Date: Tuesday, 1 September 2015

Time: 10:00 am – 11:30 am

Room: HG17, DCU       


A Hyper Cellular Architecture and its Software-defined Implementation for 5G Mobile Communications


Zhisheng Niu

Electronic Engineering Department, Tsinghua University

Tsinghua National Lab for Information Science and Technology


Abstract: Cellular concept was invented to improve the spectrum efficiency by spectrum reuse and has contributed a lot for the explosive deployment of today’s mobile communication industry.  As mobile data and video traffic is fast growing, the next-generation mobile communication (5G) networks are expected to further provide 10-fold more capacity than 4G mobile networks with the limited spectrum as well as energy resources.  To deal with this challenge, the traditional physical- and MAC-layer capacity-enhancement approaches are no more sufficient and efficient.  A system- or network-level approach is needed, including rethinking about the existing cellular structure.  On the other hand, cellular networks are transforming from just a mobile communication platform to a smart information infrastructure on which more and more always-online type of traffic (e.g., short but frequent signaling packets of various social networks, sensing information of smart earth and smart community, control packets in cooperative heterogeneous wireless networks) need to be handled in an energy-efficient way.  As a result, the existing cellular framework should be revisited.


In this talk, we propose a new cellular framework, named hyper-cellular arcitecture (HCA), aiming at increasing the whole network capacity by more than 10-fold based on the existing limited spectrum and energy resources as well as accommodating ever-increasing always-online traffic in a more energy-efficient way.  The key idea here is to separate the coverage of control signals from the coverage of data signals so that the data coverage can be more elastic in accordance with the dynamics of traffic needs and QoS requirements.  This can be considered as the further extension of the existing C-RAN concept and one of the key candidate technologies for 5G mobile communications systems.  Some preliminary results have shown that this new paradigm has a great potential in the capacity enhancement and energy savings.  Its software-defined implementation through the convergence of virtual BS and edge cloud technologies will also be discussed.



Biography: Zhisheng Niu graduated from Beijing Jiaotong University, China, in 1985, and got his M.E. and D.E. degrees from Toyohashi University of Technology, Japan, in 1989 and 1992, respectively.  In 1992-94 he worked for Fujitsu Laboratories Ltd., Kawasaki, Japan, and joined with Tsinghua University, Beijing, China, in 1994, where he is now a professor at the Department of Electronic Engineering. He is also a guest chair professor of Shandong University, China.  His major research interests include queueing theory, traffic engineering, mobile Internet, radio resource management of wireless networks, and green communication and networks.

Dr. Niu has been an active volunteer for various academic societies, including Director for Conference Publications (2010-11), Director for Asia-Pacific Board (2008-09), and member of the Award Committee of IEEE Communication Society, Membership Development Coordinator (2009-10) of IEEE Region 10, Councilor of IEICE-Japan (2009-11), council member of Chinese Institute of Electronics (2006-11), and an editor of IEEE Wireless Communication Magazine (2009-2013).  He is now a distinguished lecturer (2012-15) and Chair of Emerging Technology Committee (2014-15) of IEEE Communication Society, member of the Fellow Nomination Committee of IEICE Communication Society (2013-14), standing committee member of Chinese Institute of Communications (2012-16), and associate editor-in-chief of IEEE/CIC joint publication “China Communications”.

Dr. Niu received the Outstanding Young Researcher Award from Natural Science Foundation of China in 2009 and the Best Paper Award of IEEE ComSoc Asia-Pacific Board in 2013.  He also co-received the Best Paper Awards (with his colleagues) from the 13th, 15th and 19th Asia-Pacific Conference on Communication (APCC) in 2007, 2009, and 2013, respectively, International Conference on Wireless Communications and Signal Processing (WCSP’13), and  the Best Student Paper Award (with his student) from the 25th International Teletraffic Congress (ITC25), 2013.  He is now the Chief Scientist of the National Basic Research Program (so called “973 Project”) of China on “Fundamental Research on the Energy and Resource Optimized Hyper-Cellular Mobile Communication System” (2012-2016), which is the first national project on green communications in China.  He is a fellow of both IEEE and IEICE


Online Social Network Data Placement over Geo-Distributed Clouds

 Lei Jiao

Researcher with Bell Labs Ireland


Online social networks (or more generally, socially aware services) are online services where users build social relationships and interact with one another. With a large user base, a socially aware service often needs users’ data to be partitioned and replicated across multiple geo-distributed clouds. Choosing at which cloud to place which user’s data, however, is difficult, as an effective data placement must achieve various system objectives while facing critical challenges such as the interconnection of users, the master-slave data replication, the conflicting requirements of different objectives, and the diversity of multi-cloud data access policies.


In this talk, we present our recent work on placing data of socially aware services across geo-distributed clouds. We investigate two problem settings. In the first setting, we optimize the service provider’s monetary expense of using cloud resources, while guaranteeing the service quality and the data availability by ensuring data of interconnected users are always co-located at a common cloud. In the second setting, we optimize system objectives of multiple dimensions simultaneously, e.g., the carbon footprint, the service quality, the inter-cloud traffic, as well as the reconfiguration cost incurred by changing one data placement to another. Both problems are large-scale discrete, combinatorial optimization problems that are hard to solve. Having the model formulations, our core contributions are the algorithms that could solve the two problems: for the first problem, our approach is based on the observation that swapping the roles, either master or slave, of a user’s data replicas at different clouds not only leads to possible cost reduction, but also maintains service quality and data availability; for the second problem, we propose to decompose it into two subproblems of placing master replicas and slave replicas respectively, where we leverage the graph cuts technique to solve the master placement problem, use a greedy method to place the slaves, and solve the two subproblems alternately in multiple rounds. Extensive evaluations with real-world large-scale data traces demonstrate that, compared with the state of the art and de facto methods, our approaches have substantial advantages in saving monetary expense and optimizing multiple objectives. We further analyze and discuss related issues such as complexity, optimality, scalability, and design alternatives, if time permits.


Short bio:

Lei Jiao is a researcher with Bell Labs Ireland. He received his Ph.D. in computer science from University of Göttingen, Germany. Prior to that, he was a researcher with IBM Research China. His recent research interests lie in exploring theories (e.g., optimization, graph theory, control, and game theory) and their application to networking and distributed computing problems. His work has been published in IEEE/ACM Transactions on Networking, IEEE INFOCOM, ICNP, etc. He was also a recipient of the Best Paper Award of IEEE LANMAN 2013.