Active special issues

Special issue on BIG DATA 2022



There has been a tremendous growth in the amount of data generated in the last two decades. Digitization of process, advent of Internet of Things (IoT), substantial rise of social media usage, adoption of hand-held and wearable devices has become the major cause for incredible rise in data generation. Studies show that in the next five years, the amount of data generated each day is expected to reach around 450 Exabyte’s globally making it viable to create new pathways in understanding social and cultural dynamics. Such data can help the organization / business in decision-making thus providing competitive advantage and sustainability in market. Huge volumes of data generated in variety of forms makes it ‘Big’ hence its challenges and complexity. With the enormous potential of big data, it is important for organizations to know the key tenants of big data optimisation. Big data optimisation is the key to accurate data analytics. If data is not properly optimized, several challenges such as inaccurate findings and delays in processing may arise. However, there are different ways to optimize big data including standardizing format, tuning algorithms, leveraging the latest technology, fixing data errors and removing any latency in processing. Optimized data improves the rate of data processing and the accuracy of results. The complexity and challenges exist in collecting, storing, retrieving, processing, transmission, decision making and applicability in various sectors.

Big data is widely perceived as essential for the accomplishment of the design optimization of complex systems. Much effort has been dedicated to the use of data to enhance the performance of meta-heuristic optimization algorithms for solving large-scale problems in the presence of large amounts of uncertainties. Seamless integration of modern learning and optimization techniques, effective formulation of optimization problem and visualization are few of the challenges in Big Data Optimization. One major hindrance is the massive computational cost required for evaluating the quality of complex engineering systems. The emerging Big Data technologies will eradicate the obstacle to a certain extent by reusing knowledge extracted from huge volumes of high-dimensional, heterogeneous and noisy data. Such knowledge can also be acquired with new visualization techniques. Big data driven optimization will also play a key role in reconstruction of large-scale biological systems.

This Special Issue entitled “Big Data Optimization Methods Challenges, Issues and Applications” provides the necessary background for both academics and practitioners interested to explore optimization algorithms for Big Data and work in the Big Data setting making it beneficial to the society, industry, academia, government and in a variety of industries. This will be useful for the investigators aiming to analyze large scale data and its optimisation methods.

The topics of interest for the special issue include but not limited to the following:

·       Optimization Strategies in Big Data Analytics

·       Convergent parallel algorithms for big data

·       Performance Tools for Big Data Optimization

·       Big Data and Query Optimization Techniques

·       Optimized approaches for storing and accessing files

·       Challenges in Big Data Optimization

·       Optimization Techniques for Learning in Big Data

·       Hadoop Optimization and Performance Tuning techniques

·       Optimization Tools, Techniques and Research Issues for Cloud-Based Big Data Analytics

·       Optimization algorithms for Big Data in Real-time application

·       Machine Learning Optimization Methods and Techniques



Tentative Timeline:

Submission Deadline of Papers:          20.01.2022

Authors Notification Date:                  24.03.2022

Revised Papers Due Date:                    13.06.2022

Final notification Date:                        05.09.2022


Guest Editor Team:

Dr. BalaAnand Muthu [Lead Guest Editor]

Associate Professor,

Department of Computer Science & Engineering,

Adhiyamaan College of Engineering, India


Google Scholar:  


BalaAnand Muthu received Ph.D from Anna University, India and working as Associate Professor in the Department of Computer Science & Engineering at Adhiyamaan College of Engineering, India, India. His area of interest includes Big Data Analytics, Social Networks, Internet of Things, Cloud Computing in Healthcare and Environment applications. Served Guest editor in several journals of  IGI, Inderscience, Springer publishers. Also, have published research articles in IEEE Transactions, SCI, SCIE, Scopus indexed peer review journals. Meanwhile, handled Guest lectures, Intensive Workshop, Hands on programming in Hadoop, Spark, Grid & Cloud Computing at various technical institutions around India. He is serving as reviewer in Computer Communication, IEEE Access, Multimedia Tools & Applications, International Journal of Parallel Programming, Enterprise Information System, Computer Networks, Measurement, Computer & Electrical Engineering, Wireless Personal Communication, Cluster Computing, Computational Intelligence, IET Transport Systems and so on. Having membership in IEEE & ACM.



