Multi-Hop Clustering and Routing Protocol Based on Enhanced Snake Optimizer and Golden Jackal Optimization in WSNs

A collection of smaller, less expensive sensor nodes called wireless sensor networks (WSNs) use their sensing range to gather environmental data. Data are sent in a multi-hop manner from the sensing node to the base station (BS). The bulk of these sensor nodes run on batteries, which makes replacement and maintenance somewhat difficult. Preserving the network's energy efficiency is essential to its longevity. In this study, we propose an energy-efficient multi-hop routing protocol called ESO-GJO, which combines the enhanced Snake Optimizer (SO) and Golden Jackal Optimization (GJO). The ESO-GJO method first applies the traditional SO algorithm and then integrates the Brownian motion function in the exploitation stage. The process then integrates multiple parameters, including the energy consumption of the cluster head (CH), node degree of CH, and distance between node and BS to create a fitness function that is used to choose a group of appropriate CHs. Lastly, a multi-hop routing path between CH and BS is created using the GJO optimization technique. According to simulation results, the suggested scheme outperforms LSA, LEACH-IACA, and LEACH-ANT in terms of lowering network energy consumption and extending network lifetime.

Energy Consumption Analysis for Continuous Phase Modulation in Smart-Grid Internet of Things of beyond 5G

Wireless sensor network (WSN) underpinning the smart-grid Internet of Things (SG-IoT) has been a popular research topic in recent years due to its great potential for enabling a wide range of important applications. However, the energy consumption (EC) characteristic of sensor nodes is a key factor that affects the operational performance (e.g., lifetime of sensors) and the total cost of ownership of WSNs. In this paper, to find the modulation techniques suitable for WSNs, we investigate the EC characteristic of continuous phase modulation (CPM), which is an attractive modulation scheme candidate for WSNs because of its constant envelope property. We first develop an EC model for the sensor nodes of WSNs by considering the circuits and a typical communication protocol that relies on automatic repeat request (ARQ)-based retransmissions to ensure successful data delivery. Then, we use this model to analyze the EC characteristic of CPM under various configurations of modulation parameters. Furthermore, we compare the EC characteristic of CPM with that of other representative modulation schemes, such as offset quadrature phase-shift keying (OQPSK) and quadrature amplitude modulation (QAM), which are commonly used in communication protocols of WSNs. Our analysis and simulation results provide insights into the EC characteristics of multiple modulation schemes in the context of WSNs; thus, they are beneficial for designing energy-efficient SG-IoT in the beyond-5G (B5G) and the 6G era.

Enhanced Pelican Optimization Algorithm for Cluster Head Selection in Heterogeneous Wireless Sensor Networks

In the research of heterogeneous wireless sensor networks, clustering is one of the most commonly used energy-saving methods. However, existing clustering methods face challenges when applied to heterogeneous wireless sensor networks, such as energy balance, node heterogeneity, algorithm efficiency, and more. Among these challenges, a well-designed clustering approach can lead to extended node lifetimes. Efficient selection of cluster heads is crucial for achieving optimal clustering. In this paper, we propose an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS) to address these issues and enhance cluster head selection for optimal clustering. This method combines the Levy flight process with the traditional POA algorithm, which not only improves the optimization level of the algorithm, but also ensures the selection of the optimal cluster head. The logistic-sine chaotic mapping method is used in the population initialization, and the appropriate cluster head is selected through the new fitness function. Finally, we utilized MATLAB to simulate 100 sensor nodes within a configured area of 100 × 100 m2. These nodes were categorized into four heterogeneous scenarios: m=0,α=0, m=0.1,α=2, m=0.2,α=3, and m=0.3,α=1.5. We conducted verification for four aspects: total residual energy, network survival time, number of surviving nodes, and network throughput, across all protocols. Extensive experimental research ultimately indicates that the EPOA-CHS method outperforms the SEP, DEEC, Z-SEP, and PSO-ECSM protocols in these aspects.

