Journal Information
IEEE Communications Magazine
http://www.comsoc.org/commag
Impact Factor:
5.125
Publisher:
IEEE
ISSN:
0163-6804
Viewed:
5278
Tracked:
9

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IEEE Communications Magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications systems (PCS), ISDN, and more. It includes special feature technical articles and monthly departments: book reviews, conferences, short courses, standards, governmental regulations and legislation, new products, and Society news such as administration and elections.
Last updated by Dou Sun in 2016-10-17
Special Issues
Special Issue on Advances in Network Services Chain
Submission Date: 2017-02-01

Several business research forecasts sustain the necessity of a more open software- and user- centric approach towards networking. During the last years, the interested scientific community has witnessed the emergence of a whole range of novel network architectures. To name just a few of them, we could enumerate Software Defined Networking (SDN) and Network Function Virtualization (NFV). However all these advances may be insufficient for providing full openness and user-centric infrastructures. For example, SDN has reached a high popularity but fails in opening the platform to the end users. Network programmability in SDN is in charge of the operator of the service. Something similar occurs in the case of NFV, where the applications (network services) are controlled by the service providers. Therefore, a number of suggestions for improving existing architectures have been proposed with the objective to provide an open and extensible networking platform, capable of counteracting the increased dominance of few but mighty global players in the fields of internet technology, information storage and social media. Between these promising technologies and implementation patterns let us emphasize Microservices architectures, Adaptive Security and Containerization. On the (distributed) data storage mechanisms side, emerging strongly, we can name Blockchain and other similar approaches. Microservices are starting to get a lot of attention in the two or three years although the programming pattern itself is not so new. An application that is designed in a microservice-like style implies that the programming of composing modules as stand-alone services communicating with each other is figured in a lightweight manner, often using a REST/Http API. The main difference to the classic Monolithic Applications (built a single module/entity) or even Enterprise Applications (often constructed as a 2 or 3-tier system with a frontend, backend and database layer) is the splitting of the application functionality into independently deployable components (the microservices) each one being designed to scale independently from the others. Also, service boundaries are clean, opening the possibility to write the microservices (belonging to the same application) even in different programming languages. In this context, this Feature Topic (FT) aims to promote new research for providing mechanisms and introducing them to the existing (or novel) architectures in order to increase openness and user-centric capabilities of networking infrastructures. Such mechanisms and programming patterns may be based on old solutions but decisively should help the new architectures to deal with the most outstanding problematics for becoming open software-centric and user-centric.
Last updated by Dou Sun in 2016-10-17
Special Issue on Behavior Recognition based on Wi-Fi Channel State Information (CSI)
Submission Date: 2017-02-01

Human behavior recognition is the core technology that enables a wide variety of human-machine systems and applications, e.g., health care, smart homes, and fitness tracking. Traditional approaches mainly use cameras, radars, or wearable sensors. However, all these approaches have certain disadvantages. For example, camera-based approaches have the limitations of requiring line of sight with enough lighting and potentially breaching human privacy. Low cost radar-based solutions have limited operation range of just tens of centimeters. Wearable sensor-based approaches are inconvenient sometimes because of the sensors that users have to wear. Recently, Wi-Fi CSI-based human behavior recognition approaches are attracting increasing attention. The rationale is that different human behaviors introduce different multi-path distortions in Wi-Fi CSI. Compared with traditional approaches, the key advantages of Wi-Fi CSI-based approaches are that they do not require lighting, provide better coverage as they can operate through walls, preserve user privacy, and do not require users to carry any devices as they rely on the Wi-Fi signals reflected by humans. As a result, the recognition of quite a number of behaviors that are difficult based on traditional approaches have now become possible, e.g., fine-grained movements (e.g., gesture and lip language), keystrokes, drawings, gait patterns, vital signals (e.g., breathing rate and heart rate), etc. However, Wi-Fi CSI-based behavior recognition still faces a number of challenges: How to build the CSI-behavior model and algorithms that are robust for different humans? How to overcome the impact of noise and ensure the performance of CSI-enabled systems? How to simultaneously recognize the behavior of multiple users? How the CSI-enabled system can adapt and evolve according to the environment change? This FT provides the opportunity for researchers and product developers to review and discuss the state-of-the-art and trends of Wi-Fi CSI-based behavior recognition techniques and systems. In the light of the above, the main goals of this FT are threefold: - to promote unparalleled / first-time approaches and techniques in signal processing, feature extraction, data mining and model construction for behavior recognition based on Wi-Fi CSI; - to identify open issues which remain a challenge towards the convergence of computation theories and technologies for behavior recognition based on Wi-Fi CSI; - to exploit novel application areas and demonstrate the benefits of Wi-Fi CSI in contrast with more traditional sensing approaches. Topics may include (but are not limited to): - Behavior Recognition Model/Theory based on Wi-Fi CSI - Behavior Recognition Algorithms based on Wi-Fi CSI - Wi-Fi CSI Signal Processing for Behavior Recognition - Wi-Fi CSI Data Mining for Behavior Recognition - Novel Behavior Recognition Applications/Systems Supported by Wi-Fi CSI - Evaluation Metrics and Empirical Studies of Wi-Fi CSI enabled Systems - Quality-enhanced and adaptive sensing models with Wi-Fi CSI
Last updated by Dou Sun in 2016-10-17
Special Issue on Education & Training: Scholarship of Teaching and Supervision
Submission Date: 2017-05-01

The Scholarship of Teaching and Learning (SoTL) encourages educators to examine their own classroom practice, record their successes and failures, and ultimately share their experiences in a formal and scholarly way so that others may reflect on their findings and build upon teaching and learning processes. SoTL acknowledges that concerns for privacy and other ethical issues associated with studies involving human subjects place limits on the types of research that can be conducted in classroom setting. Nevertheless, SoTL provides a mechanism for raising the standard of discussion concerning teaching and learning in the literature. The Scholarship of Research and Supervision (SoRL) is a related concept that invites the same reflective approach to improving the quality of training through research, especially that conducted at the postgraduate level. SoRL invites researchers to examine their own supervisory practice, record their successes and failures, and ultimately share their experiences in a formal and scholarly way so that others may reflect on their findings and improve research and supervision processes. This feature topic on the Scholarship of Teaching and Supervision is intended to hasten the incorporation of SoTL and SoRL into communications engineering curricula by providing educators and researchers with an opportunity to share their experience, best practices and case studies.
Last updated by Dou Sun in 2016-10-17
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