Wireless Network Economics and Games
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Lecturer: Jianwei Huang Associate Professor and Director of Master of Science Program Department of Information Engineering The Chinese University of Hong Kong |
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Abstract: Today's communication networks are highly complex, carry heterogeneous traffic in diverse environments, and are often owned by multiple profit-making entities. To successfully maintain, optimize, and upgrade such large distributed networks, it is important to design new economic incentive mechanisms as well as develop new technologies. The deregulation of the telecommunication industry in many countries makes the interactions between government regulators, commercial network operators, and consumers increasingly complex. Such interactions often can be best understood from a game theoretical point of view. The latest development of wireless access networks, such as small cell technologies, dynamic spectrum sharing, and cooperative communication schemes, bring many new economical issues in network planning, deployment, and operations. The objective of this tutorial is to introduce key economic and game theoretical issues in the development of modern wireless communication networks. We will provide a short introduction on game theory and network economics, including static game and Nash equilibrium, dynamic games and subgame perfect equilibrium, games with incomplete information, price differentiation, oligopoly competition, and network externality. Then we will illustrate relevant applications in wireless communications, through case studies of femtocell economics, Wi-Fi data offloading, cellular network upgrade, cooperative spectrum bargaining, dynamic spectrum leasing, and spatial spectrum sharing. The tutorial will help the conference attendees to get a good exposure of this fast-growing and fascinating interdisciplinary research area, and enough background information to appreciate the important theoretical and practical issues in the related industry. |
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Lecturer's short biography: Jianwei Huang is an Associate Professor in the Department of Information Engineering at the Chinese University of Hong Kong. He received Ph.D. in Electrical and Computer Engineering from Northwestern University in 2005, and worked as a Postdoc Research Associate at Princeton University during 2005-2007. Dr. Huang leads the Network Communications and Economics Lab, with the main research focus on nonlinear optimization and game theoretical analysis of networks, especially on network economics, cognitive radio networks, and smart grid. He is the recipient of the IEEE Marconi Prize Paper Award in Wireless Communications in 2011, and a co-author of Best Paper Awards from IEEE WiOpt 2013, SmartGridComm 2012, WiCON 2011, GLOBECOM 2010, and APCC 2009. He received the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009. Dr. Huang has served as Associate Editor-in-Chief of IEEE ComSoc Technology News, Editor of IEEE Journal on Selected Areas in Communications - Cognitive Radio Series, Editor of IEEE Transactions on Wireless Communications, Guest Editor of IEEE Journal on Selected Areas in Communications special issue on "Economics of Communication Networks and Systems", Lead Guest Editor of IEEE Journal of Selected Areas in Communications special issue on "Game Theory in Communication Systems", and Lead Guest Editor of IEEE Communications Magazine Feature Topic on "Communications Network Economics". Dr. Huang is the Chair of IEEE ComSoc Multimedia Communications Technical Committee, and is a Steering Committee Member of IEEE Transactions on Multimedia and IEEE ICME. He has served as a TPC Co-Chair of IEEE SmartGridComm Demand Response and Dynamic Pricing Sympoisum 2014, NetGCoop 2014, IEEE GLOBECOM SAC Symposium (Game Theory for Communications Track) 2013, IEEE WiOpt 2012, IEEE ICCC Communication Theory and Security Symposium 2012, IEEE GlOBECOM Wireless Communications Symposium 2010, IWCMC Mobile Computing Symposium 2010, and GameNets 2009. He has been a TPC member of IEEE INFOCOM (2009-2014) and ACM Mobihoc (2009, 2012, 2013). He is a Senior Member of IEEE. |
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Convergence of IoT and Social Networks Issues
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Lecturer: Antonio Iera Full Professor of Telecommunications Director of Laboratory for Advanced Research into Telecommunication Systems University Mediterranea, Reggio Calabria |
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Abstract: In the IoT, all that is real becomes virtual (each person and thing has a locatable, addressable, and readable counterpart in the Internet) and the role of any object is to produce and consume services. The IoT paradigm, at its present stage of evolution relies on the presence of new generations of "smart objects" able to discover new services, start new acquaintances, exchange information, connect to external services, exploit other objects' capabilities, and collaborate towards a common goal. We are now living the age of the Social Networks, which rule great part of the interactions and communication exchanges among people. Also ongoing is the development of a new generations of social objects, which: are able to mutually interact in an autonomous way with respect to the owners, can easily crawl the IoT made of billions of objects to discover services and information