Giuseppe Caire was born in Torino, Italy, in 1965. He received the B.Sc. in Electrical Engineering from Politecnico di Torino (Italy), in 1990, the M.Sc. in Electrical Engineering from Princeton University in 1992 and the Ph.D. from Politecnico di Torino in 1994. He has been a post-doctoral research fellow with the European Space Agency (ESTEC, Noordwijk, The Netherlands) in 1994-1995, Assistant Professor in Telecommunications at the Politecnico di Torino, Associate Professor at the University of Parma, Italy, Professor with the Department of Mobile Communications at the Eurecom Institute, Sophia-Antipolis, France, a Professor of Electrical Engineering with the Viterbi School of Engineering, University of Southern California, Los Angeles, and he is currently an Alexander von Humboldt Professor with the Electrical Engineering and Computer Science Department of the Technical University of Berlin, Germany.
He served as Associate Editor for the IEEE Transactions on Communications in 1998-2001 and as Associate Editor for the IEEE Transactions on Information Theory in 2001-2003. He received the Jack Neubauer Best System Paper Award from the IEEE Vehicular Technology Society in 2003, the IEEE Communications Society & Information Theory Society Joint Paper Award in 2004 and in 2011, the Okawa Research Award in 2006, the Alexander von Humboldt Professorship in 2014, and the Vodafone Innovation Prize in 2015. Giuseppe Caire is a Fellow of IEEE since 2005. He has served in the Board of Governors of the IEEE Information Theory Society from 2004 to 2007, and as officer from 2008 to 2013. He was President of the IEEE Information Theory Society in 2011. His main research interests are in the field of communications theory, information theory, channel and source coding with particular focus on wireless communications.
Modern society depends on faster, safer, and environment friendly transportation system. Vehicular communications network in terms of vehicle to vehicle, vehicle to infrastructure, vehicle to pedestrian, vehicle to cloud, and vehicle to sensor, can provide a solution to modern transportation system. In this talk, we first introduce the all connected vehicles. We then present the applications, challenges and scientific research issues of vehicular communications network. We also explain the role of vehicular networking in the automated driving era. We conclude the talk by discuss the future Space-Air-Ground (SAG) Integrated vehicular networks and related research results.
Xuemin (Sherman) Shen (IEEE Fellow) is a University Professor and Associate Chair for Graduate Studies, Department of Electrical and Computer Engineering, University of Waterloo, Canada. Dr. Shen's research focuses on wireless resource management, wireless network security, wireless body area networks, smart grid and vehicular ad hoc and sensor networks. He is the Editor-in-Chief of IEEE IoT Journal. He serves as the General Chair for Mobihoc'15, the Technical Program Committee Chair for IEEE GC'16, IEEE Infocom'14, IEEE VTC'10, the Symposia Chair for IEEE ICC'10, the Technical Program Committee Chair for IEEE Globecom'07, the Chair for IEEE Communications Society Technical Committee on Wireless Communications. Dr. Shen is the elected VP Publication of IEEE ComSoc, and was the chair of IEEE ComSoc Distinguish Lecturer selection committee and a member of IEEE ComSoc Fellow evaluation committee. Dr. Shen received the Excellent Graduate Supervision Award in 2006, and the Premier's Research Excellence Award (PREA) in 2003 from the Province of Ontario, Canada. Dr. Shen is a registered Professional Engineer of Ontario, Canada, an IEEE Fellow, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, a Royal Society of Canada Fellow, and a Distinguished Lecturer of IEEE Vehicular Technology Society and Communications Society.
The explosive growth in data collection is accelerating the use of machine learning in many IoT applications and shaping our networked life. In particular, private data is often collected based on “informed consent," where users decide whether to report data or not based upon who is collecting the data. This approach is however untenable, because of vague privacy policies and a behind-the-scenes data brokerage market becoming the norm. Indeed, data privacy has become one notorious threat in human civilization, as evidenced by the very recent Facebook scandal. Two fundamental issues remain open: (i) users have no control of data privacy after reporting private data and the use of data is without their knowledge; and (ii) the data collector has sole liability to protect users' private data.
Making a paradigm shift, this study advocates a new approach to privacy-preserving data collection for IoT applications: users control their own data privacy by reporting data with noise injection, and the data collector provides rewards in exchange for receiving more accurate data. We first consider the basic case where each user reports data based on her own data, and show that the user data reporting strategy at the Nash Equilibrium is either symmetric randomized response or non-informative strategy. Then, we zero in on the more sophisticated case where users can also share (noisy versions of) their private data with social friends. Based on both her private data and her friends’ noisy data, each user makes strategic decisions to report privacy-preserving data. We develop a Bayesian game theoretic framework to study the impact of social sharing on users’ data reporting strategies and devise the payment mechanism for the data collector. Our findings reveal that both the data collector and the users benefit from social sharing under some conditions.
Junshan Zhang received his Ph.D. degree from the School of ECE at Purdue University in 2000. He joined the School of ECEE at Arizona State University in August 2000, where he has been Fulton Chair Professor since 2015. His research interests fall in the general field of information networks and data science, including communication networks, Internet of Things (IoT), Fog Computing, social networks, smart grid. His current research focuses on fundamental problems in information networks and data science, including Fog Computing and its applications in IoT and 5G, IoT data privacy/security, optimization/control of mobile social networks, cognitive radio networks, stochastic modeling and optimization for smart grid.
Prof. Zhang is a Fellow of the IEEE, and a recipient of the ONR Young Investigator Award in 2005 and the NSF CAREER award in 2003. He received the IEEE Wireless Communication Technical Committee Recognition Award in 2016. His papers have won a few awards, including the Kenneth C. Sevcik Outstanding Student Paper Award of ACM SIGMETRICS/IFIP Performance 2016, the Best Paper Runner-up Award of IEEE INFOCOM 2009 and IEEE INFOCOM 2014, and the Best Paper Award at IEEE ICC 2008 and ICC 2017. Building on his research findings, he co-founded Smartiply Inc in 2015, a Fog Computing startup company delivering boosted network connectivity and embedded artificial intelligence. Prof. Zhang was TPC co-chair for a number of major conferences in communication networks, including IEEE INFOCOM 2012 and ACM MOBIHOC 2015. He was the general chair for ACM/IEEE SEC 2017, WiOPT 2016, and IEEE Communication Theory Workshop 2007. He was a Distinguished Lecturer of the IEEE Communications Society. He is currently serving as an editor-at-large for IEEE/ACM Transactions on Networking and an editor for IEEE Network Magazine.