This event is endorsed
and organized by

10th EAI International Conference on Mobile Multimedia Communications

July 13–14, 2017 | Chongqing, People's Republic of China

Distinguished Talks

Listed in alphabetical order

Distinguished Talk 1

Wei Chen

Tsinghua University

User Request Prediction Increases Energy Efficiency of Wireless Communications


Proactively pushing content to users has emerged as a promising way of coping with the explosively growing traffic demand of next-generation mobile networks. However, it is still unclear whether content pushing can substantially improve the energy efficiency (EE) of delay-constrained communications over wireless channels. In this talk, we shall demonstrate from an information theoretic perspective the energy efficiency gain due to user request prediction, which enables proactive pushing in wireless communications. An information-theoretic model, along with its optimal pushing policies and various EE bounds will be presented in this talk. We shall also show that the EE can be significantly improved as the content request probability increases.


Wei Chen (S'05-M'07-SM'13) received his BS and Ph.D. degrees (both with the highest honors) from Tsinghua University in 2002 and 2007. From 2005 until 2007, he was also a visiting PhD student at the Hong Kong University of Science \& Technology. Since 2007, he has been on the faculty at Tsinghua University, where he is a tenured full Professor, the director of Academic Degree Office of Tsinghua University, and a member of the University Council. During 2014 to 2016, he served as deputy head of Department of Electronic Engineering. He has also held visiting appointments at several universities, including most recently at Princeton. His research interests are in the areas of wireless networks and information theory.

Dr. Chen is a member of the National 10000-Talent Program, a Cheung Kong Young Scholar, and a Chief Scientist of the National 973 Youth Project. He is also supported by the NSFC Excellent Young Investigator Project, the New Century Talent Program of Ministry of Education, and the Beijing Nova Program. He received the first prize of 14th Henry Fok Ying-Tung Young Faculty Award, the 17th Yi-Sheng Mao Science & Technology Award for Beijing Youth, the 2017 Young Scientist Award of the China Institute of Communications, and the 2015 Information Theory New Star Award of the China Institute of Electronics. He received the IEEE Marconi Prize Paper Award and the IEEE Comsoc Asia Pacific Board Best Young Researcher Award in 2009 and 2011, espectively. He is a winner of the National May 1st Medal and Beijing Youth May 4th Medal. He serves as an Editor of the IEEE TRANSACTIONS COMMUNICATIONS and the IEEE TRANSACTIONS ON EDUCATION. He also serves as the Executive Chairman of the Youth Forum of the China Institute of Communications.

Distinguished Talk 2

Shiwen Mao

Auburn University

On CSI based Vital Sign Monitoring in Healthcare IoT


Vital signs, such as breathing and heartbeat, are useful to health monitoring since such signals provide important clues of medical conditions. Effective solutions are needed to provide contact-free, easy deployment, low-cost, and long-term vital sign monitoring. Exploiting wireless signals for contact-free vital sign monitoring will be an important part of the future healthcare Internet of Things (IoT). In this talk, we present our recent work on contact-free vital sign monitoring. The first part is to exploit channel state information (CSI) phase difference data to monitor breathing and heartbeat with commodity WiFi devices. We will present PhaseBeat, a discrete wavelet transform based design, and TensorBeat, a tensor decomposition based design, as well as our experimental study to validate their performance. The second part of this talk is to exploit a 20KHz ultrasound signal for breathing rate detection. We will present our smartphone App based implementation. Our experimental study shows that the proposed systems can achieve high accuracy under different environments for vital sign monitoring.


Shiwen Mao received his Ph.D. in electrical and computer engineering from Polytechnic University (now NYU Tandon School of Engineering), Brooklyn, NY in 2004. He is the Samuel Ginn Distinguished Professor and Director of the Wireless Engineering Research and Education Center (WEREC) at Auburn University, Auburn, AL. His research interests include wireless networks and multimedia communications. He is a Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS) for 2014-2018. He is on the Editorial Board of IEEE Transactions on Multimedia, IEEE Internet of Things Journal, IEEE Multimedia, ACM GetMobile, Elsevier Digital Communications and Networks, among others, and the Steering Committee of IEEE Transactions on Multimedia and IEEE Transactions on Network Science and Engineering. He is a TPC/Symposium Co-Chair of IEEE INFOCOM 2018, IEEE ICC 2017, IEEE WCNC 2017, among others. He received the 2015 IEEE ComSoc TC-CSR Distinguished Service Award, the 2013 IEEE ComSoc MMTC Outstanding Leadership Award, and the NSF CAREER Award in 2010. He is a co-recipient of the Best Paper Awards from IEEE GLOBECOM 2016 & 2015, IEEE WCNC 2015, and IEEE ICC 2013, and the 2004 IEEE Communications Society Leonard G. Abraham Prize in the Field of Communications Systems.

