Green energy‐efficient computing solutions in Internet of Things communications

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. This special issue has attracted many submissions and only 10 papers were accepted. Some of the accepted papers have appeared in regular issues of the journal due to the fact that the journal has moved to a new submission site, which made it difficult for the journal's publication staff to recognize these as special issue papers. These include the papers with a brief description given below: The paper entitled “A Novel Dynamic Clustering Approach for Energy Hole Mitigation in Internet of Things-Based Wireless Sensor Network” by Dogra et al3 provides a dynamic clustering methodology for enhancing energy consumption of wireless devices in IoT environments. The paper entitled “Swarm Intelligence-Based Optimal Device Deployment in Heterogeneous Internet Of Things Networks for Wind Farm Application” by Sarobin et al4 introduces a swarm intelligence technique known as particle swarm optimization (PSO) to solve the connectivity issue and to minimize the cost of devices deployment. In “Research and Application of Node Fuzzy Identification and Localization in Wireless Sensor Networks,” by Wu and Wu5 present a fuzzy controller to fuzzify the input information of sensor nodes in ioT. The paper entitled “Data Denoising and Compression of Intelligent Transportation System Based on Two-dimensional Discrete Wavelet Transform” by Dou and Wang6 introduces a construction of two-dimensional discrete wavelet transform, including separation calculation method and nonseparation calculation method, and proposes the construction of time–space data model of intelligent transportation system, including support vector machine (SVM), K-nearest neighbor algorithm, and deep neural network algorithm. In “Scale-Free Topology Security Mechanism of Wireless Sensor Network Against Cascade Failure,” by Gao et al7 present a secure multipath routing algorithm for wireless sensor networks (WSNs) based on scale-free topology in IoT. In “A Multi-Objective Distance Vector-Hop Localization Algorithm Based on Differential Evolution Quantum Particle Swarm Optimization,” Han et al8 introduce a multiobjective DV-HOP localization algorithm based on differential evolution quantum particle swarm optimization (DQPSO-DV-HOP). In “A Two-Level Clustering Mechanism for Energy Enhancement in IoT-based Wireless Sensor Networks,” Bany Salameh et al9 provide a novel clustering mechanism with the objective of extending network lifetime through load balancing in WSNs. Three of these accepted papers were identified as part of the special issue. These include: The paper entitled “TRACTOR: Traffic-Aware and Power-Efficient Virtual Machine Placement in Edge-Cloud Data Centers Using Artificial Bee Colony Optimization” by Nabavi et al10 proposed a new many-objective virtual machine (VM) placement. They reported that the proposed method is able to reduce energy consumption by 3.5% while decreasing network traffic. In “Fault Detection of Energy-Aware Grid Systems in Big Data Environment,” Fan11 presents a new concept of a fault detector to precisely control the cost of message detection and the state distribution of the detection result and the time of message delay. Finally, in “Energy Aware Cloud-Edge Service Placement Approaches in the Internet of Things Communications,” Heng et al12 provide a technical analysis on the cloud-edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches that need additional consideration to progress more efficient and effective placement strategies in IoT environments. We are extremely grateful to Prof. Mohammad Obaidat, the Editor-in-Chief of the International Journal of Communication Systems (IJCS), and reviewers and the staff of IJCS for having supported this special issue and having helped to select high-quality papers. This outstanding support allowed for producing a valuable special issue that provides a state-of-the-art overview on the existing challenges and opportunities of the energy-aware computing and communication strategies in the IoT.