Thin-Film Solar Energy Absorber Structure for Window Coatings for Self-Sufficient Futuristic Buildings

Energy-efficient buildings are a new demand in the current era. In this paper, we present a novel metamaterial design aimed at achieving efficient solar energy absorption through a periodic MMA structure composed of a W-GaAs-W. The proposed structure can be implemented as the window coating and in turn it can absorb the incident solar energy and, then, this energy can be used to fulfill the energy demand of the building. Our results reveal significant improvements, achieving an average absorptance of 96.94% in the spectral range. Furthermore, we explore the influence of the angle of incidence on the absorber's response, demonstrating its angle-insensitive behavior with high absorption levels (above 90%) for incidence angles up to 60° for TE polarization and 40° for TM polarization. The proposed structure presents a significant advancement in metamaterial-based solar energy absorption. By exploring the effects of structural parameters and incident angles, we have demonstrated the optimized version of our proposed absorber. The potential applications of this metamaterial absorber in self-sufficient futuristic building technologies and self-sustaining systems offer new opportunities for harnessing solar energy and are a valuable contribution to future developments in the fields of metamaterials and renewable energy.

Energy-Efficient Opportunistic Routing Algorithm for Post-Disaster Mine Internet of Things Networks

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables a user to monitor and control the safety of an affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in a low level of network reliability for the post-disaster MIoT. To improve transmission reliability and reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) approach for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in the CFS are prioritized based on a routing quality evaluation, which takes the local attributes of the nodes, such as the directional angle, transmission distance, and residual energy, into consideration. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results verify that the proposed DEOR approach outperforms the ORR, OBRN and ECSOR methods in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

Energy-Efficient and Variability-Resilient 11T SRAM Design Using Data-Aware Read-Write Assist (DARWA) Technique for Low-Power Applications

The need for power-efficient devices, such as smart sensor nodes, mobile devices, and portable digital gadgets, is markedly increasing and these devices are becoming commonly used in daily life. These devices continue to demand an energy-efficient cache memory designed on Static Random-Access Memory (SRAM) with enhanced speed, performance, and stability to perform on-chip data processing and faster computations. This paper presents an energy-efficient and variability-resilient 11T (E²VR11T) SRAM cell, which is designed with a novel Data-Aware Read-Write Assist (DARWA) technique. The E²VR11T cell comprises 11 transistors and operates with single-ended read and dynamic differential write circuits. The simulated results in a 45 nm CMOS technology exhibit 71.63% and 58.77% lower read energy than ST9T and LP10T and lower write energies of 28.25% and 51.79% against S8T and LP10T cells, respectively. The leakage power is reduced by 56.32% and 40.90% compared to ST9T and LP10T cells. The read static noise margin (RSNM) is improved by 1.94× and 0.18×, while the write noise margin (WNM) is improved by 19.57% and 8.70% against C6T and S8T cells. The variability investigation using the Monte Carlo simulation on 5000 samples highly validates the robustness and variability resilience of the proposed cell. The improved overall performance of the proposed E²VR11T cell makes it suitable for low-power applications.

Energy-Aware IoT-Based Method for a Hybrid On-Wrist Fall Detection System Using a Supervised Dictionary Learning Technique

In recent decades, falls have posed multiple critical health issues, especially for the older population, with their emerging growth. Recent research has shown that a wrist-based fall detection system offers an accessory-like comfortable solution for Internet of Things (IoT)-based monitoring. Nevertheless, an autonomous device for anywhere-anytime may present an energy consumption concern. Hence, this paper proposes a novel energy-aware IoT-based architecture for Message Queuing Telemetry Transport (MQTT)-based gateway-less monitoring for wearable fall detection. Accordingly, a hybrid double prediction technique based on Supervised Dictionary Learning was implemented to reinforce the detection efficiency of our previous works. A controlled dataset was collected for training (offline), while a real set of measurements of the proposed system was used for validation (online). It achieved a noteworthy offline and online detection performance of 99.8% and 91%, respectively, overpassing most of the related works using only an accelerometer. In the worst case, the system showed a battery consumption optimization by a minimum of 27.32 working hours, significantly higher than other research prototypes. The approach presented here proves to be promising for real applications, which require a reliable and long-term anywhere-anytime solution.

