Modern society has become increasingly reliant on mobile networks for their communication needs. Such networks are characterized by their dynamic, heterogeneous, complex, and data intensive nature, which makes them more amenable to automated optimization performed using "computational intelligence" (CI) techniques rather than manual optimization. CI techniques—which subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have a rich history in terms of being deployed in networking. Looking ahead, greater integration of CI into mobile networking architectures will likely be an essential component of the future of mobile networking, and will play a leading role in the upcoming 5th generation (5G) wireless mobile networks. It is anticipated that future mobile networks will have characteristics of cognitive networks that will show intelligent network-wide behavior to solve problems such as routing, scheduling, traffic, capacity, coverage and heterogeneous network optimization, etc.
Realizing this vision of the future-generation mobile networking environment requires the seamless integration of CI into the frameworks used for mobile network optimization. From the perspective of mobile networking, CI techniques can be used to propose intelligent solutions that optimize problems such as scheduling and routing, traffic, capacity, coverage and power optimization for mobile networks (current 4G and the future 5G systems). In particular, CI techniques will likely play an important role in future 5G wireless networks since the traditional self-organizing network (SON) techniques deployed for 3G and 4G would not suffice for 5G, keeping in view the stringent requirements of exceptionally high data rates and extremely low latency in the future 5G technology. New mechanisms need to developed that can optimize the capital expenditure (CAPEX) and the operating expenditure (OPEX) of future mobile networks—which will be challenging since the stringent performance requirements of future mobile networks such as 5G add to the network complexity, which will likely make the system management more costly.
With the future of mobile networks linked invariably with the wide support for multiple heterogeneous technologies, the problem of heterogeneous network optimization is of paramount importance for the success of mobile networking. It is foreseen that future wireless networks will allow everything to connect with everything—and mobile networks will play an important role in enabling the vision of Internet of Things (IoT). We can use CI techniques in conjunction with techniques such as Network Function Virtualization (NFV) and Software Defined Networking (SDN) to flexibly optimize the performance and operating costs of the future networks. It is anticipated that mobile network optimization performed using CI will leverage the huge amount of network data (or Big Data) that can be harnessed to optimize in real-time the various performance metrics (in particular the network traffic loads) and realize an exclusive SON for future communication technologies (particularly 5G). The heterogeneity and the dynamic nature of the current and future substrate networks, upon which different networks can be instantiated (thanks to NFV, light weight operating systems, and new virtualization technologies such as Docker’s containers), emphasize the need for cooperative communication among different parts of the overall communication network and optimal, real-time, and efficient resource sharing and allocation.
The aim of this special issue is to bring together researchers from the diverse communities of wireless networking, mobile networking, and computational intelligence and seek to curate the state-of-art work in developing CI-based solutions to problems related to mobile network optimization. Papers are solicited on novel concepts, models, methodologies, and designs of CI-enhanced network models, architectures, and protocols for mobile network optimization.
CI-based techniques for mobile network optimization (MNO):
Technical issues related to building CI-based MNO solutions:
Application of CI techniques for various MNO tasks:
Works in particular MNO configurations:
The following schedule will be followed for this special issue:
The maximum length for the manuscripts included in this special issue will be 10 pages in double column, including figures and references. Authors of papers should specify in the first page of their manuscripts the contacts of the corresponding author and up to 5 keywords.
Additional information about submission guidelines and information for authors is provided at the IEEE CIM website.
Submission should be made via Easychair.
JUNAID QADIR, Information Technology University (ITU), Pakistan
Junaid Qadir completed his BS in Electrical Engineering from UET, Lahore, Pakistan and his PhD from University of New South Wales, Australia in 2008. He is currently an Associate Professor at the Information Technology University (ITU)-Punjab, Lahore, Pakistan. He is the Director of the IHSAN Lab at ITU that focuses on deploying ICT for development, and is engaged in systems and networking research. Prior to joining ITU, he was an Assistant Professor at the School of Electrical Engineering and Computer Sciences (SEECS), National University of Sciences and Technology (NUST), Pakistan. At SEECS, he directed the Cognet Lab at SEECS that focused on cognitive networking and the application of computational intelligence techniques in networking. He has been awarded the highest national teaching award in Pakistan—the higher education commission’s (HEC) best university teacher award—for the year 2012-2013. He has been nominated for this award twice (2011, and 2012-2013). His research interests include the application of algorithmic, machine learning, and optimization techniques in networks. In particular, he is interested in the broad areas of wireless networks, cognitive networking, software-defined networks, and cloud computing. He is a regular reviewer for a number of journals and has served in the program committee of a number of international conferences. He serves as an Associate Editor for IEEE Access, IEEE Communication Magazine, and Springer Nature Big Data Analytics. He was the lead guest editor for the special issue “Artificial Intelligence Enabled Networking” in IEEE Access and the feature topic “Wireless Technologies for Development” in IEEE Communications Magazine. He is a member of ACM, and a senior member of IEEE.
