SmartCity 2018 - Keynotes
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Keynote Speakers

Keynote Speech:
Provisioning and Resource Management for the Internet of Things

Prof. Albert Y. Zomaya
University of Sydney


ABSTRACT: Recent technological trends such as Industry 4.0 introduced new challenges that push the limit of current computer and networking architectures. It demands the connection of thousands, if not millions, of sensors and mobile devices coupled with optimized operations to automate various operations inside factories. This led to the new era of Internet of Things (IoTs) where lightweight (possibly mobile) devices are envisaged to send vital information to cloud data centres (mobile and fixed infrastructure) for further processing and decision making.

Current cloud computing systems, however, are not able to efficiently digest and process collected information from IoT devices with strict response requests for two main reasons: (1) the round trip delay between IoT devices to the processing engines of cloud could exceed an application’s threshold, and (2) network links to cloud resources could be clogged when IoT devices flush data in an uncoordinated fashion. Fog and Edge Computing are two solutions to address both of the previous problems. Though designed to alleviate the same problem, they have fundamental differences that make adopting one more applicable than the other.

This talk will overview the practical concerns of today’s IoT implementations through tackling the most important obstacles that hinder their adoption. First, production of applicable network (fixed and mobile) latency models to capture all elements of IoT platforms. Second, building a holistic platform to orchestrate various inter-related layers of IoT platforms, including connectivity, big-data analytics, and workload optimization. Third, proposing viable solutions that can be actually implemented in IoT-based applications. More details will be provided about the above issues during the talk.

BIO: Albert Y. Zomaya is the Chair Professor of High Performance Computing & Networking and Australian Research Council Professorial Fellow in the School of Information Technologies, Sydney University. He is also the Director of the Centre for Distributed and High Performance Computing which was established in late 2009.

Dr. Zomaya published more than 500 scientific papers and articles and is author, co-author or editor of more than 20 books. He served as the Editor in Chief of the IEEE Transactions on Computers (2011-2014) and was elected recently as a Founding Editor in Chief for the newly established IEEE Transactions on Sustainable Computing. Also, Dr. Zomaya serves as a Co-Founding Editor-in-Chief of IET Cyber-Physical Systems, Founding Editor-in-Chief of the Journal of Scalable Computing and Communications (Springer), and Associate Editor-in-Chief (Special Issues) of the Journal of Parallel and Distributed Computing. He also serves as an associate editor for 22 leading journals, such as, the ACM Computing Surveys, ACM Transactions on Internet Technology, IEEE Transactions on Cloud Computing, and IEEE Transactions on Computational Social Systems. Dr. Zomaya is the Founding Editor of several book series, such as, the Wiley Book Series on Parallel and Distributed Computing, Springer Scalable Computing and Communications, and IET Book Series on Big Data. Dr. Zomaya has delivered more than 160 keynote addresses, invited seminars, and media briefings and has been actively involved, in a variety of capacities, in the organization of more than 700 conferences. Dr. Zomaya is the recipient of the IEEE Technical Committee on Parallel Processing Outstanding Service Award (2011), the IEEE Technical Committee on Scalable Computing Medal for Excellence in Scalable Computing (2011), and the IEEE Computer Society Technical Achievement Award (2014). He is a Chartered Engineer, a Fellow of AAAS, IEEE, and IET. Dr. Zomaya’s research interests are in the areas of parallel and distributed computing and complex systems.

Keynote Speech:
Energy Packet Networks - Challenges in Energy and QoS

Prof. Erol Gelenbe
Imperial College London


ABSTRACT: Various sources point to annual electrical energy consumption by ICT of roughly 1500 TWH per year worldwide, similar to the total electricity consumption of Japan plus Germany, or 8% of the total electricity consumption in the world. In the UK, it is estimated that the new £20 Billion nuclear generators at Hinckley point will not suffice to cover the UK's electricity needs for ICT. Although the potential for reducing energy consumption in other areas of the economy through judicious use of ICT, but ICT's increasing consumption of electricity may at some point raise questions of social acceptability and cost. Thus our presentation will dwell on three approaches drawn from our recent work, to reduce or mitigate this growth. The first approach is to balance Quality of Service against energy consumption. The second approach is to use Energy Packet Networks to dynamically manage energy flows among different components of a complex computer system that includes sensors or actuators, servers, and diverse sources of stored and renewable energies, so as to optimise QoS and the energy used. The third approach is to save energy by encoding information with small numbers of physical particles to represent large amounts of data.