Evaluation of Growth Responses of Lettuce and Energy Efficiency of the Substrate and Smart Hydroponics Cropping System

Smart sensing devices enabled hydroponics, a concept of vertical farming that involves soilless technology that increases green area. Although the cultivation medium is water, hydroponic cultivation uses 13 ± 10 times less water and gives 10 ± 5 times better quality products compared with those obtained through the substrate cultivation medium. The use of smart sensing devices helps in continuous real-time monitoring of the nutrient requirements and the environmental conditions required by the crop selected for cultivation. This, in turn, helps in enhanced year-round agricultural production. In this study, lettuce, a leafy crop, is cultivated with the Nutrient Film Technique (NFT) setup of hydroponics, and the growth results are compared with cultivation in a substrate medium. The leaf growth was analyzed in terms of cultivation cycle, leaf length, leaf perimeter, and leaf count in both cultivation methods, where hydroponics outperformed substrate cultivation. The results of the 'AquaCrop simulator also showed similar results, not only qualitatively and quantitatively, but also in terms of sustainable growth and year-round production. The energy consumption of both the cultivation methods is compared, and it is found that hydroponics consumes 70 ± 11 times more energy compared to substrate cultivation. Finally, it is concluded that smart sensing devices form the backbone of precision agriculture, thereby multiplying crop yield by real-time monitoring of the agronomical variables.

DCP-SLAM: Distributed Collaborative Partial Swarm SLAM for Efficient Navigation of Autonomous Robots

Collaborative robots represent an evolution in the field of swarm robotics that is pervasive in modern industrial undertakings from manufacturing to exploration. Though there has been much work on path planning for autonomous robots employing floor plans, energy-efficient navigation of autonomous robots in unknown environments is gaining traction. This work presents a novel methodology of low-overhead collaborative sensing, run-time mapping and localization, and navigation for robot swarms. The aim is to optimize energy consumption for the swarm as a whole rather than individual robots. An energy- and information-aware management algorithm is proposed to optimize the time and energy required for a swarm of autonomous robots to move from a launch area to the predefined destination. This is achieved by modifying the classical Partial Swarm SLAM technique, whereby sections of objects discovered by different members of the swarm are stitched together and broadcast to members of the swarm. Thus, a follower can find the shortest path to the destination while avoiding even far away obstacles in an efficient manner. The proposed algorithm reduces the energy consumption of the swarm as a whole due to the fact that the leading robots sense and discover respective optimal paths and share their discoveries with the followers. The simulation results show that the robots effectively re-optimized the previous solution while sharing necessary information within the swarm. Furthermore, the efficiency of the proposed scheme is shown via comparative results, i.e., reducing traveling distance by 13% for individual robots and up to 11% for the swarm as a whole in the performed experiments.

Transmitter and Receiver Circuits for a High-Speed Polymer Fiber-Based PAM-4 Communication Link

A high data rate RF-DAC and a power detector (PD) are designed and fabricated in a 250 nm indium phosphide (InP) double heterojunction bipolar transistor (DHBT) technology. A communication link using the Tx-Rx over polymer microwave fiber (PMF) is measured. The link consists of a pulse amplitude modulation (PAM) modulator and a PD as a demodulator, as well as a one-meter-long dielectric waveguide. The working frequency range of the complete link is verified to be 110−150 GHz. The peak output power of the PAM modulator is 5 dBm, and it has a −3 dB bandwidth of 43 GHz. The PD consists of a parallel connected common emitter configured transistor and a common base configured transistor to suppress the odd-order harmonics at the PD’s output, as well as a stacked transistor to amplify the output signal. Tx and Rx chips, including pads, occupy a total area of only 0.83 mm2. The PMF link can support a PAM-4 signal with 22 Gbps data transmission, and a PAM-2 signal with 30 Gbps data transmission, with a bit error rate (BER) of <10−12, with demodulation performed in real time. Furthermore, the energy efficiency for the link (Tx + Rx) is 4.1 pJ/bit, using digital data input and receiving PAM-2 output (5.6 pJ/bit for PAM-4).