Dr. Imran Shafique Ansari

James Watt School of Engineering

University of Glasgow,

Official Website:   


Google Scholar:   


Imran Shafique Ansari received the B.Sc. degree in Computer Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2009 (with First Honors) and M.Sc. and PhD degrees from King Abdullah University of Science and Technology (KAUST) in 2010 and 2015, respectively. Currently, since August 2018, he is a Lecturer (Assistant Professor) with University of Glasgow, Glasgow, UK. Prior to this, from November 2017 to July 2018, he was a Lecturer (Assistant Professor) with Global College of Engineering and Technology (GCET) (affiliated with University of the West of England (UWE), Bristol, UK). From April 2015 to November 2017, he was a Postdoctoral Research Associate (PRA) with Texas A\&M University at Qatar (TAMUQ). From May 2009 through Aug. 2009, he was a visiting scholar with Michigan State University (MSU), East Lansing, MI, USA, and from Jun. 2010 through Aug. 2010, he was a research intern with Carleton University, Ottawa, ON, Canada.


He has been affiliated with IEEE since 2007 and has served in various capacities. He is serving on the IEEE (Global) Nominations and Appointments (N\&A) Committee 2020-2021 and IEEE Communication Society Young Professionals (ComSoc YP) Committee since April 2016. He is part of the IEEE 5G Tech Focus Publications Editorial Board since Feb. 2017. He is an active reviewer for various IEEE Transactions and various other journals. He has served as a TPC for various IEEE conferences. He is a recipient of appreciation for an exemplary reviewer for IEEE Transaction on Communications (TCOM) in 2018 and 2016, a recipient of appreciation for an exemplary reviewer for IEEE Wireless Communications Letters (WCL) in 2017 and 2014, a recipient of post-doctoral research award (PDRA) (first cycle) with Qatar national research foundation (QNRF) in 2014, and a recipient of IEEE Richard E. Merwin student scholarship award in Jul. 2013.


Dr. Ansari has authored/co-authored 95+ journal and conference publications. He has co-organized the GRASNET'2016, 2017, 2018 workshops in conjunction with IEEE WCNC'2016, 2017 and IEEE Globecom 2018. His current research interests include free-space optics (FSO), channel modeling/signal propagation issues, relay/multihop communications, physical layer security, full duplex systems, and secure D2D applications for 5G+ systems, among others.




Dr. Xuan Liu (yusuf)

College of Information Engineering (College of Artificial Intelligence),

Yangzhou University, China;


Personal Website:  

Google Scholar:


Xuan Liu (MIEEE’17) received Ph.D. degree in Computer Science and Engineering at Southeast University, China, and is a lecturer currently with School of Information Engineering at Yangzhou University, China. He is also serving as an Advisory Editor of Wiley Engineering Reports, an Associate Editor of Springer Telecommunication Systems, IET Smart Cities, Taylor& Francis International Journal of Computers and Applications and KeAi International Journal of Intelligent Networks, an Area Editor of EAI Endorsed Transactions on Internet of Things, the Lead Guest Editor of Elsevier Internet of Things, Wiley Transactions on Emerging Telecommunications Technologies and Wiley Internet Technology Letters, and the Chair of CollaborateCom 2020 workshop. He served(s) as a TPC Member of ACM MobiCom 2020 workshop, IEEE INFOCOM 2020 workshop, IEEE ICC 2021/2020/2019, IEEE GlobeCom 2020/2019, IEEE WCNC 2021, IFIP/IEEE IM 2021, IEEE PIMRC 2020/2019, IEEE MSN 2020, IEEE VTC 2020/2019/2018, IEEE ICIN2020, IEEE GIIS 2020, IEEE DASC 2019, APNOMS 2020/2019, AdHoc-Now2020, FNC 2020/2019, EAI CollaborateCom 2020/2019, and EAI ChinaCom 2019, etc. Furthermore, he served as a Reviewer for 20+ reputable conferences/journals including IEEE INFOCOM, IEEE ICC, IEEE GlobeCom, IEEE WCNC, IEEE PIMRC, IEEE COMMAG, IEEE TII, IEEE IoT, IEEE CL, Elsevier JNCA, Elsevier FGCS, Springer WINE, Springer TELS, IET SMC, EAI CollaborateCom, and Wiley IJCS, etc. His main research interests focus on UAVs-enabled collaborative networking techniques.

Special issue on Design Optimization of Soft Robotics

Important Dates

[Article Submission Deadline]


[Authors Notification Date]


[Revised Papers Due Date]


[Final notification Date]


Currently, robotics is highly used in factory workplaces and manufacturing industries, where human-robot interaction rarely occurs. Although this rigid body robot is programmed precisely to perform any high-precision factory tasks in well-structured surroundings, they have limitations in dealing with an unforeseeable event that occurs in highly dynamic environments due to the lack of adaptability, flexibility, and multifunctionality of natural organisms. This lack of flexibility leads to the separate robotic workplace from human interaction to ensure human safety. Also, the lack of compliance and obedience in conventional robotics is another issue. Soft robotics is a recent emerging and exciting research field that efficiently addresses these traditional robotics issues and improves hard robotics performance and image.  With flexibility and compliance, soft robotics able to fill the gap between human and machine.

