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Special Issue "Secure and Energy-Aware Computation Offloading of IoT Sensors in Mobile Edge Computing"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 1 June 2019

Special Issue Editor

Guest Editor
Dr. Robert Hsu

Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan
Website | E-Mail
Interests: Cloud Computing; IoT; RFID; Big Data; Edge & Fog Computing; distributed systems

Special Issue Information

Dear Colleagues,

Sensing technology is fast becoming a part of our lives. It is often expected to continuously sense, collect, and upload various physiological data to improve quality of life. These requirements put a significant demand on improving communication security and reducing the power consumption of the system. As a consequence, traditional computing and mobile communication primarily designed for human being-oriented applications are facing tremendous challenges. Mobile Edge Computing and Communication (MECC) integrates the radio access network, the software defined network, device to device communications, and cloud/edge technologies. With MECC, devices or nodes with storage, computing, and caching capabilities can be deployed in close proximity with sensing devices and act as middleware between cloud and local networks. Computation-excessive and latency-stringent applications can be offloaded to nearby devices through device to device communications or to nearby edge nodes through cellular or other wireless technologies. It is expected that together with MECC, critical issues faced by sensing devices such as short battery life, limited computing capability, and stringent latency can be greatly alleviated.

This Special Issue aims to attract contributions covering both the theory and practice of any of the aforementioned challenges, from the management software stack to domain-specific applications, bringing together state-of-the-art technical solutions and prototype implementations for future MECC. In particular, it focuses on system modelling, design, architecture, implementation, assessment, adaptation, and management of MECC applications and services with wearable devices, together with communication protocols and sharing mechanisms. Possible topics include, but are not limited to, the following:

  • Communications among edges, communication between edges and central cloud, mobile and wearable communications, wearable sensor networks, smart communication technologies;
  • Sensing and wearable devices, implantable devices, wearable sensors;
  • Powering wearable devices, energy harvesting techniques, power management, and constraints optimization;
  • Architecture of MECC, system design, ambient intelligence-driven system, systems designs combining wearable MECC features, and ubiquity;
  • Transmission/networking technologies;
  • Deployment of wearable devices;
  • Trends in mobile/wearable/implantable devices;
  • Trends in mobile/wearable/implantable services and technologies;
  • Assistive, patient body-driven technology;
  • Novel application models;
  • Service migration in Edge Computing systems;
  • Reliability and availability;
  • Security, privacy, and QoS/QoE.

Dr. Robert Hsu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IoT Sensors
  • Mobile Computing
  • Edge Computing
  • Computation offloading
  • Energy-Aware
  • wearable communication

Published Papers (2 papers)

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Research

Open AccessArticle A Feature Extraction Method Based on Differential Entropy and Linear Discriminant Analysis for Emotion Recognition
Sensors 2019, 19(7), 1631; https://doi.org/10.3390/s19071631
Received: 12 February 2019 / Revised: 13 March 2019 / Accepted: 3 April 2019 / Published: 5 April 2019
PDF Full-text (2968 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Feature extraction of electroencephalography (EEG) signals plays a significant role in the wearable computing field. Due to the practical applications of EEG emotion calculation, researchers often use edge calculation to reduce data transmission times, however, as EEG involves a large amount of data, [...] Read more.
Feature extraction of electroencephalography (EEG) signals plays a significant role in the wearable computing field. Due to the practical applications of EEG emotion calculation, researchers often use edge calculation to reduce data transmission times, however, as EEG involves a large amount of data, determining how to effectively extract features and reduce the amount of calculation is still the focus of abundant research. Researchers have proposed many EEG feature extraction methods. However, these methods have problems such as high time complexity and insufficient precision. The main purpose of this paper is to introduce an innovative method for obtaining reliable distinguishing features from EEG signals. This feature extraction method combines differential entropy with Linear Discriminant Analysis (LDA) that can be applied in feature extraction of emotional EEG signals. We use a three-category sentiment EEG dataset to conduct experiments. The experimental results show that the proposed feature extraction method can significantly improve the performance of the EEG classification: Compared with the result of the original dataset, the average accuracy increases by 68%, which is 7% higher than the result obtained when only using differential entropy in feature extraction. The total execution time shows that the proposed method has a lower time complexity. Full article
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Open AccessArticle SatEC: A 5G Satellite Edge Computing Framework Based on Microservice Architecture
Sensors 2019, 19(4), 831; https://doi.org/10.3390/s19040831
Received: 12 January 2019 / Revised: 13 February 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
PDF Full-text (3095 KB) | HTML Full-text | XML Full-text
Abstract
As outlined in the 3Gpp Release 16, 5G satellite access is important for 5G network development in the future. A terrestrial-satellite network integrated with 5G has the characteristics of low delay, high bandwidth, and ubiquitous coverage. A few researchers have proposed integrated schemes [...] Read more.
As outlined in the 3Gpp Release 16, 5G satellite access is important for 5G network development in the future. A terrestrial-satellite network integrated with 5G has the characteristics of low delay, high bandwidth, and ubiquitous coverage. A few researchers have proposed integrated schemes for such a network; however, these schemes do not consider the possibility of achieving optimization of the delay characteristic by changing the computing mode of the 5G satellite network. We propose a 5G satellite edge computing framework (5GsatEC), which aims to reduce delay and expand network coverage. This framework consists of embedded hardware platforms and edge computing microservices in satellites. To increase the flexibility of the framework in complex scenarios, we unify the resource management of the central processing unit (CPU), graphics processing unit (GPU), and field-programmable gate array (FPGA); we divide the services into three types: system services, basic services, and user services. In order to verify the performance of the framework, we carried out a series of experiments. The results show that 5GsatEC has a broader coverage than the ground 5G network. The results also show that 5GsatEC has lower delay, a lower packet loss rate, and lower bandwidth consumption than the 5G satellite network. Full article
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