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  • Abstract

In the past several years, there are various technologies emerging, which are either directly or indirectly related to communication. Some of them are over the evolution of traditional communication systems, while others are over new systems such as smart grids, molecular networks, and big data systems.

In this special issue, we cover some recent results in the following four emerging areas: 5G cellular systems, big data systems, bio/nano/molecular networks, and smart grids.

Specifically, for 5G, we have included six papers.

The paper 5G-Enabled Tactile Internet presents the most important concepts, which lay at the intersection between the tactile Internet and the emerging 5G systems. The paper outlines the key technical requirements and architectural approaches for the tactile Internet, pertaining to wireless access protocols, radio resource management aspects, next generation core networking capabilities, edge-cloud, and edge-AI capabilities.

The paper New Paradigm of 5G Wireless Internet provides an overview of China Mobile’s 5G vision and potential solutions. The 5G network design considerations are discussed, including cloud radio access network (C-RAN), ultra-dense network (UDN), software defined network (SDN), and network function virtualization (NFV), examined as key potential solutions toward a green, soft, and super fast 5G network.

The paper On Service Resilience in Cloud-Native 5G Mobile Systems introduces a unified framework, along with efficient and proactive restoration mechanisms, to ensure service resilience in carrier cloud. As restoration of a network function failure impacts a potential number of users, adequate network overload control mechanisms are discussed. A mathematical model is developed to evaluate the performance of the proposed mechanisms.

The paper Low-Complexity MIMO Non-Linear Precoding Using Degree-2 Sparse Vector Perturbation investigates the fundamental problem of MU-MIMO scalability tackled through a novel signal-processing approach, which is called degree-2 vector perturbation (D2VP). Unlike the conventional VP approaches that aim at minimizing the transmit-to-receive energy ratio through searching over an N-dimensional Euclidean space, D2VP shares the same target through iterative searching over two optimally selected subspaces. By this means, the computational complexity is managed to be in the cubic order of the size of MU-MIMO networks.

The paper Internet of Things in the 5G Era: Enablers, Architecture and Business Models analyzes in detail the potential of 5G technologies for IoT, by considering both the technological and standardization aspects. The present-day IoT connectivity landscape is reviewed, as well as the main 5G enablers for the IoT. In addition, massive business shifts that a tight link between IoT and 5G may cause in the operator and vendors ecosystem are discussed.

The paper User Mobility Evaluation for 5G Small Cell Networks Based on Individual Mobility Model derives user pause, arrival, and departure probabilities for evaluating the user mobility performance in a hotspot-type 5G small cell network. Furthermore, coverage probabilities of small cell and macro cell BSs are derived for all the users in the 5G small cell networks, respectively.

For big data systems, we have three papers.

The paper Negatively Correlated Search presents a novel and efficient evolutionary algorithm, namely Negatively Correlated Search (NCS), which maintains multiple individual search processes in parallel and models the search behaviors of individual search processes as probability distributions.

The paper Analyzing Enterprise Storage Workloads with Graph Modeling and Clustering presents a novel graph analytics framework, GraphLens, for mining, and analyzing real world storage traces. The evaluation on real storage traces shows that GraphLens can provide broad and deep trace analysis for better storage strategy planning and efficient data placement guidance.

The paper Big Data for Autonomic Intercontinental Overlays shows that intercontinental Internet Protocol (IP) paths are far from optimal with respect to Quality of Service (QoS) metrics such as end-to-end round-trip delay based on the collection of data sampled over a large number of source–destinations pairs. It presents a machine learning-based scheme to exploit large scale datasets collected from communicating node pairs in a multihop overlay network that uses IP between the overlay nodes, and selects paths that provide substantially better QoS than IP.

For bio/nano/molecular networks, we have three papers.

The paper Queuing Models for Abstracting Interactions in Bacterial Communities considers communication models for populations of bacteria, particularly those that communicate via quorum sensing, or via electron exchange. It is shown that models based on queues may be used to describe and analyze this kind of communication, which is important to the study of microbiology and may have applications in medicine or nanotechnology.

The paper Molecular MIMO: From Theory to Prototype discusses the use of multiple transmitters and receivers in nanoscale biological and molecular communications systems. In conventional radio frequency wireless communications, it is well known that using multiple antennas at both ends of the radio link can significantly increase the data capacity of the system. This paper uses detailed modeling techniques to demonstrate that similar performance gains can be attained in molecular communication setups. Detection algorithms for this configuration are also proposed and analyzed. An initial laboratory experimental system is also described to show an initial verification of this principle for a communications system using multiple chemical receivers to detect multiple alcohol sprays.

The paper Analysis of Error Detection Schemes in Diffusion-based Molecular Communication considers physical layer aspects of molecular communication, particularly when ON/OFF keying is used, where molecular communication channels face important complexity constraints, as well as the challenges of the channel physics. Coding schemes (particularly error-detecting schemes) are developed, which explicitly take into account the complexity limitations of biological agents.