Soft robots are primarily made up of soft, flexible, deformable matter materials like gels, elastomers, and fluid that exhibit rheological and elastic characteristics of biological organs and tissues. Such a deformable structure and biological muscular system based actuation make soft robots adaptable, sensitive, and agile, just like octopus or caterpillar who can hunt their prey with their flexible muscular strength and agility. The soft robot with such locomotion and adaptable strategy can apply to a broad range of tasks that include unexpected obstacles and executes in dynamic environments. As the soft robots exhibit soft, versatile, and elastic properties of a natural organism, the utility of this bioinspired based soft robot is extended to a highly multidisciplinary paradigm in engineering. This technological and nature-inspired advancement revolutionizes robotics in various application domains, including healthcare, agriculture, and supportive human assistance. In addition to the multifunctionality of the natural organism, efficiency is also essential for soft robot design. A natural-inspired and evolutionary algorithm is one of the promising solutions to address this challenge.

Recently, lots of research has been conducted in this area to solve optimization issues. Consequently, various algorithms have been developed in this field, including ant colony optimization, particle swarm optimization, wolf search, bee colony, flower pollination, bat algorithm, and cat swarm.  However, designing efficient nature-inspired algorithms and using these algorithms for real-world application domains in soft robotics and control are still significant issues and need further exploration. This special issue focuses on bringing research work on developing newly nature-inspired and evolutionary algorithms or innovative applications in the soft robot design for real-world applications from every corner of the world. We invite all potential research scholars to submit their original research article that proposes innovative research ideas in designing soft robot based on nature-inspired and human- intelligence technology.

The topics of interest for the special issue include, but not limited to, the following:

Å     Design optimization of the soft robot using a nature-inspired algorithm

Å     IoT assisted machine-intelligence based soft robotic design optimization model using an evolutionary algorithm

Å     Research trend towards bio-inspired soft robotic design optimization

Å     Challenges and opportunities to design real-world application based soft robot using a nature-inspired optimization technique

Å     A bio-inspired design optimization model for a soft robot

Å     The auto-intelligent soft robot design with a nature-inspired optimization technique

Å     Biological inspiration based soft robotic model for healthcare assistance

Å     Teaching learning based soft robotic design model using a nature-inspired algorithm

Å     Intelligent, adaptable, and nature-inspired soft robot design model

Å     A fully flexible three-dimensional bio-inspired soft robot with magnetic actuation

Å     Soft robot sensing and controlling design with bio-inspiration based optimization technology

Å     Resilient and adaptive soft robot using a nature-inspired and evolutionary algorithm based design optimization

Å      A dynamic model for soft robotic with nature-inspired design optimization

Å     Explore the soft robotic behavior with natural inspiration with intelligence and quick adaptability

Guest Editors Bio

Dr. Gunasekaran Manogaran [Leading Guest Editor]

College of Engineering and Architecture (CEA),

Department of Electrical Engineering and Computer Science,

Howard University,

Washington D.C., USA


Google Scholar:

Dr. Gunasekaran Manogaran is currently working in theDepartment of Electrical Engineering and Computer Science, Howard University, Washington, D.C., USA. He is also an Adjunct Assistant Professor, Department of Computer Science & Information Engineering, Asia University, Taiwan and Adjunct Faculty, in School of Computing, SRM Institute of Science and Technology, Kattankulathur, India. He is a visiting researcher/scientist in University of La Frontera, Colombia and International University of La Rioja, Spain. He received his Ph.D. from the Vellore Institute of Technology University, India. He received his Bachelor of Engineering and Master of Technology from Anna University, India and Vellore Institute of Technology University, India respectively. He is the author/co-author of more than 100 papers in conferences, book chapters and journals including IEEE Transactions on Industrial Informatics, IEEE Transactions on Computational Social Systems, IEEE Internet of Things, IEEE Intelligent System, IEEE Access, ACM Transactions on Multimedia Computing, Communications, and Applications. He is currently serving as an Associate Editor in Ambient Intelligence & Humanized Computing (Springer), International Journal of Automation and Computing (Springer), Data in Brief (Elsevier) and International Journal of Interactive Multimedia and Artificial Intelligence. He is one of the Advisory Board Member of Information System (Elsevier) and an Editorial Board Member of International Journal of Computer Applications in Technology. He also appointed as Internet of Things Section Editor in Sensors (MDPI). He is on the reviewer board of several international journals and has been a member of the program committee for several international/national conferences and workshops. He currently serves on Technical Program Committee for 2018 IEEE International Conference on Consumer Electronics (ICCE) in Las Vegas, USA. He is the guest editor for various international journals including IEEE, Springer, Elsevier, Inderscience, IGI, Taylor & Francis and Emerald publishing. He has worked as a Research Assistant for a project on spatial data mining funded by Indian Council of Medical Research, Government of India. He is Principal Investigator (PI) for the project entitled “Prognosis of Microaneurysm and Early Diagnosis System for Non-Proliferative Diabetic Retinopathy using Deep Convolutional Neural Network”, (Fund Allocated: $83,322.51 (USD), Project-ID: #111) funded by Scheme for Promotion of Academic and Research Collaborations (SPARC), Ministry of Human Resource Development, Government of India. He is a Co-Investigator for the project entitled “Agent Based Modeling of HIV epidemic in state of Telangana, India” funded by Pitt Public Health, Pittsburgh University, USA. He got an award for young investigator from India and Southeast Asia by Bill and Melinda Gates Foundation, USA. He is a member of IEEE Society and International Society for Infectious Diseases and Machine Intelligence Research labs. His current research interests include Big Data Analytics, Internet of Things and Soft Computing.

