Emerging Edge-of-Things Computing: Opportunities and Challenges

in Special Issue   Posted on August 13, 2017 

Information for the Special Issue

Submission Deadline: Thu 30 Nov 2017
Journal Impact Factor : 3.997
Journal Name : Future Generation Computer Systems
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/special-issue-on-emerging-edge-of-things-computing
Journal & Submission Website: https://www.sciencedirect.com/journal/future-generation-computer-systems

Special Issue Call for Papers:

Recently, the Internet of Things (IoT) has emerged as a revolutionary technology that promises to offer a fully connected “smart” world. It enables billions of everyday objects such as consumer goods, enduring products, vehicles, utility components, sensors, and other physical devices to be connected with the global Internet that aims to transform the way we live, work, and play. However, a wide-scale realization of IoT is hindered due to the significant constraints of IoT devices in terms of memory, processing resources, energy, or communication bandwidth. The rise of Cloud-assisted Internet of Things or Cloud-of-Things (CoT) paradigm has been seen as an enabler to solve many of these issues as it offers networked and remote computing resources to process, manage, store and share huge volume of IoT data. It has stimulated the development of various innovative and novel applications in areas such as smart cities, smart homes, smart grids, smart agriculture, smart transportation, smart healthcare, etc. to improve all aspects of people’s life.

However, currently the CoT paradigm is facing increasing difficulty to handle the Big data that IoT generates from these application use cases. As billions of previously unconnected devices are now generating more than two exabytes of data each day, it is challenging to ensure low latency and network bandwidth consumption, optimal utilization of computational recourses, scalability and energy efficiency of IoT devices while moving all data to the Cloud. To cope with these challenges, a recent trend is to deploy an Edge Computing infrastructure between IoT systems and Cloud computing. This new paradigm termed as Edge-of-Things (EoT) computing, allows data computing, storage and service supply to be moved from Cloud to the local Edge devices such as smart phones, smart gateways or routers and local PCs that can offer computing and storage capabilities on a smaller scale in real-time. EoT pushes data storage, computing and controls closer to the IoT data source(s); therefore, enables each Edge device to play its own role of determining what information should be stored or processed locally and what needs to be sent to the Cloud for further use. Thus, EoT complements CoT paradigm in terms of high scalability, low delay, location awareness, and allowing of using local client computing capabilities in real time.

While researchers and practitioners have been making progress within the area of Edge-of Things computing, still there exists several issues that need to be addressed for its large-scale adoption. Some of these issues are: novel network architecture and middleware platform for EoT paradigm considering emerging technologies such as 5G wireless networks, software defined network and semantic computing; Edge analytics for IoT Big data; novel security and privacy methods for EoT; social intelligence into the Edge node to host IoT applications; and context-aware service management on the EoT with effective quality of service (QoS) support and other issues.

Topics of Interest

This special issue targets a mixed audience of researchers, academics and investigators from different communities to share and exchange new ideas, approaches, theories and practice to resolve the challenging issues associated with the leveraging of Edge computing for Edge-of-Things paradigm. Therefore, the suggested topics of interest for this special issue include, but are not limited to:

– Novel middleware architecture design for EoT paradigm

– Semantic Edge computing for IoT

– Edge analytics for Big data in IoT

– Edge-enabled 5G network architecture and protocols for IoT

– Software Defined Networking for EoT paradigm

– Social intelligence in EoT system

– EoT operating system design and validation

– Interoperability and mobility for Edge to IoT connectivity

– Trust, security and privacy issues in EoT system

– Resource, service and context management on Edge computing for IoT applications

– Software and simulation platform for EoT paradigm

– Energy-aware resource scheduling in Edge computing for IoT applications

– Emerging Edge commuting services and applications for IoT

– Industrial Edge computing in IoT paradigm

Submission Guidelines

Submissions will be judged based on their originality, novelty, and quality. Submissions must not substantially overlap with papers that have been previously published or are currently submitted for publication. The submissions must be clearly written and in excellent English. All received submissions within the scope of the issue will be peer-reviewed following the FGCS reviewing procedures and will be evaluated with respect to the relevance to this special issue, level of innovation, depth of contribution, and quality of presentation. Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Future Generation Computer Systems at http://ees.elsevier.com/fgcs/. Authors should select SI “Emerging Edge-of-Things” when they reach the “Article Type” step in the submission process.

Important Dates

Paper submission due: Nov 30, 2017

First-round acceptance notification: March 1, 2018

Revision submission: April 15, 2018

Notification of final decision: May 15, 2018

Submission of final paper: June 15, 2018

Publication date: 3rd quarter of 2018

Guest Editors

Mohammad Mehedi Hassan (Leading Guest Editor)
King Saud University, Riyadh Saudi Arabia
[email protected]

A.M. Goscinski
Deakin University, Burwood, Australia
[email protected]

Giancarlo Fortino
University of Calabria, Italy
[email protected]

Sourav Bhattacharya
Nokia Bell Labs, Dublin, Ireland
[email protected]

Sheng Chen (IEEE Fellow)
University of Southampton, United Kingdom
[email protected]

Mengchu Zhou (IEEE Fellow)
New Jersey Institute of Technology, Newark, NJ, USA
[email protected]

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