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The Internet of Things (IoT) provides robust services to connected sensors in a distributed manner, and maintains real-time communication using wireless standards. The smart network has offered many autonomous smart systems to collect information from remote nodes, and share it by exploring the network layer. Researchers have recently offered a variety of ways to increase the effectiveness of emerging applications using trustworthy relaying systems. However, there are still many issues with route reformulation due to frequent disconnections of mobile devices and resource limitations. Furthermore, most of the existing methods for IoT systems are unable to utilize network resources, which lowers the performance of green networks. Thus, providing a foolproof solution for the autonomous system with energy efficiency is a challenging task. Therefore, this paper presents an algorithm for the mobile network using fog computing to reduce network disconnectivity. Furthermore, using security services, the proposed algorithm efficiently explores the characteristics of the device, and avoids malicious traffic to drain the additional energy consumption of the network. The main aspects of the proposed algorithm are as follows: (i) using the adjustable transmission power, the proposed algorithm offers a fault-tolerant solution to transmit the aggregated data over the unpredictable wireless system; (ii) with the support of fog nodes, the data load is reduced among devices with the offering of a secured authentication scheme. Using simulations, the proposed algorithm is tested, and its significance is demonstrated against other related studies. [ABSTRACT FROM AUTHOR]

The environment and the economy are negatively impacted by conventional energy sources, such as coal, gasoline, and other fossil fuels. Pakistan's reliance on these resources has resulted in a catastrophic energy crisis. This has driven the government to make critical decisions such as early retail closures, power outages for the industrial sector, and an increase to two days a week vacations. Wind energy, accessible and affordable, will become a viable option for meeting Pakistan's present and future energy demands. Approximately 3% of Pakistan's land can produce nearly 132 GW of power with an installed capacity of 5 MW per km2. In this study, four zones (Karachi, Thatta, Badin, and Jamshoro) in Sindh province are assessed for the feasibility of wind energy generation. The installed capacity, generator types, and detailed specifications are provided for each zone. Moreover, the wind mapping of Pakistan is presented considering the four potential zones. The zones are analyzed using annual wind speed and power output considering wind data measured at 50 m height over one year. The higher mean speed is recorded at Jamshoro compared to other zones. The analysis indicates that all four sites are suitable for large-scale wind power generation due to their energy potential. [ABSTRACT FROM AUTHOR]

Capacitive deionization (CDI) is an alternative desalination technique for low-to-moderate salinity feeds. Despite significant advances in electrode material design, CDI's thermodynamic energy efficiency (TEE) remains low and has become important in assessing feasibility for real-world applications. Innovative cell configurations are key to improving TEE ; however, their performance trends need to be contextualized, given the scattered information that can be challenging to compare. This study evaluates various desalination cells, including conventional CDI, single- and multi-channel asymmetric CDI, and multi-channel battery deionization (BDI). Using MoS 2 as a representative intercalating material, the position of active sites on composite electrodes was first optimized. Hydrothermally-grown MoS 2 on carbon nanofibers exhibited enhanced charge transfer compared to MoS 2 embedded in nanofibers. Among the tested configurations using 20 mM NaCl in single-pass mode and 50% water recovery, BDI demonstrated over 3.7 times higher TEE than asymmetric setups and 50 times higher than typical CDI while maintaining consistent desalination performance. BDI benefited from the combined effects of electrosorption/intercalation and ion exchange membranes in symmetric conformation, effectively utilizing charge. These findings provide insights into process engineering for improved electrochemical desalination and the enhancement of ion intercalation-based desalination configurations. • The performance of intercalating electrodes was systematically evaluated. • The variations in intercalating materials by fabrication route were investigated. • Study provides insights for maximizing electrochemical desalination performance. • Study guides the development of various BDIs using faradaic materials. [ABSTRACT FROM AUTHOR]

The smart energy consumption of any household, maintaining the thermal comfort level of the occupant, is of great interest. Sensors and Internet-of-Things (IoT)-based intelligent hardware setups control the home appliances intelligently and ensure smart energy consumption, considering environment parameters. However, the effects of environment-driven consumer body dynamics on energy consumption, considering consumer comfort level, need to be addressed. Therefore, an Energy Management System (EMS) is modeled, designed, and analyzed with hybrid inputs, namely environmental perturbations, and consumer body biological shifts, such as blood flows in skin, fat, muscle, and core layers (affecting consumer comfort through blood-driven-sensations). In this regard, our work incorporates 69 Multi-Node (MN) Stolwijik's consumer body interfaced with an indoor (room) electrical system capable of mutual interactions exchange from room environmental parameters and consumer body dynamics. The mutual energy transactions are controlled with classical PID and Adaptive Neuro-Fuzzy-Type II (NF-II) systems inside the room dimensions. Further, consumer comfort, room environment, and energy consumption relations with bidirectional control are demonstrated, analyzed, and tested in MATLAB/Simulink to reduce energy consumption and energy cost. Finally, six different cases are considered in simulation settings and for performance validation, one case is validated as real-time hardware experimentation. [ABSTRACT FROM AUTHOR]