in a trust-oriented way, and are able to advertise their presence to provide services to the rest of the network. This pushes IoT to evolve towards a social IoT where the concepts and technologies typical of social networks are applied to the world of things to foster resource visibility, service discovery, object reputation assessment, source crowding, and service composition. Focus of the speech will thus be the convergence of the Internet of Things (IoT) and Social Network paradigms towards the deployment of a social network in which things are nodes that establish social links as humans do. The speech will follow a holistic approach by capitalizing experiences coming mostly from the research areas of social networking and IoT, to introduce the audience to a unifying paradigm. All the different aspects of the cited topic will be thoroughly addressed by finalizing them to the constitution of the background for the definition of new paradigms for data networking in the future Internet; models that should be based on the way the resources interact each other over the time. |
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Lecturer's short biography: Antonio Iera graduated in Computer Engineering at the University of Calabria, Italy, in 1991 and received a Master Diploma in Information Technology from CEFRIEL/Politecnico di Milano, Italy, in 1992 and a Ph.D. degree from the University of Calabria, Italy, in 1996. From 1994 to 1995 he has been with the Mobile Network Division Research Center, Siemens AG - Munich, Germany and since 1997 with the University Mediterranea, Reggio Calabria, where he currently holds the positions of full professor of Telecommunications and Director of the ARTS (www.arts.unirc.it) - Laboratory for Advanced Research into Telecommunication Systems. He served as TPC member of several IEEE International Conferences and has been co-Guest Editor for different special issues in the IEEE Wireless Communications Magazine. Elevated to the IEEE Senior Member status in 2007. His research interests include: Next generation mobile systems, Advanced Systems for Personal Communications, RFID systems, and Internet of Things. |
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Security, Privacy and Trust in IoT and M2M
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Lecturer: Joseph Teo Chee Ming Scientist Sense and Sense-ability Program Institute for Infocomm Research, A*STAR |
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Abstract: As Internet of Things (IoT) and M2M technologies become more prevalent, it is important to ensure that the IoT and M2M remains secure, trusted and privacy-enabled. Otherwise, attackers and hackers could break into the IoT and M2M devices and cause tremendous damages. In this talk, we first explore the threats and vulnerabilities that affect IoT and M2M technologies, i.e. what can the attacker do. Next, we study the challenges and issues for security, privacy and trust in IoT and M2M. We shall then look at how we can evaluate the security, privacy and trust schemes for IoT and M2M. With that, we can then introduce and discuss the topics and areas in Security, Privacy and Trust for IoT and M2M. Finally, we shall also look at some current efforts around the world to standardize the IoT and M2M, especially in the area of IoT and M2M security. |
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Lecturer's short biography: Dr. Joseph Teo Chee Ming is a Scientist with the Institute for Infocomm Research, A*STAR, Singapore since 2008. He is also the Principal Investigator (PI) for an A*STAR SERC-funded project named Security, Privacy and tRust Framework platform for Large-Scale Heterogeneous Wireless Sensor and Actuator Networks (SPARK) in collaboration with Nanyang Technological University, Singapore. He has been actively working in the research areas of Security, Privacy and Trust for wireless networks since 2004 and has published numerous journal and conference papers in these areas. His current research interests includes Wireless network security, Authentication, Privacy, Key Management, Trust, Smart Grid Security, mobile healthcare, vehicular network security, mesh network security and IoT/M2M Security. He was also heavily involved in the IEEE standardization works, contributing extensively in the security communications portion of IEEE 802.16 WiMAX standards. To date, he has 2 patents pending in this standard. He also held the officer role of Secretary for the IEEE 802.11ah Sub?1GHz Task Group from 2011 til 2012. |
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IoT/M2M Big Data Analytics: from Static to Streaming data
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Lecturer: Mahmoud Daneshmand
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Abstract: The Big Data of the future will be generated by Internet of Things (IoT) i.e., "things" connected to the Internet. IoT may be simplified as: "Sensors/RFID devices + Communications". Billions of "things" such as sensors/RFID, mobility devices & smart phones are generating mountains of data on all aspects of the human life: health, environment, transportations, security, shopping, smart cities, smart grids, home, etc. The Biggest Challenge of the current Big Data Era is management and mining of ever-increasing streams of data generated by these devices. "Without stream processing, there's no Big Data and no Internet of Things", (Dana Sandu, March 19, 2014). This lecture will cover Big Data Analytics methodologies applicable to Static Data as well as Streaming IoT/M2M data. Topics include: an end-to-end framework for data mining; well-known analytical methodologies, techniques, algorithms, and models developed and successfully applied to the Static data over the last 15+ years; an overview of IoT architecture; the stream data model; data streams quality; and most recent & emerging techniques invented for Stream Data Analytics. Practical as well theoretical basis of algorithms will be covered. Many real world applications will be presented. Future research directions and opportunities for real-time large scale IoT/M2M Big Data Streams Analytics are suggested. |