BIO: Erol Gelenbe is the Dennis Gabor Professor of Electrical and Electronic Engineering at Imperial College London. Gelenbe invented trailblazing mathematical models including the G(Gelenbe)-Network that allows the performance evaluation and analysis of computer systems and networks, and the Random Neural Network (RNN) model. Gelenbe's fundamental contributions in these areas have also been instrumental in allowing networks to operate seamlessly without overloading. Along with colleagues, he is also credited with inventing an early computer architecture that allowed voice and images to travel over multi-hop and multi-path computer and communications networks. Gelenbe's current research interests include Software Defined Networks (SDNs), energy savings in information and computing technology (ICT), security in networks, and reinforcement and deep learning within neural networks. Gelenbe is a Fellow of ACM, IEEE and the Institution of Engineering and Technology (IET) UK. He was also elected a Fellow of the National Academy of Technologies of France, and the Science Academies of Belgium, Hungary, Poland and Turkey. In 2017, he received the Mustafa Prize, a biennial science and technology award which aims to rival the Nobel prizes, that is bestowed by the Mustafa Foundation of Iran. He is also a recipient of the 2008 ACM SIGMETRICS Achievement Award, given annually to an individual who has made long-lasting influential contributions to the analysis and evaluation of computer and communication system performance, and several other awards, including the Grand Prix France Telecom 1996 of the French Academy of Sciences.

Keynote Speech:
Seeking Transformative Processor Paradigms for the Post-Moore’s Law Era

Professor Tarek El-Ghazawi
The George Washington University


ABSTRACT: Due to the end of the Moore’s law in clocking and Dennard’s scaling, we are reaching very crippling limits with our current von Neumann processor paradigms. All the help is sought from both technology and architectures to innovate and engender new processing paradigms that can overcome those limitations and define the future of computing. New ideas and directions ranged from neuromorphic processors, to analog, mersisters, quantum and the use of nano photonics. This talk will examine a number of these emerging directions and work by the community including ours and evaluate some of the associated implications for the future of computing.

BIO: Tarek El-Ghazawi is a Professor in the Department of Electrical and Computer Engineering at The George Washington University, where he leads the university-wide Strategic Academic Program in High-Performance Computing. He is a founding director of The GW Institute for Massively Parallel Applications and Computing Technologies (IMPACT) and the NSF Industry/University Center for High-Performance Reconfigurable Computing (CHREC). El-Ghazawi’s research interests include high-performance computing, computer architectures, and heterogeneous computing. He is one of the principal co-authors of the UPC parallel programming language and the first author of the UPC Texbook. El-Ghazawi has published close to 300 refereed research publications in this area. Dr. El-Ghazawi has served in many editorial roles including an Associate Editor for the IEEE Transactions on Computers and Transactions on Parallel and Distributed Systems. He has chaired and co-chaired many international conferences and symposia. Dr. El-Ghazawi’s research has been frequently supported by Federal agencies and industry including DARPA/DoD, NSF, DoE/LBNL, AFRL, NASA, IBM, HP, Intel, AMD, SGI, and Microsoft. Professor El-Ghazawi is a Fellow of the IEEE and was selected Research Faculty Fellow of the IBM Center for Advanced Studies, Toronto. Professor El-Ghazawi was also awarded the Alexander von Humboldt Research Award, and was selected as IEEE Computer Society Distinguished Visor speaker. He was a recipient of the 2012 Alexander Schwarzkopf Prize for Technical Innovation, and served as a Senior Fulbright Scholar.

Keynote Speech:
Measuring the Robustness of Computing Systems

Professor H. J. Siegel
Colorado State University


ABSTRACT: Throughout all fields of science and engineering, it is important that resources are allocated so that systems are robust against uncertainty. The robustness analysis approach presented here can be adapted to a variety of computing and communication environments.

