The 22nd IEEE International Conference on Parallel and Distributed Systems

December 13-16, 2016

Wuhan, China



Keynote Speakers

Bio.: Beng Chin OOI is a Distinguished Professor of Computer Science at the National University of Singapore (NUS), and an adjunct Chang Jiang Professor at Zhejiang University. He obtained his BSc (1st Class Honors) and PhD from Monash University, Australia, in 1985 and 1989 respectively. His research interests include database, distributed processing, and large scale analytics, in the aspects of system architectures, performance issues, security, accuracy and correctness. Beng Chin has served as Vice PC Chair for ICDE'00,04,06, PC Chair for ACM SIGMOD'07, Core DB PC chair for VLDB'08, and PC co-Chair for IEEE ICDE'12 and IEEE Big Data'15. He is serving as co-PC chair for IEEE ICDE'18.  He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (TKDE)(2009-2012), and co-Editor-in-Chief of Journal of Big Data Research (2013-2015). He is serving as a Trustee Board Member and President of VLDB Endowment, and an Advisory Board Member of ACM SIGMOD. Beng Chin was the recipient of ACM SIGMOD 2009 Contributions award, a co-winner of the 2011 Singapore President's Science Award, the recipient of 2012 IEEE Computer Society Kanai award, 2013 NUS Outstanding Researcher Award, and 2014 IEEE TCDE CSEE Impact Award.  He is a fellow of the ACM, IEEE, and Singapore National Academy of Science(SNAS).


Title: Database Meets Deep Learning: Challenges and Opportunities


Introduction: Deep learning has recently become very popular on account of its incredible success in many complex data driven applications, such as image classification and speech recognition. The database community has worked on data-driven applications for many years, and therefore should be playing a substantial role in supporting this new wave. However, databases and deep learning are different in terms of both techniques and applications. In this talk, I shall discuss research problems at the intersection of the two fields. In particular, I shall discuss possible improvements for deep learning systems from a database perspective, and analyze database applications that may benefit from deep learning techniques. I shall also present Apache SINGA, a distributed deep learning platform, which has built based on our experience in developing  distributed data flow systems.



Bio.: Chen Ding is a Professor of Computer Science at University of Rochester, a research-oriented private university in Rochester, New York.  He received Ph.D. from Rice University, M.S. from Michigan Tech, and B.S. from Peking University.   His research seeks to understand the composite and emergent behavior in computer systems especially its dynamic parallelism and active data usage and develop software techniques for locality optimization, data management, and program parallelization and optimization.  His work received the young investigator awards from NSF and DOE. He co-founded the ACM SIGPLAN Workshop on Memory System Performance and Correctness (MSPC) and was a visiting researcher at Microsoft Research, a visiting associate professor at MIT, a faculty fellow at  IBM Center for Advanced Studies.   More information about his work can be found at http://www.cs.rochester.edu/~cding/.


Title: Theory and Optimization of Multicore Memory Performance


Introduction: The limit of memory speed, size and cost and hence data capacity and communication is a fundamental problem in computer and information science and engineering.  Locality theory is concerned with the universal properties of data usage in applications and memory management in hardware, VM, OS, and other run-time systems.  In this talk, I'll review multiple branches of the past research in different areas that culminate in our higher-order theory of locality (HOTL) showing the mathematical relationship between the locality metrics for performance evaluation, system management, and program optimization.  Based on the new theory, I'll discuss the recent advances in performance analysis and optimization on current mulitcore processors.  This material has been presented internationally including DragonStar lectures at Institute of Computing Technology (ICT) in Beijing and University of Science and Technology of China (USTC), two HPC China conferences, two CCF Advanced Discipline Lectures, a Shonan Meeting in Japan, and  an European Union  graduate summer school (ACACES) in Italy.