AMIR HUSSAIN, University of Stirling
Amir Hussain is an IEEE CIM Associate Editor, and served as the Guest Editor of IEEE CIM Nov 2015 Special Issue. Amir Hussain obtained his BEng (with the highest 1st Class Honours with distinction) and PhD in Electronic and Electrical Engineering (EEE), both from the University of Strathclyde in Glasgow, in 1992 and 1997 respectively. Following a post-doctoral Research Fellowship at the University of Paisley (1996-98) and a Research Lectureship at the University of Dundee (1998-2000), he joined the University of Stirling in 2000, where he is currently full (Chair) Professor of Cognitive Computing Science and founding Director of the Cognitive Big Data Informatics (CogBID – formerly COSIPRA) Laboratory. His research interests are cross-disciplinary & industry focused and include: next generation brain-inspired multi-modal cognitive technology for solving complex real world problems, including medical and social multi-media Big Data analytics, manifold-based learning, dimensionality reduction and visualization, sentiment and opinion mining, multi-lingual natural language processing, personalized and preventative (e and m) healthcare, and medical informatics engineering, agent based complex autonomous systems modeling and control, cognitive multi-modal hearing systems, more natural multi-modal human computer interaction, assistive technology & related clinical research. He has published sixteen Books: 8 edited volumes and 8 research monographs, including: Sentic Computing, Cognitive Agent based Computing, and Cognitively-inspired Audio-visual Speech Filtering (first books in their respective areas); and, nearly 300 research papers (including around 100 in leading international journals). He has conducted and led collaborative research with industry (attracting research grants worth several million dollars, as Principal Investigator); partnered in major European research programs, and has supervised more than 30 PhDs. He is founding Editor-in-Chief of the internationally-leading journal: Cognitive Computation journal, published by Springer Nature (Neuroscience, USA, http://springer.com/12559), the new BMC Big Data Analytics journal (published by BioMed Central/Springer Nature, http://bdataanalytics.com), and the Springer Book Series on Socio-Affective Computing, and SpringerBriefs in Cognitive Computation. He is Associate Editor for the world’s leading IEEE Transactions on Neural Networks & Learning Systems, the IEEE Computational Intelligence Magazine, and serves on the editorial board of a number of other leading journals.
KOK-LIM ALVIN YAU, Sunway University
Kok-Lim Alvin Yau received the B.Eng. degree in Electrical and Electronics (Honors) from the Universiti Teknologi Petronas, Malaysia, the M.Sc. (Electrical Engineering) from the National University of Singapore, and the Ph.D. (Network Engineering) from Victoria University of Wellington, New Zealand in 2005, 2007 and 2010, respectively. He was awarded the 2014 Sunway University Award for Excellence in Teaching, and 2007 Professional Engineer Board of Singapore Gold Medal for being the best graduate of the M.Sc. degree in 2006/07. He is currently an Associate Professor with the Department of Computer Science and Networked Systems, Faculty of Science and Technology, Sunway University. The focus of his research is in the areas of cognitive radio, wireless networking, applied reinforcement learning, network routing, network security, as well as information and communications technology in education. He is a regular reviewer for over 15 journals, including IEEE journals and magazines, Ad Hoc Networks, IET Communications, and others. He serves as TPC and reviewer for various major international conferences including ICC, VTC, LCN, Globecom, AINA, etc. He serves as an editor for KSII Transactions on Internet and Information Systems. He was a guest editor for the special issue “Artificial Intelligence Enabled Networking” in IEEE Access and "Creating a Smarter Environment through the Advancement of Communication Systems, Networks and Applications” in IET Networks. He also served as General Co-chair for IET ICFCNA’14 and Co-chair Organizing Committee for IET ICWCA’12.
MUHAMMAD ALI IMRAN, University of Glasgow
Muhammad Ali Imran received his M.Sc. (Distinction) and Ph.D. degrees from Imperial College London, UK, in 2002 and 2007, respectively. Starting from September 2016, he will be a Professor in Communication Systems in University of Glasgow, Vice Dean of Glasgow College UESTC and Program Director of Electrical and Electronics with Communications. He is an adjunct Associate Professor at the University of Oklahoma, USA and has served previously in the Institute for Communication Systems (ICS - formerly known as CCSR) at the University of Surrey, UK, from June 2007 to Aug 2016. He has a global collaborative research network spanning both academia and key industrial players in the field of wireless communications. He has lead role in a number of multimillion international research projects including the new physical layer work area for the 5G innovation centre at Surrey. He has supervised 28 successful PhD graduates and published over 200 peer-reviewed research papers including more than 30 IEEE Journals. His research interests include the derivation of information theoretic performance limits, energy efficient design of cellular system and learning/self-organizing techniques for optimization of cellular system operation. He is an associate editor of IET Communications, IEEE Communications Letters and IEEE Access. He was a guest editor of special issues in IEEE Communications Magazine and IEEE Wireless Communications Magazine. He was a guest editor for the special issue “Artificial Intelligence Enabled Networking” in IEEE Access. He is a senior member of IEEE and a Fellow of Higher Education Academy (FHEA), UK.
ADAM WOLISZ, Technische Universität Berlin
Adam Wolisz is chaired Professor of Electrical Engineering and Computer Science at the Technische Universität Berlin, where he has founded and is leading the Telecommunication Networks Group (TKN). Currently he is executive director of the Institute for Telecommunication Systems, grouping the activities in Communications, Networking and Distributed Systems. In parallel he is also adjunct Professor Department of EE&CS, University of California, Berkeley (BWRC). His research interests are in architectures and protocols of communication networks as well as in protocol engineering with impact on performance and QoS aspects. His research focus has been on mobile multimedia communication, sensor networks, and cognitive / cooperative wireless systems. He has authored two books and authored or co-authored over 200 papers in technical journals and conference proceedings. He is senior member of IEEE, IEEE Communications Society (including the TCCC and TCPC) and member of ITG. He is a member of the Steering Board of the GI/ITG Technical Committee on Communication and Distributed Systems (KuVS).