Distinguished Talk 3

Jian Ren

Michigan State University

Privacy Characterization and Utility Trade-offs in Data Publishing


The increasing interest in collecting and publishing large amounts of data for medical research, market analysis and economical measures has created major privacy concerns. However, data privacy and its usefulness are two conflicting issues. Increase privacy protection will decrease data utility. To characterize this trade off, in this talk, we first present a novel multi-variable privacy characterization and quantification model. Based on this model, we are able to analyze the prior and posterior adversarial belief, and sensitivity of any attribute in privacy characterization. Then we discussed optimal privacy data process under the constraints of data utility. The principles introduced in this research can be applied in many scenarios to address the privacy-utility trade offs.


Jian Ren received his B.S. degree and M.S. degree from Shaanxi Normal University, China. He received the Ph.D. degree from the Xidian University, China. Currently, he is an Associate Professor in the Department of Electrical and Computer Engineering at Michigan State University, East Lansing, MI. Prior to joining MSU, Dr. Ren was the Leading Secure Architect at Avaya Lab, Bell Lab and Racal Datacom in security architecture and solution development.

His most recent research interests include network security, cost-aware security protocol design, privacy-preserving communications, cloud computing, optimal distributed storage and smart home/grid. His group recently developed a hardware secure access gateway to enable remote managing and monitoring of ZigBee enabled devices using a mobile phone, protected through one-time login and one-time password based secure access control. Dr. Ren has been the principle investigator of eight NSF funded projects, including the US National Science Foundation Faculty Early Career Development (CAREER) award in 2009. He is a senior member of the IEEE. He served as the TPC China for ICNC 2017, TPC co-chairs for IEEE Trustcom 2014 and Chinacom 2011. He is serving as the General Chair for IEEE ICNC 2018.

Distinguished Talk 4

Yonggang Wen

Nanyang Technological University

Performance Optimization for Distributed Machine-Learning Applications at Scale: A Swiss-Army-Knife Approach


Distributed machine-learning (ML) applications play an important role in fueling the emerging artificial intelligence revolution. In this context, the parameter server (PS) framework is widely used to train models at scale in modern ML systems, such as Petuum, MxNet, TensorFlow and Factorbird. It tackles the big-data problem by having worker nodes perform data-parallel computation, and having server nodes maintain globally shared parameters. However, when training models of large size, worker nodes frequently pull parameters from server nodes and push updates to server nodes, often resulting in high communication overhead. Our investigations show that modern distributed ML applications could spend up to 5 times more time on communication than computation. To address this problem, we propose an optimized communication layer for the PS framework, called as Parameter Flow (PF). The PS employs a Swiss-army-knife approach by staking three complementary techniques. First, we introduce an update-centric communication (UCC) model to exchange data between worker/server nodes via two operations: broadcast and push. Second, we develop a dynamic value-bounded filter (DVF) to reduce network traffic by selectively dropping updates before transmission. Third, we design a tree-based streaming broadcasting (TSB) system to efficiently broadcast aggregated updates among worker nodes. Our proposed PF can significantly reduce network traffic and communication time. Extensive performance evaluations have showed that PF can speed up popular distributed ML applications by a factor of up to 4.3 in a dedicated cluster, and up to 8.2 in a shared cluster, compared to a generic PS system without PF. The PF framework has been used by a few industry partners.


Dr. Yonggang Wen is an associate professor with School of Computer Science and Engineering (SCSE) at Nanyang Technological University (NTU), Singapore. He is also the Assistant Chair for Innovation at SCSE and the founding director of SCSE Innovation Lab at NTU. He received his PhD degree in Electrical Engineering and Computer Science (minor in Western Literature) from Massachusetts Institute of Technology (MIT), Cambridge, USA, in 2008. Previously he has worked in Cisco to lead product development in content delivery network, which had a revenue impact of 3 Billion US dollars globally. Dr. Wen has published over 170 papers in top journals and prestigious conferences. His systems research has gained global recognitions. His work in Multi-Screen Cloud Social TV has been featured by global media (more than 1600 news articles from over 29 countries) and received ASEAN ICT Award 2013 (Gold Medal). His work on Cloud3DView for Data Centre Life-Cycle Management, as the only academia entry, has won the 2015 Data Centre Dynamics Awards – APAC (the ‘Oscar’ award of data centre industry) and 2016 ASEAN ICT Awards (Gold Medal). He is the winner of 2017 Nanyang Award for Innovation and Entrepreneurship, the highest recognition at NTU. He is a co-recipient of Best Paper Awards at 2016 IEEE Globecom, 2016 IEEE Infocom MuSIC Workshop, 2015 EAI Chinacom, 2014 IEEE WCSP, 2013 IEEE Globecom and 2012 IEEE EUC, and a co-recipient of 2015 IEEE Multimedia Best Paper Award. He serves on editorial boards for IEEE Communications Survey & Tutorials, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Wireless Communication, IEEE Transactions on Signal and Information Processing over Networks, IEEE Access Journal and Elsevier Ad Hoc Networks, and was elected as the Chair for IEEE ComSoc Multimedia Communication Technical Committee (2014-2016). His research interests include cloud computing, green data center, big data analytics, multimedia network and mobile computing.