The losses in the power system vary the gap between energy supply and demand. Among these losses, the distribution system has major contributions compared to the transmission system. This paper thoroughly examines the PESCO distribution losses and implements a practical approach that forties in the loss's minimization. Using the bifurcation and restoration strategies, the PESCO distribution system can be well-organized and an effective system can be designed. The proposed approach also helps in estimating the entailed capital investments and the rate of return over time. Both the HT (High Tension) and LT (Low Tension) distribution systems are considered for observation and the proposed systems are endorsed. Computer-based software, such as ELR (Energy Loss Reduction) and CADPAW (Computer-Aided Distribution Planning Work) is exploited to measure the results of both the proposed and existing system. After the restoration of a particular system, recommendations are concluded. The proposed approach applies to any existing power system. [ABSTRACT FROM AUTHOR]

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As compared to fuel and gasoline type vehicles, the EV has a limited driving range and needs to recharge its battery frequently during long journeys. Hence, with plug-in charging services one major concern is the long duration of battery recharging. In this paper, we employ heterogeneous BS (Battery Switching) technology to provide an alternative charging option to minimize the charging duration of EV. Furthermore, enabling BS reservation in a centralized manner for mobile EVs, load balancing algorithm and optimal selection of Battery Switching Station (BSS) across the network are proposed. In addition, we suggest a scheduling technique for depleted batteries to recharge effectively in BSS to minimize power loss and queuing time at selected BSS. We have conducted a performance evaluation by comparing the proposed scheme with other benchmarks, in terms of average trip duration, total trip energy consumption, etc. Finally, it is proven that the battery stock is managed across the network efficiently through the proposed scheme. [ABSTRACT FROM AUTHOR]

Fossil fuels account for more than 80% of the world's energy consumption. Constituents of the atmosphere have changed perceptibly due to the increased use of fossil fuels. Therefore, many researchers have tried to relate their effect on society. In Pakistan, fossil fuel consumption and its CO2-based emission factor have been significantly correlated to economic growth. However, it needs further attention to study the adverse effects of fossil fuels. This study is an attempt to assess the cost of fossil fuels to society. Damages caused by fossil fuels are evaluated for the years of 2005–2009, using local pollution factors based on CO2 emission. Results show that the market price of fossil fuels increases after adding up the cost of damage caused by the final use of the fuel. People pay a huge amount of PKR 133 billion per year for taxes, health services, insurance premiums, and low living standards. Accordingly, it is suggested that we must shift from fossil fuels to other alternative clean types of energy. [ABSTRACT FROM AUTHOR]

Internet of things have emerged enough due to its applications in a wide range of fields such as governance, industry, healthcare, and smart environments (home, smart, cities, and so on). Internet of things–based networks connect smart devices ubiquitously. In such scenario, the role of wireless sensor networks becomes vital in order to enhance the ubiquity of the Internet of things devices with lower cost and easy deployment. The sensor nodes are limited in terms of energy storage, processing, and data storage capabilities, while their radio frequencies are very sensitive to noise and interference. These factors consequently threaten the energy consumption, lifetime, and throughput of network. One way to cope with energy consumption issue is energy harvesting techniques used in wireless sensor network–based Internet of things. However, some recent studies addressed the problems of clustering and routing in energy harvesting wireless sensor networks which either concentrate on energy efficiency or quality of service. There is a need of an adequate approach that can perform efficiently in terms of energy utilization as well as to ensure the quality of service. In this article, a novel protocol named energy-efficient multi-attribute-based clustering scheme (E2-MACH) is proposed which addresses the energy efficiency and communication reliability. It uses selection criteria of reliable cluster head based on a weighted function defined by multiple attributes such as link statistics, neighborhood density, current residual energy, and the rate of energy harvesting of nodes. The consideration of such parameters in cluster head selection helps to preserve the node's energy and reduce its consumption by sending data over links possessing better signal-to-noise ratio and hence ensure minimum packet loss. The minimized packet loss ratio contributes toward enhanced network throughput, energy consumption, and lifetime with better service availability for Internet of things applications. A set of experiments using network simulator 2 revealed that our proposed approach outperforms the state-of-the-art low-energy adaptive clustering hierarchy and other recent protocols in terms of first-node death, overall energy consumption, and network throughput. [ABSTRACT FROM AUTHOR]