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Lecturer's short biography: Mahmoud Daneshmand is an Industry Professor of Business Intelligence & Analytics at Howe School of Technology Management, Stevens Institute of Technology. He has more than 35 years of teaching, research & publications, consultation, and management experience in academia & industry including: Bell Laboratories, AT&T Shannon Labs - Research, University of California at Berkeley, University of Texas at Austin, Sharif University of Technology, University of Tehran, New York University, and Stevens Institute of Technology. He has served as Distinguished Member of Technical Staff (DMTS) at Bell Labs as well as AT&T Shannon Labs-Research; Technology Leader at AT&T Labs; Assistant Chief Scientist of AT&T Labs; Founder and Executive Director of the AT&T Labs university collaborations program. He is an Industry Professor at Howe School of Technology Management, Departments of Computer Science as well as Financial Engineering, and Co-Founder of the Business Intelligence & Analytics MS program at Stevens Institute of Technology. He is an expert in Big Data Analytics, Internet of Things (IoT)/Sensor & RFID Data Streams Analytics, Data Mining Algorithms, Machine Learning, Probability & Stochastic Processes, and Statistics. He is experienced in Risk Management, Quality and Reliability of IP-Based Services and Applications. He has published more than 96 Journal and conference papers; authored/co-authored three books; holds two patents (2009 and 2010). He holds key leadership roles with IEEE Journals Publications as well as IEEE Major Conferences including: Co-Founder and Chair of Steering Committee of New IEEE Journal of Internet of Things; Steering Committee of new IEEE Transactions on Big Data; Guest Editor of several IEEE Journal Special Issues; Keynote Speaker of many IEEE as well as other International Conferences; Executive Committee of Globecom as well as ICC; Chair of Steering Committee of IEEE ISCC; and General Chair and Technical Chair of many IEEE conferences. He has a PhD and MS in Statistics from the University of California, Berkeley, and MS and BS in Mathematics from the University of Tehran. He is the founder of the Department of Statistics and co-founder of the School of Informatics and Management Sciences of the National University of Iran. He has served as Chairman of the Department of Statistics and Dean of the School of Informatics & Management Sciences of the National University. Mahmoud is well recognized within the academia and industry. A partial list of his recent technical accomplishments include: Guest Editor , IEEE Sensors Journal SI on Internet of Things (to be published September 2013); Guest Editor of IEEE Communications Magazine (published in Feb 2011), Guest Editor of Journal of Networks and System Management (published September 2011); Keynote Speaker , The 2013 IEEE International Conference on Internet of Things (iThings2013), Beijing, China, August 20-23, 2013; Keynote Speaker , International Conference on Cyber-enabled distributed computing and Knowledge Discovery, 10-12, October 2013, Beijing, China; Keynote Speaker : ISITCE 2012 (South Korea), IEEE ISCC 2011 (Corfu), ICC 09 (Dresden), IEEE ISCC 2008 (Marrakesh), ICT 2008 (St. Petersburg), IMSEE 2000 (Tehran), and ICISTM 2008 (Dubai); Co-editor of three IEEE Proceedings on Computers and Communications with a total of more than 450 peer reviewed accepted technical papers (ISCC 2002, ISCC 2006 , and ISCC 2010); innovated and led execution of more than 60 Bell Labs and AT&T Labs large-scale projects on computer and communications; served as analytics and statistics consultant in many research, business and operations projects; made extensive contributions to the Industry Standards and regulatory organizations including ITU, ANSI, and FCC (invented the well known standardized Networks Outage Index). He has chaired multiple international conferences including IEE 2003 (London), IEEE ISCC 2002 (Sicily), IEEE ISCC 2006 (Sardinia, Italy), WICON 2010 (Singapore), and IEEE ISCC 2010 (Riccione, Italy), and Cyber Security (China 2011). Organized and served as Keynote Chair and Panel Chair of many IEEE conference in including: ICC 2007 (Glasgow, Scotland), ICC 2009 (Dresden, Germany), GLOBECOM 2009 (Hawaii, US), NOMS 2010 (Osaka, Japan), GLOBECOM 2010 (Miami, US), GLOBECOM 2011 (Houston), NOMS 2012 (Hawaii), INFOCOM 2012 (New Orleans), GLOBECOM 2012 (Anaheim), and GLOBECOM 2014 (Austin, TX); Held and chaired AT&T Labs annual Academia-Industry Joint Research Collaborations Symposiums (UC Symposiums 2005, 2006, 2007, 2008, 2009, and 2010). He served as a member of Advisory Board of Center for Networked Systems at the University California San Diego; Advisory Board of SATM (Stevens Alliance for Technology Management); Editorial Board of the JNSM (Journal of Network and Systems Management). |