Distinguished Talk 5

Jun Wu

Tongji University

Wireless image/video transmission with support of big data


The tradition radio access network is built on the specific hardware platform, now is evolving towards cloud computing platform. With the new cloud radio access network (C-RAN) architecture, the communication and computation is converging, which facilitates the Base Station (BS) to utilize big data to assist data communication. The image communication is very popular with wide use of cloud storage and wechat, which produces big data traffics. The emergence of visual big data is a double edged sword to mobile communications. It puts forward a huge challenge to the wireless networks, while its abundant information provides potential to improve the spectrum efficiency significantly. We propose a novel data assisted communication of mobile image (DAC-Mobi) scheme, which utilizes a large amount of correlated (similar) images stored in the cloud to improve the spectrum efficiency and visual quality. The Simulations show that the proposed scheme outperforms conventional digital schemes about 4 dB in peak signal to noise power ratio (PSNR) and achieves 2 dB gain over the state-of-the-art uncoded transmission. At low signal to noise power ratio (SNR), an additional 2-3dB gain is achieved.


Jun Wu received his B.S. degree and M.S in Information Engineering from XIDIAN University in 1993 and 1996, respectively. He received his Ph.D. degrees in Information Engineering from Beijing University of Posts and Telecomm. in 1999. Wu joined Tongji University as a Professor in Dec. 2010. He has been a principal scientist in Huawei from 2009 to 2010, and also a principal scientist in Broadcom Inc. from 2006 to 2009. His research interests include information theory, wireless communication, and digital signal processing. He has authored or co-authored over 100 papers, two chapters of a book, and filed 23 patents (8 patents are granted in USA).

Wu is currently an IEEE senior member, ACM member, senior member of Chinese Institute of Electronics (CIE). He is serving as an Associate Editor of IEEE Transactions on Multimedia (TMM), Associate Editor of IEEE Wireless Communications Letters (WCL) and editor of Wireless Communication and Mobile Computing (WCMC). He served as IEEE GlobeCom 2016 Symposium Chair of Communications Software, Services and Multimedia Apps, Chinacom 2015 TPC Co-chair, IEEE ICCC 2014 Wireless Networking and Multimedia Symposium Co-chair.

Distinguished Talk 6

Zheng Yan

Aalto University

Unwanted Traffic Control based on Trust Management


Networks such as the Internet, mobile cellular networks and self-organized ad hoc networks have dramatically changed our daily life and brought tremendous benefits to us. However, they are also bogged down by unwanted traffic, which is malicious, harmful or unexpected. Literature still lacks an effective, generic and practical solution to control the unwanted traffic over the networks, especially the mobile Internet. In this talk, I will introduce a generic scheme for unwanted traffic detection and control based on trust management. It can control unwanted traffic from its source to destinations in a personalized manner according to trust evaluation at a Global Trust Operator, traffic and behavior analysis at hosts and traffic observation at network service providers. The proposed scheme can conduct unwanted traffic detection and control by integrating distributed and centralized functions and supporting both defensive and offensive approaches of unwanted traffic control. We successfully applied the scheme to control SMS spam and unwanted contents in pervasive social networking and implemented it under the infrastructure of Software Defined Networking (SDN). System implementation and evaluation showed that the scheme is effective with regard to accuracy and efficiency. It is also robust against a number of internal misleading system attacks, such as hide evidence attack, bad mouthing attack, and on-off attack, playing in conjunction with traffic intrusions. Meanwhile, the scheme can provide personalized unwanted traffic control based on unwanted traffic detection behaviors. In particular, we also analyzed its deployment condition with Game Theory and proposed a compensation and punishment mechanism to motivate its practical adoption. Finally, I will introduce how to realize privacy-preserving unwanted traffic control based on trust management.


