The dramatic recent increase of the smart Internet of Everything (IoE) in Industry 4.0 has significantly\nincreased energy consumption, carbon emissions, and global warming. IoE applications in Industry\n4.0 face many challenges, including energy efficiency, heterogeneity, security, interoperability, and\ncentralization. Therefore, Industry 4.0 in Beyond the Sixth-Generation (6G) networks demands moving\nto sustainable, green IoE and identifying efficient and emerging technologies to overcome sustainability\nchallenges. Many advanced technologies and strategies efficiently solve issues by enhancing\nconnectivity, interoperability, security, decentralization, and reliability. Greening IoE is a promising\napproach that focuses on improving energy efficiency, providing a high Quality of Service (QoS), and\nreducing carbon emissions to enhance the quality of life at a low cost. This survey provides a comprehensive\noverview of how advanced technologies can contribute to green IoE in the 6G network of\nIndustry 4.0 applications. This survey provides a comprehensive overview of advanced technologies,\nincluding Blockchain, Digital Twins (DTs), Unmanned Aerial Vehicles (UAVs, a.k.a. drones), and\nMachine Learning (ML), to improve connectivity, QoS, and energy efficiency for green IoE in 6G\nnetworks. We evaluate the capability of each technology in greening IoE in Industry 4.0 applications\nand analyze the challenges and opportunities to make IoE greener using the discussed technologies.

Abstract The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must be environmentally-friendly, hence require a move towards green IoT. Green IoT leads to an eco-friendly environment, which is more sustainable for smart cities. Therefore, it is essential to address the techniques and strategies for reducing pollution hazards, traffic waste, resource usage, energy consumption, providing public safety, life quality, and sustaining the environment and cost management. This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly. Furthermore, the survey focuses on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities. Finally, we discuss challenges and opportunities for future research in smart city applications.

Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a significant interest in supporting many applications such as surveillance, agriculture, communication, transportation, pollution monitoring, disaster management, public safety, healthcare, and environmental preservation. Industry 4.0 applications are conceived of intelligent things that can automatically and collaboratively improve beyond 5G (B5G). Therefore, the Internet of Things (IoT) is required to ensure collaboration between the vast multitude of things efficiently anywhere in real-world applications that are monitored in real-time. However, many IoT devices consume a significant amount of energy when transmitting the collected data from surrounding environments. Due to a drone's capability to fly closer to IoT, UAV technology plays a vital role in greening IoT by transmitting collected data to achieve a sustainable, reliable, eco-friendly Industry 4.0. This survey presents an overview of the techniques and strategies proposed recently to achieve green IoT using UAVs infrastructure for a reliable and sustainable smart world. This survey is different from other attempts in terms of concept, focus, and discussion. Finally, various use cases, challenges, and opportunities regarding green IoT using UAVs are presented.

The Virtual Design Advisor (VDA) has addressed the problem of optimizing the performance of Database Management System (DBMS) instances running on virtual machines that share a common physical machine pool. In this work, the search algorithm in the optimization module of the VDA is improved. The particle swarm optimization (PSO) heuristic is used as a controller of the greedy heuristic algorithm to reduce trapping into local optima. Our proposed algorithm, called Greedy Particle Swarm Optimization (GPSO), was evaluated using prototype experiments on TPC-H benchmark queries against PostgreSQL instances in Xen virtualization environment. Our results show that the GPSO algorithm required more computation but in many test cases have succeeded to escape local optima and reduced the cost as compared to the greedy algorithm alone.