Intelligent Resource Management in Mobile Edge Computing for IIoT applications

Editor-in-Chief: Carla-Fabiana Chiasserini

Scope and Motivation:

The involvement of Wireless Sensor Network (WSN) in the field of Internet-of-Things (IoT) and Industrial IoT (IIoT) applications has become a new hotspot for the researchers and industries. The Artificial Intelligence (AI) and Machine Learning (ML) is an emerging technology that has proven to have great potential in communications, such as signal classification, channel estimation, and performance optimization. However, in the current era of 5G and Mobile Edge Computing (MEC), cooperative and heterogeneous communication scenarios are developing in a complex and large-scale trend for all the smart applications, especially for IIoTs. These technologies play a vital role in routing establishment, network resource optimization and energy-efficient computing, which are mainly operating in Network and Transport upper layer of OSI model. The power allocation and resource management in these networks remain a challenge due to the miniature size, limited battery life and dynamic movement of the sensor nodes in the Industrial applications. Therefore, for efficient power management and necessary optimization for IIoT applications, AI, Deep Learning (DL) and other Neural Network (NN) based approaches will come up as a solution for green communication. These technologies can be used in MEC paradigm for IIoT applications due to is merits of real-time response, resource capacity as well as low processing power.

For the 5G system specifications (MEC ISG) and 3GPP ecosystem draws attention towards the edge computing enablers. These MEC systems provide opportunities of the ETSI Multi-access Edge Computing group. Recently, the International Telecommunication Union (ITU) have also expressed that the MEC services and resource management can be offered by both mobile network operators as well as third party vendors. Thus, the scope of these paradigms is growing exponentially towards the design, deployment, maintenance and security of MEC for Industry 4.0 applications.

This special issue will focus on Intelligent Resource management in MEC with the theory and practical aspects of recent outcomes and developments in MEC IIoT applications. The issue invites the researchers and industry practitioners to submit high quality unpublished technical articles, highlighting the scopes and challenges for resource allocation in MEC IIoT applications.

The topics of interest include, but are not limited to:

• Distributed Artificial Intelligence based computation models for MECs
• Resource optimization in IIoT applications
• Network set-up, security issues with MEC IIoT
• Resource allocation techniques for green MEC IIoT services
• Data offloading, traffic and cloud services for Industrial MEC
• Energy efficient user scheduling and resource allocation for Industry 4.0
• Congestion control and low latency for MEC IIoT
• Neural network based ambience intelligence for IIoT
• AI based cloud virtualization in Industrial MEC
• Cloud and edge security for IIoT applications
• Fog and mist computing for Industry 4.0
• Architecture and scalability for AI enabled mobile IIoT applications

Schedule:

Deadline for submissions: 30th April 2020

Notification of First Round: 15th June 2020

Notification of Second Round: 30th August 2020

Final Acceptance: 30 October

Tentative Publication Date: December 2020

Guest Editors:

1. Prof. Rubén González Crespo
Deputy Director and Professor
Department of Computer Science
Universidad Internacional de la Rioja (UNIR)
Email: ruben.gonzalez@ijimai.org, ruben.gonzalez@unir.net
Webpage: https://www.unir.net/profesores/ruben-gonzalez-crespo/

2. Dr. Hongyang Chen
Fujitsu Limited, Japan
Email: dr.h.chen@ieee.org
Webpage: https://www.linkedin.com/in/hongyangchen/

3. Prof. Yannick Le Moullec
Professor
Thomas Johann Seebeck Department of Electronics
Tallinn University of Technology
Email: yannick.lemoullec@taltech.ee
Webpage: https://www.taltech.ee/en/personnel-search/&kood=T0066767

4. Dr. Amrit Mukherjee
School of Computer Science and Communication Engineering
Jiangsu University, Zhenjiang, China
Email: amrit1460@ujs.edu.cn, amrit1460@ieee.org
Webpage: https://www.researchgate.net/profile/Amrit_Mukherjee