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Optimization and Inference for Cyber Security in Complex Engineered Networks
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Lecturer: Chee Wei Tan Assistant Professor City University Hong Kong |
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Abstract: Networks represent a fundamental medium for spreading and diffusion of various types of behavior and information. Spreading processes are those where the actions, infections or failure of certain nodes increase the susceptibility of other nodes to the same; this results in the successive spread of infections / failures / other phenomena from a small set of initial nodes to a much larger set. Examples include (a) online social networks: cascading processes provide natural models for understanding both the consumption of online media (e.g. viral videos, news) and spread of opinions on online social networks such as Twitter, (b) online viral marketing: predicting uptake on social buying sites like Groupon etc., (c) security and reliability: epidemic-like spreading of computer virus and malware, and cascading failures of in large complex engineered networks such as the Internet of Things and Smart Grid, (d) social computing in big data: to spot an Internet hoax, verify a Tweet, and timely quarantine to enhance network resilience and limit the damage caused. This tutorial will focus on theories and algorithms for optimization and network inference in these complex engineered networks. Algorithm design based on statistical inference, maximum likelihood estimation and their advances will then be explained with step-by-step instructions for reliable network forensics. Finally, new cyber security protocols and their software implementation in practical complex engineered networks will be introduced. |
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Lecturer's short biography: Chee Wei Tan is an Assistant Professor at the City University of Hong Kong. He received his B.S. from the National University of Singapore and M.A. and Ph.D. degree from Princeton University all in Electrical Engineering. He was a Postdoctoral Scholar at the California Institute of Technology (Caltech). His industrial experience includes corporate research at Fraser Research Lab in Princeton and Qualcomm R&D in San Diego. His research interests are in networks, inference in large data analytics, internet of things, smart grid, and optimization theory and its applications. Dr. Tan was the recipient of the 2008 Princeton University Wu Prize for Excellence and a 2011 IEEE Communications Society Asia-Pacific Young Researcher Award. He was a selected participant at the US National Academy of Engineering 2013 China-America Frontiers of Engineering Symposium. He currently serves as the Chair of the IEEE Information Theory Society Hong Kong Chapter and as an Editor of the IEEE Transactions on Communications. |
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Sensor Networking and Decentralized Signal Processing for Energy Management
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Lecturer: Anna Scaglione IEEE Fellow Professor Electrical and Computer Engineering University of California at Davis |
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Abstract: Part 1: The lecture will be divided in two parts. In the first part of the lecture, we will provide some basic technical knowledge on decentralized signal processing primitives, from consensus, to optimization via network diffusion to the alternating direction method of multipliers, to bio inspired protocols for scheduling and synchronization. Part 2: In the second part of the talk we will look at the benefits that IoT can bring into energy management, and the challenges that lie ahead in fully harnessing the flexibility of electric appliance consumption. We will start from an historical perspective on the traditional Sensory Control and Data Acquisition model used in managing wide area power systems to the present architectures for Advanced Metering Infrastructures to the future of Home Control and Management and Electric Vehicle charging, that challenge the traditional centralize management of energy. In each of these applications we will discuss how decentralized signal processing could be applied to easily interconnect and operate harmoniously many subsystems. |
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Lecturer's short biography: Prof. Anna Scaglione (M.Sc.'95, Ph.D. '99) is currently Professor in Electrical and Computer Engineering at University of California at Davis. She joined UC Davis in 2008, after leaving Cornell University, Ithaca, NY, where she started as Assistant Professor in 2001 and became Associate Professor in 2006; prior to joining Cornell she was Assistant Professor in the year 2000-2001, at the University of New Mexico. She is a Fellow of the IEEE since 2011 and was honored by both the Signal Processing and the Communication Societies. She is the Editor in Chief of the IEEE Signal Processing Letters, and served as Associate Editor for the IEEE Transactions on Wireless Communications from 2002 to 2005, and from 2008 to 2011 in the Editorial Board of the IEEE Transactions on Signal Processing from 2008, where she was Area Editor in 2010-11. She has been general chair of the workshop SPAWC 2005 in the Signal Processing for Communication Committee from 2004 to 2009 and is in the steering committee for the conference Smartgridcomm since 2010 and is currently in the Board of Governors of the SIgnal Processing Society. Dr. Scaglione is the first author of the paper that received the 2000 IEEE Signal Processing Transactions Best Paper Award; she has also received the NSF Career Award in 2002 and she is co-recipient of the Ellersick Best Paper Award (MILCOM 2005) and of the 2013 IEEE Donald G. Fink Prize Paper Award. Her expertise is in the broad area of signal processing for communication systems and networks. Her current research focuses on studying and enabling decentralized learning and signal processing in networks of sensors. She also focuses on sensor systems and networking models for the demand side management and reliable energy delivery. |