What does it mean for a system to be “robust”? How can the performance of a system be robust against uncertainty? How can robustness be described? How does one determine if a claim of robustness is true? How can one measure robustness to decide which of two systems is more robust?

We explore these general questions in the context of parallel and distributed computing systems. Such computing systems are often heterogeneous mixtures of machines, used to execute collections of tasks with diverse computational requirements. A critical research problem is how to allocate heterogeneous resources to tasks to optimize some performance objective. However, systems frequently have degraded performance due to uncertainties, such as inaccurate estimates of actual workload parameters. To reduce this degradation, we present a model for deriving the robustness of a resource allocation. The robustness of a resource allocation is quantified as the probability that a user-specified level of system performance can be met. We show how to use historical data to build a probabilistic model to evaluate the robustness of resource assignments and to design resource management techniques that produce robust allocations.

BIO: H. J. Siegel is a Professor Emeritus and Senior Research Scientist/Scholar at Colorado State University (CSU). From 2001 to 2017, he was the George T. Abell Endowed Chair Distinguished Professor of Electrical and Computer Engineering at CSU, where he was also a Professor of Computer Science. He was a professor at Purdue University from 1976 to 2001. He received two B.S. degrees from the Massachusetts Institute of Technology (MIT), and the M.A., M.S.E., and Ph.D. degrees from Princeton University. He is a Fellow of the IEEE and a Fellow of the ACM. Prof. Siegel has co-authored over 450 published technical papers in the areas of parallel and distributed computing and communications, which have been cited over 17,700 times. He was a Coeditor-in-Chief of the Journal of Parallel and Distributed Computing, and was on the Editorial Boards of the IEEE Transactions on Parallel and Distributed Systems and the IEEE Transactions on Computers. For more information, please see

Keynote Speech:
Performance and Cost Optimization for Elastic Cloud Computing Platforms

Professor Keqin Li
State University of New York


ABSTRACT: Elasticity is a fundamental feature of cloud computing and can be considered as a great advantage and a key benefit of cloud computing. There are two types of elastic and scalable multiserver management, i.e., scale-up and scale-down elastic server management (i.e., workload dependent dynamic multiserver speed management, or auto speed scaling), and scale-out and scale-in elastic server management (i.e., workload dependent dynamic multiserver size management, or auto size scaling). The two types of cloud resource scaling in an elastic cloud computing system are also called vertical scalability and horizontal scalability. We formally define auto speed scaling schemes and auto size scaling schemes. We develop analytical models to study vertical elasticity and horizontal elasticity by treating a cloud computing platform as a queueing system. We use continuous-time Markov chain (CTMC) models to precisely calculate the performance (i.e., the average response time) and cost (i.e., the average power consumption and the average number of virtual machines) of a cloud platform. We demonstrate the superiority of an elastic cloud computing system over an inelastic cloud computing system in terms of higher quality of service and lower cost of service. We investigate auto scaling scheme optimization, i.e., performance optimization with cost constraint and cost optimization with performance constraint. We discuss optimal load distribution on heterogeneous elastic cloud servers to minimize the average task response time, or to minimize the average power consumption, or to minimize the average cost-performance ratio. We also discuss optimal load distribution and optimal speed setting on heterogeneous elastic cloud servers for power constrained performance optimization and performance constrained power optimization.

BIO: Dr. Keqin Li is a SUNY Distinguished Professor of computer science in the State University of New York. He is also a Distinguished Professor of Chinese National Recruitment Program of Global Experts (1000 Plan) at Hunan University, China. He was an Intellectual Ventures endowed visiting chair professor at the National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China, during 2011-2014. His current research interests include parallel computing and high-performance computing, distributed computing, energy-efficient computing and communication, heterogeneous computing systems, cloud computing, big data computing, CPU-GPU hybrid and cooperative computing, multicore computing, storage and file systems, wireless communication networks, sensor networks, peer-to-peer file sharing systems, mobile computing, service computing, Internet of things and cyber-physical systems. He has published over 550 journal articles, book chapters, and refereed conference papers, and has received several best paper awards. He is currently serving or has served on the editorial boards of IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Computers, IEEE Transactions on Cloud Computing, IEEE Transactions on Services Computing, and IEEE Transactions on Sustainable Computing. He is an IEEE Fellow.



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