Abstract
Over the last decade, the Internet of Things (IoT) had impressive growth and became the new direction of information technology. Also, the energy consumption has reached distressing rates due to the large scale of digital context, a number of subscribers, and the number of smart devices.1 By capturing and processing sensitive information in human life, the IoT devices and cloud data centers are increasing energy consumption with a high carbon emission phenomenon. In the IoT ecosystem, intelligent applications require to select smart devices with low energy consumption and battery saving because all smart devices have limited battery life and may lead to disconnect data transmission. However, it is challenging to design a fully optimized framework due to the interconnected nature of smart devices with different technologies.
On the other hand, green energy-efficient computing has become a potential research focus in the IoT environment.2 Finally, energy consumption techniques are incoming a more advanced stage in the IoT communications. Also, green energy-efficient techniques can use on-demand protocols, machine learning, deep learning, and artificial intelligence methods to manage cost-effective and power-saving methods on smart devices in IoT communications. To this point, green energy-efficient computing solutions in IoT systems have emerging efforts and high potential to evaluate the critical points and safety conditions. The goal of this special issue is to highlight the latest research focusing on green energy-efficient computing solutions in IoT systems to address the challenges and critical points. We also aim to invite researchers to publish selected original articles presenting intelligent trends to solve new challenges of new problems. We are also interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research, and new future issues.
This special issue provides a new platform for researchers and scientific experts to share and analyze existing technical case studies to the field of energy-efficient computing solutions in the IoT environments. Our special issue has attracted 35 manuscripts. After a peer review process, 10 papers have been selected for publication in this special issue. Details of these selected papers are presented in the next section.