For smart grids, we have five papers.

The paper An Online Gradient Algorithm for Optimal Power Flow on Radial Networks proposes an online algorithm to solve the optimal power flow problems on radial networks. An important feature of the proposed gradient projection algorithm is that the intermediate iterates always satisfy power flow equations and operational constraints. It shows that the proposed algorithm converges to the set of local optima and provides sufficient conditions under which it converges to a global optimum.

The paper Joint Optimal Design and Operation of Hybrid Energy Storage Systems studies the problem of jointly optimizing the sizing and the operating strategy of a hybrid energy storage system. The solution provides a Pareto-optimal frontier of the sizes of the underlying storage technologies. The proposed framework is used to analyze two concrete case studies.

The paper Robust Workload and Energy Management for Sustainable Data Centers uses a robust optimization framework to study the problem of integrating renewable energy sources, distributed storage units, cooling facilities, and dynamic pricing into the workload and energy management tasks of a data center network. It aims to minimize the system’s worst-case net cost subject to the operational constraints of data center. Numerical results with real data corroborate the merits of the proposed framework.

The paper Renewables and Storage in Distribution Systems: Centralized vs. Decentralized Integration studies the problem of integrating renewables and storage into a distribution network. Both the centralized integration and decentralized integration models are analyzed using Stackelberg games. The tradeoff between the consumer surplus and retail profit of the utility is investigated.

The paper Assessment of LTE Wireless Access for Monitoring of Energy Distribution in the Smart Grid discusses how the fourth generation long term evolution wireless networks can support data from future smart grid devices including smart meters. In smart grid applications, a very large number of devices in one cell may periodically access the network to send data. The authors show through detailed analysis that conventional protocols that enable devices to access the Internet wirelessly may not cope very well in this scenario, due to the significant increase in the expected number of devices. It shows that a significant redesign of the long term evolution system is required to support future smart grid data traffic efficiently.

It is the editorial team’s objective that these results could motivate more research efforts in these areas.

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Authors

Shuguang Cui

Shuguang Cui

Shuguang Cui (S’99–M’05–SM’12–F’14) received the Ph.D. degree in electrical engineering from Stanford University, Stanford, California, USA, in 2005. He is working as a Professor in Electrical and Computer Engineering with the Texas A&M University, College Station, TX, USA. His research interests include data oriented large-scale information analysis and system design, including large-scale distributed estimation and detection, information theoretical approaches for large data set analysis, complex cyber-physical system design, and cognitive network optimization. He has served as the General Co-Chair and TPC Co-Chairs for many IEEE conferences. He has also been serving as the Area Editor for the IEEE Signal Processing Magazine, and an Associate Editor for the IEEE TRANSACTIONS ON BIG DATA, the IEEE TRANSACTIONS ON SIGNAL PROCESSING, the IEEE JSAC Series on Green Communications and Networking, and the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. He was the elected member for IEEE Signal Processing Society SPCOM Technical Committee (2009–2014) and the elected Vice Chair for the IEEE ComSoc Wireless Technical Committee (2015–2016). He is a member of the Steering Committee for both the IEEE TRANSACTIONS ON BIG DATA and the IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING.

He is also a member of the IEEE ComSoc Emerging Technology Committee. He was the Distinguished Lecturer of the IEEE ComSoc in 2014. He was selected as the Thomson Reuters Highly Cited Researcher and listed in the World’s Most Influential Scientific Minds by ScienceWatch in 2014. He was the recipient of the IEEE Signal Processing Society 2012 Best Paper Award.

John S. Thompson

John S. Thompson

John S. Thompson (S’94–M’03–SM’13–F’16) is currently a Professor in Signal Processing and Communications with the School of Engineering, University of Edinburgh, Edinburgh, U.K. He has authored in excess of 300 papers on these topics, including 100 journal paper publications. He research interests include antenna array processing, co-operative communications systems, and energy efficient wireless communications. He is currently the project co-ordinator for the EU Marie Curie International Training Network project ADVANTAGE, which studies how communications and power engineering can provide future “smart grid” systems). He was an elected Member-at-Large for the Board of Governors of the IEEE Communications Society from 2012–2014, the second largest IEEE Society. He was a Distinguished Lecturer on the topic of energy efficient communications and smart grid for the IEEE Communications Society from 2014–2015. He is an Editor for the Green Communications and Computing Series that appears regularly in the IEEE Communications Magazine.