Zheng Yan is currently a professor at the Xidian University, Xi'an, China and a docent/visiting professor in Aalto University, Finland. She joined the Nokia Research Center, Helsinki in 2000, working as a senior researcher until 2011. She authored more than 150 peer-reviewed publications and solely authored 2 books. She is the inventor of 12 US patents and EU patents, and 41 PCT patent applications. She was invited to offer more than 10 talks or keynotes in international conferences or universities. Her research interests are in trust, security and privacy; mobile applications and services; social networking; cloud computing, pervasive computing, and data mining. Prof. Yan is an associate editor of Information Sciences, Information Fusion, IEEE Access, IEEE IoT Journal, JNCA, Security and Communication Networks, etc., a special issue leading guest editor of more than 20 journals, such as ACM TOMM, IEEE Systems Journal, Future Generation Computer Systems, Computers & Security, IJCS, ACM/Springer MONET, and IET Information Security, etc., and acts as a reviewer for many top journals. She is the organizer of IEEE TrustCom/BigDataSE/ISPA-2015, EAI MobiMedia2016, IEEE CIT2014/2017, CSS2014, ICA3PP2017, NSS2017, etc. She serves as a steering committee or organization committee member for more than 30 conferences and a TPC member for more than 50 conferences, e.g., GlobeCom, ICSOC, ACM MobileHCI, ACM SAC, etc. She is a senior member of the IEEE.

Distinguished Talk 7

Yan Zhang

University of Oslo

Energy Internet for Green Smart Cities


Energy Internet is emerging as a new inter-disciplinary research field. The main goal is to tackle the future global warming, energy crisis and climate change challenges by exploiting state-of-the-art ICT theories and tools to address energy-related problems. In this talk, we will first introduce the key concepts, visions, and joint energy-information architecture in Energy Internet. Then, we present our recent studies on smart energy management, mobile energy networks, and machine learning for energy forecasting for future sustainable smart cities.


Prof. Yan Zhang is Full Professor at the Department of Informatics, University of Oslo, Norway. He received a PhD degree in School of Electrical & Electronics Engineering, Nanyang Technological University, Singapore. He is an Associate Technical Editor of IEEE Communications Magazine, an Editor of IEEE Transactions on Green Communications and Networking, an Editor of IEEE Communications Surveys & Tutorials, an Editor of IEEE Internet of Things Journal, and an Associate Editor of IEEE Access. He serves as chair positions in a number of conferences, including IEEE GLOBECOM 2017, IEEE VTC-Spring 2017, IEEE PIMRC 2016, IEEE CloudCom 2016, IEEE ICCC 2016, IEEE CCNC 2016, IEEE SmartGridComm 2015, and IEEE CloudCom 2015. His current research interests include: next-generation wireless networks leading to 5G, reliable and secure cyber-physical systems.

Distinguished Talk 8

Liang Zhou

Nanjing University of Posts and Telecommunications

Device-to-Device Video Delivery in 5G Communications


As the video traffic has dominated the data flow of smartphones, traditional cellular communication faces substantial challenges. In this work, we study the mobile device-to-device (D2D) video distribution which leverages the storage and communication capacities of the hand-held smartphones. In such a mobile distributed framework, D2D communication is an opportunistic manner which represents an opportunity to selectively store and transmit local videos to meet the future demand of others. The performance is measured by the service time which denotes the elapsed period for fulfilling the demand, and the corresponding implementation of each device depends on the video's demand, availability, and size. The main contents of this talk lie in: 1) Considering the impact of video size in a practical mobile D2D video distribution scenario, and proposing a general global estimation of the video distribution based on the limited and local observations; 2) Designing the detailed implementation of the distributed video distribution scheme, which does not need to know the video availability, user demand, and device mobility; 3) Validating the proposed video distribution scheme in a practical mobile D2D communication environment.


Liang Zhou received his Ph.D. degree, majoring at Electronic Engineering both from Ecole Normale Supérieure (E.N.S.), Cachan, France and Shanghai Jiao Tong University, Shanghai, China in 2009. From 2009 to 2010, he was a postdoctoral researcher in ENSTA-Paris Tech, Paris, France. From 2010 to 2011, he was a Humboldt Research Fellow in Technical University of Munich, Munich, Germany. Now, he is a professor in Nanjing University of Posts and Telecommunication, Nanjing, China.

His research interests are in the area of wireless multimedia communications, in particular, resource allocation, distributed scheduling, and multimedia security. He has published more than 40 journal papers and 20 conference papers in international leading journals and key conferences in the areas of multimedia communications and wireless communications.