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Distributed Video Signal Processing for Internet-of-Things
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Lecturer: Yen-Kuang Chen IEEE Fellow Associate Director, Intel-NTU Connected Context Computing Center Adjunct Professor, Department of Electrical Engineering, National Taiwan University Prinipal Research Scientist, Intel Corporation |
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Lecturer: Shao-Yi Chien Professor Vice Chairperson, Department of Electrical Engineering, National Taiwan University |
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Abstract: Distributed video cameras will play important roles in various IoT/M2M applications, as video/image cameras can provide rich amount of information. However, there are three challenges. (1) Installation of video camera take a lot of efforts, in particular, it has to be connected to line-power and the network. This is because video sensors cannot transmit its content wirelessly and be low-power enough that we don't need provide extra wires to the camera. (2) Many people are annoyed by the fact that video sensors invade their personal privacies. This is because human readable images are captured, transmitted, and stored. (3) Today, in many system, more video contents are captured than human can possibility handle. This is because many irrelevant video contests are captured. To resolve the problems of high data rate, high power consumption, and large deployment cost of large-scale distributed video sensors, perpetual video cameras, where net energy consumption is almost zero, are required. Many technologies and design challenges are introduced for designing such cameras, such as energy harvesting, distributed video coding, distributed video analysis, and the associated VLSI designs. To bring up these issues and challenges, in this lecture, we will provide (1) an overview of challenges/opportunities in IoT, (2) an introduction to the role and requirements of distributed smart cameras in IoT, (3) the analysis of power consumption of wireless video cameras, (4) an introduction of energy harvesting techniques, and (5) distributed video coding and distributed video analysis, where both the state-of-the-art works and possible future research directions will be shown. |
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Lecturer's short biography: Dr. Yen-Kuang Chen is a Principal Engineer at Intel Corporation, and Associate Director of Intel-NTU Connected Context Computing Center. His research areas span from emerging multimedia applications that can utilize the true potential of internet of things to computer architecture that can embrace emerging applications. He has 40+ US patents, 20+ pending patent applications, and 85+ technical publications. He is one of the key contributors to Supplemental Streaming SIMD Extension 3 and Advanced Vector Extension in Intel microprocessors. He has served as a program committee member of 50+ international conferences on Internet of Things, multimedia, video communication, image processing, VLSI circuits and systems, parallel processing, and software optimization. He is a steering committee member of IEEE Internet of Things Journal, the chair of Internet of Things special interest group of IEEE Signal Processing Society, the Deputy Editor-in-Chief of IEEE Journal on Emerging and Selected Topics in Circuits and Systems. He received his Ph.D. degree from Princeton University and is an IEEE Fellow. Prof. Shao-Yi Chien is the Vice Chairperson in the Department of Electrical Engineering, National Taiwan University (NTU). He received the B.S. and Ph.D. degrees from the Department of Electrical Engineering, National Taiwan University (NTU), Taipei, Taiwan, in 1999 and 2003, respectively. During 2003 to 2004, he was a research staff in Quanta Research Institute, Tao Yuan County, Taiwan. In 2004, he joined the Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, as an Assistant Professor. Since 2012, he has been a Professor. His research interests include distributed video sensing, intelligent video coding technology, perceptual coding technology, image processing for digital still cameras and display devices, computer graphics, and the associated VLSI and processor architectures. He has published more than 200 papers in these areas. Dr. Chien serves as an Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Circuits and Systems I: Regular Papers, and Springer Circuits, Systems and Signal Processing (CSSP). He also served as a Guest Editor for Springer Journal of Signal Processing Systems in 2008. He also serves on the technical program committees of several conferences, such as ISCAS, ICME, SiPS, A-SSCC, and VLSI-DAT. He is the TPC chair of iThings2014/CPSCom2014/GreenCom2014. |
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