Special Issue "Green IoT Networks using Machine Learning, Deep Learning Models"

Submission Deadline: 31 May 2021
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Guest Editors
Dr. Thippa Reddy Gadekallu, Vellore Institute of Technology, India.
Dr. Mamoun Alazab, Charles Darwin University, Australia.
Dr. Praveen Kumar Reddy M, Vellore Institute of Technology, India.

Summary

A green IoT energy-aware network plays an important role in sensing technology. IoT growth influences many applications such as e-health care, smart cities, vehicle systems, and industrial engineering in today's era. Some of the compromise solutions occur during the design and development of IoT-based applications such as security, resources, routing, node deployment, etc. The rapid increase in sensor nodes results in increased power consumption. Therefore, the reduction of environmental impact in green media networks is a crucial challenge for academic and industrial researchers. One of the IoT-based applications' problems is improving power efficiency and network longevity by miniature size, limited battery life, and dynamic motion of the sensor nodes in industrial applications. Energy optimization and resource management in these networks remain a challenge, Therefore for efficient power management and necessary optimization for IoT applications, Artificial Intelligence (AI), Deep Learning (DL) and other Neural Network (NN) based approaches will come up as a solution for green communication.

In addition, recent literature covered machine learning; deep learning algorithms can provide energy efficiency solutions, predictions on batteries, network monitoring, etc. This special issue seeks submissions of high-quality and unpublished articles to address the technical problems and challenges of green communications networks. In particular, we seek submissions that efficiently integrate new AI, DL approaches, focusing on the assessment of IoT ecosystem performance across existing green communication solutions. Theoretical and experimental studies for such scenarios are encouraged.

We solicit papers covering various topics of interest that include, but are not limited to, the following.

• Resource optimization in IoT applications.

• Machine learning approaches for green IoT.

• Quality of service in smart green communication networks for the IoT ecosystem.

• Architectures and models for smart green communication networks for IoT.

• Green communication network designs and implementations for IoT ecosystem.

• Innovative green communications technologies and protocols suitably designed for the IoT.

• Smart energy harvesting/charging and power management techniques using ML techniques.

• Energy-efficient sensing techniques.

• Experimental results and test-beds for smart green computing systems for IoT network models.


Keywords
Internet of Things, Energy Efficiency, Green Internet of Things, Machine Learning, Deep Learning

Published Papers
  • Energy-Efficient Transmission Range Optimization Model for WSN-Based Internet of Things
  • Abstract With the explosive advancements in wireless communications and digital electronics, some tiny devices, sensors, became a part of our daily life in numerous fields. Wireless sensor networks (WSNs) is composed of tiny sensor devices. WSNs have emerged as a key technology enabling the realization of the Internet of Things (IoT). In particular, the sensor-based revolution of WSN-based IoT has led to considerable technological growth in nearly all circles of our life such as smart cities, smart homes, smart healthcare, security applications, environmental monitoring, etc. However, the limitations of energy, communication range, and computational resources are bottlenecks to the widespread applications… More
  •   Views:80       Downloads:56        Download PDF

  • A Novel Green IoT-Based Pay-As-You-Go Smart Parking System
  • Abstract The better management of resources and the potential improvement in traffic congestion via reducing the orbiting time for parking spaces is crucial in a smart city, particularly those with an uneven correlation between the increase in vehicles and infrastructure. This paper proposes and analyses a novel green IoT-based Pay-As-You-Go (PAYG) smart parking system by utilizing unused garage parking spaces. The article also presents an intelligent system that offers the most favorable prices to its users by matching private garages’ pricing portfolio with a garage’s current demand. Malta, the world’s fourth-most densely populated country, is considered as a case of a… More
  •   Views:44       Downloads:48        Download PDF

  • Position Vectors Based Efficient Indoor Positioning System
  • Abstract With the advent and advancements in the wireless technologies, Wi-Fi fingerprinting-based Indoor Positioning System (IPS) has become one of the most promising solutions for localization in indoor environments. Unlike the outdoor environment, the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efficient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things (IoTs) and green computing. In this paper, we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors. Initially, in the database development phase, Motley Kennan propagation… More
  •   Views:225       Downloads:113        Download PDF

  • Green5G: Enhancing Capacity and Coverage in Device-to-Device Communication
  • Abstract With the popularity of green computing and the huge usage of networks, there is an acute need for expansion of the 5G network. 5G is used where energy efficiency is the highest priority, and it can play a pinnacle role in helping every industry to hit sustainability. While in the 5G network, conventional performance guides, such as network capacity and coverage are still major issues and need improvements. Device to Device communication (D2D) communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques. The issue of energy utilization in the IoT based… More
  •   Views:470       Downloads:124        Download PDF