Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption, weather data, and power generation for detecting and predicting data mining in the centralized parallel processing and diagnosis. Due to these constraints, data management has become a critical research consideration and bottleneck. To cope with these constraints, cloud computing-based methodologies have been introduced for managing data efficiently in power management systems. This paper reviews the concept of cloud computing architecture that can meet the multi-level real-time requirements to improve monitoring and performance which is designed for different application scenarios for power system monitoring. Then, cloud computing solutions are discussed under the background of big data, and emerging parallel programming models such as Hadoop, Spark, and Storm are briefly described to analyze the advancement, constraints, and innovations. The key performance metrics of cloud computing applications such as core data sampling, modeling, and analyzing the competitiveness of big data was modeled by applying related hypotheses. Finally, it introduces a new design concept with cloud computing and eventually some recommendations focusing on cloud computing infrastructure, and methods for managing real-time big data in the power management system that solve the data mining challenges.

Radio frequency energy harvesting (RF-EH) is a potential technology via the generation of electromagnetic waves. This advanced technology offers the supply of wireless power that is applicable for battery-free devices, which makes it a prospective alternative energy source for future applications. In addition to the dynamic energy recharging of wireless devices and a wide range of environmentally friendly energy source options, the emergence of the RF-EH technology is advantageous in facilitating various applications that require quality of service. This review highlights the abundant source of RF-EH from the surroundings sources, including nearby mobile phones, Wi-Fi, wireless local area network, broadcast television signal or DTS, and FM/AM radio signals. In contrast, the energy is captured by a receiving antenna and rectified into a working direct current voltage. This review also summarizes the power of RF-EH technology, which would provide a guideline for developing RF-EH units. The energy harvesting circuits depend on cutting-edge electrical technology to achieve significant efficiency, given that they are built to perform with considerably small current and voltage. Hence, the review includes a thorough analysis and discussion of various RF designs and their pros and cons. Finally, the latest applications of RF-EH are presented.

The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

In this paper, a dual-band metamaterial absorber (MMA) ring with a mirror reflexed C-shape is introduced for X and Ku band sensing applications. The proposed metamaterial consists of two square ring resonators and a mirror reflexed C-shape, which reveals two distinctive absorption bands in the electromagnetic wave spectrum. The mechanism of the two-band absorber particularly demonstrates two resonance frequencies and absorption was analyzed using a quasi-TEM field distribution. The absorption can be tunable by changing the size of the metallic ring in the frequency spectrum. Design and analysis of the proposed meta-absorber was performed using the finite-integration technique (FIT)-based CST microwave studio simulation software. Two specific absorption peaks value of 99.6% and 99.14% are achieved at 13.78 GHz and 15.3 GHz, respectively. The absorption results have been measured and compared with computational results. The proposed dual-band absorber has potential applications in sensing techniques for satellite communication and radar systems.

Flying Ad-Hoc Network (FANET) is a set of Unmanned Aerial Vehicles (UAVs) inter-connected wirelessly. FANETs self-organize and provide low-cost, adaptable, and simple-to-implement flying nodes, enabling them to complete complicated tasks more quickly and collectively. The high mobility of nodes and the highly dynamic topology pose challenges to communication design, particularly when creating a routing protocol for UAV networks; this has inspired researchers to contribute and develop this technology. Hierarchical routing technique known as clustering is necessary to offer scalability, survivability, and distribute payload among UAVs to maintain the performance. This study has proposed a comprehensive survey of the cluster-based routing protocols (CBRPs) in terms of their strengths, weaknesses, specific applications, method, number of nodes, and future improvements for serving FANETs. Moreover, 21 CBRPs based FANETs were reviewed in terms of their topology, challenges, scalability, characteristics, clustering strategy, outstanding features, cluster head (CH) selection, routing metrics, and performance measures. In addition, open issues that need to be addressed in future studies in the field of routing protocols for UAV networks were also debated.

Massive multiple-input multiple-output (mMIMO) is a wireless access technique that has been studied and investigated in response to the worldwide bandwidth demand in the wireless communication sector (MIMO). Massive MIMO, which brings together antennas at the transmitter and receiver to deliver excellent spectral and energy efficiency with comparatively simple processing, is one of the main enabling technologies for the upcoming generation of networks. To actualize diverse applications of the intelligent sensing system, it is essential for the successful deployment of 5G—and beyond—networks to gain a better understanding of the massive MIMO system and address its underlying problems. The recent huge MIMO systems are highlighted in this paper’s thorough analysis of the essential enabling technologies needed for sub-6 GHz 5G networks. This article covers most of the critical issues with mMIMO antenna systems including pilot realized gain, isolation, ECC, efficiency, and bandwidth. In this study, two types of massive 5G MIMO antennas are presented. These types are used depending on the applications at sub-6 GHz bands. The first type of massive MIMO antennas is designed for base station applications, whereas the most recent structures of 5G base station antennas that support massive MIMO are introduced. The second type is constructed for smartphone applications, where several compact antennas designed in literature that can support massive MIMO technology are studied and summarized. As a result, mMIMO antennas are considered as good candidates for 5G systems.