Impact Score 2.81
Communication technologies are one of the fastest-changing areas, with related services and applications having an enormous and almost immediate impact on diverse aspects of modern society, including inter-human relations, economy, education, and entertainment. In this respect the development of reliable and robust yet flexible and future proof communication infrastructure capable of real-time, secure, and cost-effective delivery of data is of utmost importance to increase the user’s perceived quality of life by facilitating human-to-human as well as human-to-machine communication almost anywhere and anytime, providing services such as e-health, e-learning, and e-payments. Future networks will be ever more complex, extending towards ubiquitous communications, and will provide a broad range of other services and applications, from remote managing of an intelligent house to advanced real-time navigation systems. Despite the increased complexity, future networks should be energy efficient, easily maintainable and their capabilities should be continuously improved and upgraded by relying as little as possible on human intervention. The networking research community proposed a new paradigm for networking: machine learning, cybernetics, and cognitive computing for energy-aware communication technology to meet this demand. Cognitive computing breaks the traditional boundary between neuroscience and computer science and paves the way for machines that will have reasoning abilities analogous to a human brain. Cybernetics and machine learning are different ways of thinking about intelligent systems or systems that can act toward reaching a goal. Machine learning and cybernetics both consider how systems can learn. However, while machine learning considers using stored representations as a means of acting intelligently, cybernetics focuses on grounded and situated behaviors that express intelligence and learning based on feedback and interaction. Thus, cybernetics can provide a useful framework in creating human-centered interactive machine learning-based energy-aware communication applications. This special issue will consider submissions in the broad area of Machine Learning, Cybernetics, and Cognition for energy-aware communications and networks, with an emphasis on taking a holistic and possibly trans-disciplinary approach to the design of complex communications systems. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme.
Topics of interest include (but are not limited to):
General information and instructions for submitting papers to SUSCOM can be found at the journal website: https://www.journals.elsevier.com/sustainable-computing-informatics-and-systems. Please see the “Guide for Authors” and “Submit Your Paper” links. When submitting a paper to this special issue, please make sure to select the “Special Issue: EMC3” option when prompted for “Select Article Type” during the submission process. All submissions must be original and may not be under review by another publication. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 30% new material). Authors are requested to clearly identify prior submissions/papers and attach to the submitted paper their relevant, previously published articles with a summary explanation documenting the enhancements made in the journal submission. All submitted papers will be peer reviewed using the normal standards of SUSCOM. By submitting a paper to this issue, the authors agree to referee at least one paper if requested by SUSCOM editors.
Special Issue Guest Editors:
Managing Guest Editor: Gautam Srivastava, Brandon University, Canada, [email protected]
Co-Guest Editors: Jerry Chun-Wei Lin, Western Norway University of Applied Sciences, Norway, [email protected]
Nitin Gupta, National Institute of Technology, Hamirpur, India, [email protected]
Deepak Kr. Sharma, Netaji Subhas University of Technology (Formerly NSIT), New Delhi, India, [email protected]
Contact Information: For additional information or questions on this special issue, please write to: [email protected]