Tomohiko Taniguchi

Tomohiko Taniguchi

Tomohiko Taniguchi (M’87–SM’90–F’06) received the B.S.E.E. degree from the University of Tokyo, Tokyo, Japan, in 1982, and the Ph.D. degree from the same university, in 2006. From 1987 to 1988, he was a Visiting Scholar at Stanford University, Stanford, CA, USA; from 1996 to 2000, he was with Fujitsu Laboratories of America, Sunnyvale, CA, USA. He is currently with Fujitsu Laboratories Limited, Kawasaki, Japan, as a Research Principal. He has been active in the field of signal processing for more than 30 years and is recognized for his inventions in speech coding and DSP technologies (holds essential patents for international standards, such as ITU-T, MPEG, and 3GPP). He is a Fellow of IEICE. He was the recipient of several awards for his papers, patents, and contributions to academic society (Outstanding Service Award, 2006/2010, Best Symposium Award, 2011/2013, Industrial Distinguished Leader Award, 2014). As an industry expert, he teaches at Beijing University of Posts and Telecommunications (Distinguished Visiting Professor, 2013–2018) and at Duy Tan University (Guest Professor, 2014–2017).

Latif Ladid

Latif Ladid

Latif Ladid (M’10) is the Founder and the President, IPv6 FORUM, the Founding Chair, 5G World Alliance, the Chair, ETSI IPv6 Industry Specification Group, the Chair, IEEE ComSoC IoT subcommittee, Chair, IEEE ComSoC 5G subcommittee, the Vice Chair, the IEEE ComSoC SDN-NFV subcommittee, the Emeritus Trustee, Internet Society—ISOC, IPv6 Ready and Enabled Logos Program Board, World Summit Award Board Member, Research Fellow with the University of Luxembourg, Luxembourg, U.K. on multiple European Commission Next Generation Technologies IST Projects, Member of 3GPP PCG (Board), Member of 3GPP2 PCG, Former Vice Chair, the IEEE ComSoc EntNET, Member of UN Strategy Council, Member of Future Internet Forum EU Member States (representing Luxembourg).

Jie Li

Jie Li

Jie Li (M’96–SM’04) received the B.E. degree in computer science from Zhejiang University, Hangzhou, China, the M.E. degree in electronic engineering and communication systems from China Academy of Posts and Telecommunications, Beijing, China, and the Dr. Eng. degree from the University of Electro-Communications, Tokyo, Japan. He is with Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Japan, where he is a Professor. He has been a Visiting Professor with Yale University, New Haven, CT, USA, Inria France. His research interests include mobile distributed computing and networking, big data and cloud computing, IoT, OS, modeling, and performance evaluation of information systems. He is a senior member of ACM and a member of IPSJ (Information Processing Society of Japan). He is the Chair of Technical Sub-Committee on Big Data (TSCBD), the IEEE Communications Society. He has served as a secretary for Study Group on System Evaluation of IPSJ and on several editorial boards for the international Journals, and on Steering Committees of the SIG of System EVAluation (EVA) of IPSJ, the SIG of DataBase System (DBS) of IPSJ, and the SIG of MoBiLe computing and ubiquitous communications of IPSJ. He has also served on the program committees for several international conferences such as the IEEE INFOCOM, the IEEE GLOBECOM, and the IEEE MASS.

Andrew Eckford

Andrew Eckford

Andrew Eckford (M’96–SM’15) received the B.Eng. degree from the Royal Military College of Canada, Kingston, ON, Canada, in 1996, and the M.A.Sc. and Ph.D. degrees from the University of Toronto, Toronto, ON, Canada, in 1999 and 2004, respectively, all in electrical engineering. He is an Associate Professor with the Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada. He held Postdoctoral Fellowships with the University of Notre Dame, Notre Dame, IN, USA, and the University of Toronto, prior to taking up a faculty position at York in 2006. His research interests include LTE and 5G wireless networks, and the application of information theory to nonconventional channels and systems, especially the use of molecular and biological means to communicate. His research has been covered in media including The Economist and The Wall Street Journal. He is also a coauthor of the textbook Molecular Communication (Cambridge University Press), and was a Finalist for the 2014 Bell Labs Prize.

Vincent W.S. Wong

Vincent W.S. Wong

Vincent W. S. Wong (S’95–M’00–SM’06–F’16) received the B.Sc. degree from the University of Manitoba, Winnipeg, MB, Canada, in 1994, the M.A.Sc. degree from the University of Waterloo, Waterloo, ON, Canada, in 1996, and the Ph.D. degree from the University of British Columbia (UBC), Vancouver, BC, Canada, in 2000. From 2000 to 2001, he worked as a Systems Engineer with PMC-Sierra Inc. He joined the Department of Electrical and Computer Engineering, UBC, in 2002, and is currently a Professor. His research interests include protocol design, optimization, and resource management of communication networks, with applications to wireless networks, smart grid, and the Internet. He is an Editor of the IEEE TRANSACTIONS ON COMMUNICATIONS. He has served on the Editorial Boards of the IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY and Journal of Communications and Networks. He has served as a technical program Co-Chair of the IEEE SmartGridComm’14, as well as a Symposium Co-Chair of the IEEE SmartGridComm’13, and the IEEE Globecom’13. He is the Chair of the EEE Communications Society Emerging Technical Sub-Committee on Smart Grid Communications and the IEEE Vancouver Joint Communications Chapter. He was the recipient of the 2014 UBC Killam Faculty Research Fellowship.

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