Aims and Scope
In recent years, Cloud-assisted Internet of Things (Cloud-of-Things or in short CoT) has emerged as a revolutionary paradigm that enables intelligent and self-conﬁguring (smart) IoT devices and sensors to be connected with the cloud through the Internet. This new paradigm enables the resource-constrained IoT devices to get the benefit from Cloud’s powerful and scalable high-performance computing and massive storage infrastructure for real-time processing and storing of the IoT data as well as analysis of the processed information under context using inherently complex models. At the same time, cloud can benefit from IoT by allowing its users to build applications that can use and handle these smart IoT objects interconnected and controlled through software services using cloud infrastructure. Thus, the CoT paradigm can stimulate the development of innovative and novel applications to various 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. Hence, in recent times, this centralized CoT model is undergoing a paradigm shift towards a decentralized model termed as edge computing, that allows data computing, storage and service supply to be moved from Cloud to the local edge devices such as smartphones, smart gateways or routers and local PCs that can offer computing and storage capabilities on a smaller scale in real-time. Edge computing pushes data storage, computing and controls closer to the data source(s) instead of performing in a centralized local server or devices as in the case of Fog computing; 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, edge computing 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 computing, still there exists several issues that need to be addressed for CoT paradigm. Some of these issues are: novel network architecture and middleware platform for edge and CoT paradigm considering emerging technologies such as 5G wireless networks, semantic computing; edge analytics for Big data; novel security and privacy methods; social intelligence into the edge node to host CoT applications; and context-aware service management on the edge 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 Cloud-of-Things paradigm. Therefore, the suggested topics of interest for this special issue include, but are not limited to:
– New Edge-CoT computing architecture for data sensing and processing
– 5G communication architecture and protocols for Edge-CoT paradigm
– Interoperability and mobility for Edge to CoT connectivity
– Big data analytics in Edge-CoT paradigm
– Incentive models or techniques for data processing in Edge-CoT paradigm
– Social IoT in Edge-CoT paradigm
– Security and privacy issues in Edge computing for CoT system
– Dynamic resource, service and context management on edge computing for CoT application
– Simulation and emulation platform for Edge-CoT computing
– Performance evaluation of Edge-CoT paradigm
– Algorithms and techniques for computation offloading in Edge-CoT paradigm
– Quality of service/Experience (QoS/QoE) provisioning in Edge-CoT paradigm
– Semantic Edge computing for CoT paradigm
– Consumer centric emerging CoT applications and services on Edge computing
– Industrial Edge computing in CoT paradigm
Paper submission due: January 30, 2018
First-round acceptance notification: May 15, 2018
Revision submission: July 15, 2018
Notification of final decision: Ju1y 30, 2018
Submission of final paper: August 30, 2018
Publication date: November 2018
All manuscripts submission and review will be handled by Elsevier Editorial System http://ees.elsevier.com/jpdc. All papers should be prepared according to JPDC Guide for Authors online: https://www.elsevier.com/journals/journal-of-parallel-and-distributed-computing/0743-7315/guide-for-authors. All papers will be peer-reviewed following the JPDC reviewing procedures. It is important that authors select \”VSI: CoT-Edge\” when they reach the “Article Type” step in the submission process.
Mohammad Mehedi Hassan, King Saud University, Riyadh Saudi Arabia (email@example.com)
Jemal Abawajy, Deakin University, Burwood, Australia (firstname.lastname@example.org)
Min Chen, Huazhong University of Science and Technology, Wuhan, China (email@example.com)
Meikang Qiu, Pace University, USA (firstname.lastname@example.org)
Sheng Chen (IEEE Fellow), University of Southampton, United Kingdom (email@example.com)