China (UESTC), China. Before that, he was a Principal Scientist and Technical Advisor in the Institute for Infocomm Research, A*SATR, Singapore, an adjunct faculty in National University of Singapore and Nanyang Technological University, Singapore, and a visiting scholar in the Department of Electrical Engineering, Stanford University, USA. His research interest lies in the general area of wireless networking and communications, with current focus on applying artificial intelligence, big data analytics and machine learning techniques to the design and optimization of wireless networks. Dr Liang was elected a Fellow of the IEEE in December 2010, and was recognized by Thomson Reuters as a “Highly Cited Researcher” in 2014 and 2015. He received IEEE Jack Neubauer Memorial Award in 2014, the First IEEE Communications Society APB Outstanding Paper Award in 2012, and the EURASIP Journal of Wireless Communications and Networking Best Paper Award in 2010. He also received the Institute of Engineers Singapore (IES)’s Prestigious Engineering Achievement Award in 2007, and the IEEE Standards Association’s Outstanding Contribution Appreciation Award in 2011, for contributions to the development of IEEE 802.22 standard. Dr Liang is now serving as the Chair of IEEE Communications Society Technical Committee on Cognitive Networks. He is on the Editorial Board of IEEE Signal Processing Magazine, and IEEE Transactions on Signal and Information Processing over Networks, and is an Associate Editor-in-Chief of the World Scientific Journal on Random Matrices: Theory and Applications. He served as Founding Editor-in-Chief of IEEE Journal on Selected Areas in Communications – Cognitive Radio Series, and was the key founder of the new journal IEEE Transactions on Cognitive Communications and Networking. He was an Editor of IEEE Transactions on Wireless Communications from 2002 to 2005, and an Associate Editor of IEEE Transactions on Vehicular Technology from 2008 to 2012, and a (Leading) Guest Editor of five special issues on emerging topics published in IEEE, EURASIP and Elsevier journals. Dr Liang was a Distinguished Lecturer of the IEEE Communications Society and the IEEE Vehicular Technology Society, and has been a member of the Board of Governors of the IEEE Asia-Pacific Wireless Communications Symposium since 2009. He served as Technical Program Committee (TPC) Chair of CROWN’08 and DySPAN’10, Symposium Chair of ICC’12 and Globecom’12, General Co-Chair of ICCS’10 and ICCS’14. He serves as TPC Chair and Executive Vice-Chair of Globecom’17 to be held in Singapore.
Title: Wireless Big Data: Transforming Cognitive Radios to Smart Networks
Speaker:Dr Ying-Chang Liang
The future wireless networks are expected to support the explosive growth of mobile data with various types of services. To meet this challenging requirement, wireless networks should be operated in smarter ways in resource utilization, network operation, and service provisioning. In this talk, I will highlight how wireless big data can help to transform cognitive radios to smart networks.
Professor of Xidian University
Chair of cognitive and communication signal research center in State Key Laboratory of Integrated Services Networks (ISN) of China
Yangtze River scholar of Education Ministry of China
Zan Li, received her Ph.D degree at Xidian University, China, in 2006. Currently, she is a professor of Xidian University and the chair of cognitive and communication signal research center in State Key Laboratory of Integrated Services Networks (ISN) of China. She is IEEE Senior Member and the associated editor of the International Journal of Communications Systems. Meanwhile, she is also the editorial board member of some international journals. She is the general chair of IEEE CITS 2016 and served as the organizing committee co-chair of IEEE CIT 2014. She also served as the technical program committee member of IEEE GLOBECOM 2015, IEEE ICC 2015, and so on. She was recruited as the Yangtze River scholar of Education Ministry of China and awarded the thirteenth “China Youth Science and Technology Award”. Her current research interests include cognitive frequency hopping, wireless communication signal processing, and spectrum sensing. She has been in charge of more than 30 researching projects, including the Major National Science and Technology Projects of China, the National 863 project of China, and the National Natural Science Foundation of China. Up to now, she has published more than 140 papers academic journals and conference, such as IEEE Trans. on Communications and IEEE GLOBECOM.
Title: Intelligent FH Sequence in High Security Cognitive FHMA Network
In modern high-dynamic and complicated electromagnetic environment, the information transmission of the counter-terrorism or other high security applications requires strong anti-jamming and anti-interception capability. Recently, a new technique named cognitive frequency hopping (FH) is proposed to realize the high security, reliability and efficient communication. As one of the key technologies for the FH commutation, the performance of the FH sequence, which controls the frequency regularity of the FH signal, determines the anti-intercept performance of the cognitive FHMA network and its typical application—the FH multiple-access (FHMA) network—in practices. This talk will introduce some of our works on study intelligent anti-jamming FH sequence based on the requirement of the high security cognitive FHMA network. The construction of generating the family of intelligent anti-jamming FH sequence is proposed based on the cognitive system requirement, and the two complexity metrics based on the information entropy are proposed to evaluate the anti-cryptanalysis ability of the FH sequence. The multiple-access performance of FH sequences is also discussed when its application in cognitive FHMA network. Accordingly, this intelligent anti-jamming FH sequence could be extensively applied in cognitive FHMA network, especially for the high security scene such as counter-terrorism, for its high complexity and network throughput.