Special Issue: Intelligent Techniques for Efficient Resource Management in IoT Networks

Theme and Scope

The Internet of Things (IoT) has become exceptionally popular over the last few years with widespread applications. Unlike the other technologies, IoT continues to prove itself extremely valuable and inevitable across numerous sectors. As IoT adoption continues to develop, finding efficient IoT networks focusing on energy efficiency has become the emerging technological requirement. This is mainly because the new and evolving IoT applications can impose various constraints on sustainable IoT networks in terms of power resources and environmental conditions. Like smart devices, connectivity, and cloud analytics, network and device management is also an important part of the IoT architecture. In this special issue, we explore the importance of intelligent techniques in efficient IoT devices and network management, emphasizing the IoT value chain.

The prime role of intelligent techniques in IoT network management is that it offers an intelligent way to automate tasks consistently increasing in complexity and frequency. As the IoT networks and the devices become more complex, they have specific needs, managing them with traditional computing facilities and limited power are extremely hard. Using intelligent techniques helps manage the IoT networks more robustly with integration towards the existing tools, basic automation, and improved quality of services. Intelligent techniques such as artificial intelligence, machine learning, and robotic process automation effectively meet the growing demands of the IoT ecosystem. It provides improved integrability and interoperability with energy efficiency measures. It further helps in five major considerations of IoT network and device management such as modular, platform-independent design, cross-vendor device compatibility, open architecture with powerful integration tools, built-in security, and intuitive and customizable IoT networks. This property ensures efficient management of the IoT devices and networks irrespective of the changing requirements. Furthermore, it simplifies the deployment and management of the downstream applications. It streamlines the network monitoring and troubleshooting and accelerates the time to market with reduced costs.

This special issue seeks cutting-edge research submissions that address the problem of resource management in IoT networks. Specifically, we seek submissions that efficiently integrate intelligent techniques such as artificial intelligence and machine learning approaches that focus on energy efficiency and green IoT solutions. Empirical, conceptual, and practical research works in this background are most welcomed. The list of topics of interest include but are not limited to the following:

  • Intelligent techniques for energy-efficient IoT network design
  • Role of artificial intelligence in IoT network and device management
  • Computational intelligence for managing the power consumption trends and smart management of devices across IoT networks
  • AI for IoT traffic characterization and resource management
  • Trends in fog/edge computing for intelligent IoT network management solutions
  • Intelligent systems architectures for efficient IoT network management
  • Addressing the IoT network challenges with computational intelligence techniques
  • Machine learning assisted energy-aware green wireless communication networks for IoT
  • Intelligent techniques for green and sustainable IoT networks
  • AI driven power management for sensor nodes in IoT networks
  • Intelligent techniques for improved quality of services across IoT networks
  • AI for carbon-neutral smart networks management in IoT environment
  • Secure interoperable IoT networks with artificial intelligence

 

Instructions for Manuscripts

Each paper, written in English, the maximum words number in each paper should be below 8,000 words, including references and illustrations. More information can be found at https://jit.ndhu.edu.tw/. Before submission authors should carefully read over the journal’s Author Guidelines, which are located at https://jit.ndhu.edu.tw/about/submissions#authorGuidelines.

Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at https://mc04.manuscriptcentral.com/internet-tech. When submitting papers, authors should specify that the manuscript is for Special Issue on “Intelligent Techniques for Efficient Resource Management in IoT Networks”. The manuscript template can be found at https://jit.ndhu.edu.tw/about/submissions#authorGuideline.

 

Important Dates

Submissions due: 25 April 2022

Preliminary notification: 29 July 2022

Revisions due: 15 October 2022

Final notification: 31 January 2023

Tentative Publication: the 2nd quarter of 2023

 

Guest Editors:

Dr. Gai-Ge Wang (Lead Guest Editor)

Department of Computer Science and Technology, Ocean University of China, China

Emails: wgg@ouc.edu.cn; gaigewang@ieee.org     

 

Dr. Xiao-Zhi Gao

School of Engineering Science, Lappeenranta University of Technology, Finland

Emails: xiao.z.gao@gmail.com; xiao-zhi.gao@uef.fi

 

Dr. Yan Pei

Computer Science Division, The University of Aizu, Japan

Email: peiyan@u-aizu.ac.jp