Information-centric networking is the developing model envisioned by an increasing body of the data communication research community, which shifts the current network paradigm from host centric to data centric, well-known to information-centric networking (ICN). Further, the ICN adopts different types of architectures to extend the growth of the Internet infrastructure, e.g., name-based routing and in-network caching. As a result, the data can be easily routed and accessed within the network. However, when the producer generates contents for authentic consumers, then it is necessary for him/her to have a technique for content confidentiality, privacy, and access control. To provide the previously mentioned services, this paper presents a certificateless proxy reencryption scheme (CPRES) based on the hyperelliptic curve for access control in the content-centric network (CCN). Using certificateless PRE, the power of the key generation center (KGC) is limited to only the generation of partial keys to secure the access to the content. With the help of these partial keys, the producer further calculates keys for encryption and reencryption process. The simulation results show that the proposed scheme provides secure access to content during end-to-end communication. Moreover, the proposed CPRES scheme outperforms in terms of low computational energy and efficient utilization of communication bandwidth. [ABSTRACT FROM AUTHOR]

Wireless Body Area Networks (WBANs) is a revolutionary achievement in the field of health services. The field is envisioned to play an important role in medical, psychological, and even in non-medical applications. Different routing protocols are being designed in WBAN to enhance its performance, focusing on delay, energy efficiency, throughput, and network lifetime. Line-of-sight (LoS) and Non-Line-of-Sight (NLoS) communications and clustering are the least focused areas in the literature. This paper presents a routing protocol called Dual Sink approach using Clustering in Body Area Network (DSCB) which is more reliable in terms of network stability, and energy efficient in comparison to its counterparts. This protocol enhances network life-time by introducing the concept of clustering while using two sink nodes. The proposed scheme is compared with existing protocols named as SIMPLE and DARE. The cost function is established for selection of forwarder node, based on nodal distance from the sink, residual energy, and transmission power. Simulation results depict that the proposed protocol achieves significant performance improvement in network throughput by attaining 55% and 22% more efficient results compared to SIMPLE and DARE respectively. Furthermore, the results show improved performance of DSCB protocol, in terms of network stability and end-to-end delay performance metrics. [ABSTRACT FROM AUTHOR]

Underwater wireless sensor networks are a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in the area of underwater wireless sensor networks have also been discussed. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. This study reviews the ML applications in the life cycle stages of biofuels, i.e., soil, feedstock, production, consumption, and emissions. ML applications in the soil stage were mostly used for satellite images of land to estimate the yield of biofuels or a suitability analysis of agricultural land. The existing literature have reported on the assessment of rheological properties of the feedstocks and their effect on the quality of biofuels. The ML applications in the production stage include estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage include analysis of engine performance and estimation of emissions temperature and composition. This study identifies the following trends: the most dominant ML method, the stage of life cycle getting the most usage of ML, the type of data used for the development of the ML-based models, and the frequently used input and output variables for each stage. The findings of this article would be beneficial for academia and industry-related professionals involved in model development in different stages of biofuel's life cycle. [ABSTRACT FROM AUTHOR]

A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewards. However, the management and control through the third party pose a significant threat to the security and privacy of consumers'/producers' (participants) profiles. The energy transactions between participants involving central authority utilize users' time, money, and impose a computational burden over the central controlling authority. The Blockchain-based decentralized energy transaction concept, bypassing the central authority, is proposed in Smart Grid (SG) by researchers. Blockchain technology braces the concept of Peer-to-Peer (P2P) energy transactions. This work encompasses the SolarCoin-based digital currency blockchain model for SG incorporating RE. Energy transactions from Prosumer (P) to Prosumer, Energy District to Energy District, and Energy District to SG are thoroughly investigated and analyzed in this work. A robust demand-side optimized model is proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to maximize Prosumer Energy Surplus (PES), Grid revenue (GR), percentage energy transactions accomplished, and decreased Prosumer Energy Cost (PEC). Real-time averaged energy data of Australia are employed, and a piece-wise energy price mechanism is implemented in this work. The graphical analysis and tabular statistics manifest the efficacy of the proposed model. [ABSTRACT FROM AUTHOR]

Ternary content-addressable memories (TCAMs) are used to design high-speed search engines. TCAM is implemented on application-specific integrated circuit (native TCAMs) and field-programmable gate array (FPGA) (static random-access memory (SRAM)-based TCAMs) platforms but both have the drawback of high power consumption. This paper presents a pre-classifier-based architecture for an energy-efficient SRAM-based TCAM. The first classification stage divides the TCAM table into several sub-tables of balanced size. The second SRAM-based implementation stage maps each of the resultant TCAM sub-tables to a separate row of configured SRAM blocks in the architecture. The proposed architecture selectively activates at most one row of SRAM blocks for each incoming TCAM word. Compared with the existing SRAM-based TCAM designs on FPGAs, the proposed design consumes significantly reduced energy as it activates a part of SRAM memory used for lookup rather than the entire SRAM memory as in the previous schemes. We implemented the proposed approach sample designs of size 512 × 36 on Xilinx Virtex-6 FPGA. The experimental results showed that the proposed design achieved at least three times lower power consumption per performance than other SRAM-based TCAM architectures. [ABSTRACT FROM AUTHOR]