kato3Bio.: Professor, Tohoku University, Nei Kato received his Bachelor Degree from Polytechnic University, Japan, in 1986, M.S. and Ph.D. Degrees in information engineering from Tohoku University, in 1988 and 1991 respectively. He joined Computer Center of  Tohoku University as an assistant professor in 1991, and was promoted to full professor position with Graduate School of Information Sciences, Tohoku University, in 2003. He became a Strategic Adviser to the President of Tohoku University in 2013 and the Director of Research Organization of Electrical Communication (ROEC), Tohoku University in 2015. He has been engaged in research on computer networking, wireless mobile communications, satellite communications, ad hoc & sensor & mesh networks, smart grid, and pattern recognition. He has published more than 300 papers in peer-reviewed journals and conference proceedings. He currently serves as a Member-at-Large on the Board of Governors, IEEE Communications Society, the Chair of IEEE Communications Society Sendai Chapter, a Vice Chair of Fellow Committee of IEEE Computer Society(2016),  a member of IEEE Computer Society Award Committee(2015-2016) and IEEE Communications Society Award Committee(2015-2017), the Editor-in-Chief of IEEE Network Magazine(2015.7-), the Associate Editor-in-Chief of IEEE Internet of Things Journal(2013-), an Area Editor of IEEE Transactions on Vehicular Technology(2014-). He has served as the Chair of Satellite and Space Communications Technical Committee(2010-2012) and Ad Hoc & Sensor Networks Technical Committee(2014-2015) of IEEE ComSoc respectively, the Chair of IEICE Satellite Communications Technical Committee(2011-2012). His awards include Minoru Ishida Foundation Research Encouragement Prize(2003), Distinguished Contributions to Satellite Communications Award from the IEEE Communications Society, Satellite and Space Communications Technical Committee(2005), the FUNAI information Science Award(2007), the TELCOM System Technology Award from Foundation for Electrical Communications Diffusion(2008), the IEICE Network System Research Award(2009), the IEICE Satellite Communications Research Award(2011), the KDDI Foundation Excellent Research Award(2012), IEICE Communications Society Distinguished Service Award(2012), IEICE Communications Society Best Paper Award(2012), Distinguished Contributions to Disaster-resilient Networks R&D Award from Ministry of Internal Affairs and Communications, Japan(2014), Outstanding Service and Leadership Recognition Award 2016 from IEEE Communications Society and Best Paper Awards from IEEE ICC/GLOBECOM/WCNC/VTC. Besides his academic activities, he also serves on the expert committee of Telecommunications Council, Ministry of Internal Affairs and Communications, and as the chairperson of ITU-R SG4 and SG7, Japan. Nei Kato is a Distinguished Lecturer of IEEE Communications Society and Vehicular Technology Society. He is a fellow of IEEE and IEICE.


Title: IoT: Towards a Connected Era--- Research Direction and Social Impacts


Introduction: The surge in technology developments and the demand for more efficient devices in the past decades has enabled a new form of network paradigm, the Internet of Things (IoT) that allows connected objects or things to remotely sense or be sensed, control or be controlled, and transmit information over the network. IoT applications can be productive in many ways including saving time and money by providing a more efficient automation of mundane tasks, and improving the quality of life through information gathering, analysis, and feedback. As it integrates our physical world and computer/information systems, IoT is the foundation of the future Information and Communications Technology ecosystem, the networked society. Therefore, due to its immense potential, IoT has attracted a great deal of attention from the industry, the academia, and the government alike. In this talk, first, a brief introduction to the history and background, as well as the current trend of IoT, will be presented. Second, the technologies that lay out the foundation of IoT will be introduced. Finally, future research problems and directions will be identified and discussed.


Bio.: Yunhao Liu, Cheung Kong Professor and Dean of School of Software at Tsinghua University, China. Being an ACM Fellow and an IEEE Fellow, Yunhao serves as the Chair of ACM China Council and also the Associate Editor for IEEE/ACM Transactions on Networking and ACM Transactions on Sensor Network. Yunhao was the Associate Editor-in-Chief for IEEE Transactions on Parallel and Distributed Systems from 2011 through 2014. He served as TPC member for many leading conferences such as ACM MobiCom, IEEE INFOCOM, ACM MobiCom, and PC Co-Chair/Vice Co-Chair for IEEE ICDCS, IEEE MASS, IEEE ICPADS and etc. He was also General Co-Chair for IEEE RTAS 2012, WASA 2010, and Vice General Chair for WWW 2008. Yunhao has published more than 120 papers and received many best paper awards like ACM MobiCom 2014 Best Paper Award, IEEE DCOSS 2011 Best Paper Award, and IEEE ICPADS 2009 Best Paper Award. He also received many prestigious awards including ACM Presidential Award 2012, China National Natural Science Award 2011, and China National Distinguished Young Scholar Award 2011. Yunhao Liu received the BS degree in automation from Tsinghua University, China, in 1995, the MS and PhD degrees in computer science and engineering from Michigan State University, USA, in 2003 and 2004, respectively. He was Assistant Professor and Associate Professor in the Hong Kong University of Science and Technology from 2004-2010, and Joined Tsinghua University as Professor in 2011. His research interests include RFID and sensor network, the Internet and P2P&Cloud Computing.


Title: On Sensorless Sensing for Internet of Everything


Introduction: Yunhao started working on IoT and Sensor Network since early 2000. In the past years, he and his team deployed the world first working sensor network system in the D. L. Coal Mine, the world second largest coal mine, one of the world earliest RFID localization systems called LANDMARC. They implemented the GreenOrbs prototype system in the campus woodland of Zhejiang Forestry University with 330 sensor nodes and each node with several sensors. The system scale reached 400 in April 2010. Later, the Tianmu Mountain deployment includes 200 nodes and was in continuous operation since August 2009 and lasted for more than three years. The deployment area is around 200,000 square meters. From 2011 through 2016, Yunhao and his team conduct TagSys system in the Beijing International Airport and more than 100 thousand RFID tags are used. The resulted publication was awarded MobiCom 2014 Best Paper. In this talk, he is going to share the experience learned from large scale Sensor Network and IoT system deployments, and also discuss the concept Sensorless Sensing they proposed.