Dr. Hassan Qudrat-Ullah [Co-Guest Editor]       

Professor of Decision Sciences,

School of Administrative Studies, York University, Toronto, Canada


Research Gate:

Google Scholar:

Dr. Hassan Qudrat-Ullah earned his Ph. D. (Decision Sciences) in 2002 from NUS Business School, National University of Singapore. Hassan did post-doctoral fellowship at Carnegie Mellon University, USA, in 2002-2003 before joining York University in 2003. His research contributions from 2011 to 2014 include two books Better Decision Making in Complex, Dynamics Tasks (Springer, 2014), and an edited volume Energy Policy Modeling in 21st Century (Springer, 2013); he also contributed seven journal articles, two book chapters and he has also been invited to several conference proceedings and invited talks. His journal articles are published in such journals as Decision Support Systems, Energy (2 articles), Telecommunication Systems, and International Journal of Technology Management. Hassan’s research interests include dynamic decision making, system dynamics modeling, computer-simulated interactive learning environments, and energy planning models. Hassan’s work has been published in Energy, Energy Policy, Decision Support Systems, Computers & Education, and Simulation & Gaming. He is the Editor-in-Chief of International Journal of Complexity in Applied Science and Technology and Associate Editor of International Journal of Global Energy Issues. He has published more than 70 research items and has been cited around 900 times. He has Google scholar h-index of 16 i10-index of 20; his Research Gate score is 24.39. He has received Excellence in Teaching Award, Excellence in Research Award and 2016-17 Dean's Award for Distinction in Research at York University.

Dr. Qin Xin [Co –Guest Editor]

Full Professor of Computer Science, Faculty of Science and Technology,

University of the Faroe Islands, Faroe Islands. Denmark


Research Gate:

Google Scholar:        

Dr. Qin Xin graduated with his Ph.D. in Department of Computer Science at University of Liverpool, UK in December 2004. Currently, he is working as a professor of Computer Science in the Faculty of Science and Technology at the University of the Faroe Islands (UoFI), Faroe Islands. Prior to joining UoFI, he had held variant research positions in world leading universities and research laboratory including Senior Research Fellowship at UniversiteCatholique de Louvain, Belgium, Research Scientist/Postdoctoral Research Fellowship at Simula Research Laboratory, Norway and Postdoctoral Research Fellowship at University of Bergen, Norway. His main research focus is on design and analysis of sequential, parallel and distributed algorithms for various communication and optimization problems in wireless communication networks, as well as cryptography and digital currencies including quantum money. Moreover, he also investigates the combinatorial optimization problems with applications in Bioinformatics, Data Mining and Space Research. Currently, he is serving on Management Committee Board of Denmark for several EU ICT projects and has produced more than 70 peer reviewed scientific papers. His works have been published in leading international conferences and journals, such as ICALP, ACM PODC, SWAT, IEEE MASS, ISAAC, SIROCCO, IEEE ICC, Algorithmica, Theoretical Computer Science, Distributed Computing, IEEE Transactions on Computers, Journal of Parallel and Distributed Computing, IEEE Transactions on Dielectrics and Electrical Insulation, and Advances in Space Research. He has been very actively involved in the services for the community in terms of acting (or acted) on various positions (e.g., Session Chair, Member of Technical Program Committee, Symposium Organizer and Local Organization Co-chair) for numerous international leading conferences in the fields of distributed computing, wireless communications and ubiquitous intelligence and computing, including IEEE MASS, IEEE LCN, ACM SAC, IEEE ICC, IEEE Globecom, IEEE WCNC, IEEE VTC, IFIP NPC, IEEE Sarnoff and so on. He is the Organizing Committee Chair for the 17th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2020, Torshavn, Faroe Islands). Currently, he also serves on the editorial board for more than ten international journals.