Area-Efficient Integrated Current-Reuse Feedback Amplifier for Wake-Up Receivers in Wireless Sensor Network Applications

Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR implementations, meeting high performance metrics is a design challenge, and the obtention of high-sensitivity, high data rate, low-power-consumption WuRs is not a straightforward procedure. The focus of our proposals is centered on power consumption and area reduction to provide high integrability and maintain a low cost-per-node, while we simultaneously improve circuit sensitivity. Firstly, we present a two-stage design based on a feedback technique and improve the area use, power consumption and sensitivity of the circuit by adding a current-reuse approach. The first solution is composed of a feedback amplifier, two op-amps plus a low-pass filter. The circuit achieves a sensitivity of -63.2 dBm with a power consumption of 6.77 µA and an area as low as 398 × 266 µm². With the current-reuse feedback amplifier, the power consumption is halved in the second circuit (resulting in 3.63 µA), and the resulting circuit area is as low as 262 × 262 µm². Thanks to the nature of the circuit, the sensitivity is improved to -75 dBm. This latter proposal is particularly suitable in applications where a fully integrated WuR is desired, providing a reasonable sensitivity with a low power consumption and a very low die footprint, therefore facilitating integration with other components of the WSN node. A thorough discussion of the most relevant state-of-the-art solutions is presented, too, and the two developed solutions are compared to the most relevant contributions available in the literature.

Sustainability of Heating, Ventilation and Air-Conditioning (HVAC) Systems in Buildings-An Overview

Increasing demand on heating, ventilation, and air-conditioning (HVAC) systems and their importance, as the respiratory system of buildings, in developing and spreading various microbial contaminations and diseases with their huge global energy consumption share have forced researchers, industries, and policymakers to focus on improving the sustainability of HVAC systems. Understanding and considering various parameters related to the sustainability of new and existing HVAC systems as the respiratory system of buildings are vital to providing healthy, energy-efficient, and economical options for various building types. However, the greatest opportunities for improving the sustainability of HVAC systems exist at the design stage of new facilities and the retrofitting of existing equipment. Considering the high available percentage of existing HVAC systems globally reveals the importance of their retrofitting. The attempt has been made to gather all important parameters that affect decision-making to select the optimum HVAC system development considerations among the various opportunities that are available for sustainability improvement.

Distributed Destination Search Routing for 5G and beyond Networks

Fifth-generation and beyond networks target multiple distributed network application such as Internet of Things (IoT), connected robotics, and massive Machine Type Communication (mMTC). In the absence of a central management unit, the device need to search and establish a route towards the destination before initializing data transmission. In this paper, we proposes a destination search and routing method for distributed 5G and beyond networks. In the proposed method, the source node makes multiple attempts to search for a route towards the destination by expanding disk-like patterns originating from the source node. The source node increases the search area in each attempt, accommodating more nodes in the search process. As a result, the probability of finding the destination increases, which reduces energy consumption and time delay of routing. We propose three variants of routing for high, medium, and low-density network scenarios and analyze their performance for various network configurations. The results demonstrate that the performance of the proposed solution is better than previously proposed techniques in terms of time latency and reduced energy consumption, making it applicable for 5G and beyond networks.

Beam Allocation and Power Optimization for Energy-Efficiency in Multiuser mmWave Massive MIMO System

This paper studies beam allocation and power optimization scheme to decrease the hardware cost and downlink power consumption of a multiuser millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. Our target is to improve energy efficiency (EE) and decrease power consumption without obvious system performance loss. To this end, we propose a beam allocation and power optimization scheme. First, the problem of beam allocation and power optimization is formulated as a multivariate mixed-integer non-linear programming problem. Second, due to the non-convexity of this problem, we decompose it into two sub-problems which are beam allocation and power optimization. Finally, the beam allocation problem is solved by using a convex optimization technique. We solve the power optimization problem in two steps. First, the non-convex problem is converted into a convex problem by using a quadratic transformation scheme. The second step implements Lagrange dual and sub-gradient methods to solve the optimization problem. Performance analysis and simulation results show that the proposed algorithm performs almost identical to the exhaustive search (ES) method, while the greedy beam allocation and suboptimal beam allocation methods are far from the ES. Furthermore, experiment results demonstrated that our proposed algorithm outperforms the compared the greedy beam allocation method and the suboptimal beam allocation scheme in terms of average service ratio.

Low-Power RFED Wake-Up Receiver Design for Low-Cost Wireless Sensor Network Applications

The development of wake-up receivers (WuR) has recently received a lot of interest from both academia and industry researchers, primarily because of their major impact on the improvement of the performance of wireless sensor networks (WSNs). In this paper, we present the development of three different radiofrequency envelope detection (RFED) based WuRs operating at the 868 MHz industrial, scientific and medical (ISM) band. These circuits can find application in densely populated WSNs, which are fundamental components of Internet-of-Things (IoT) or Internet-of-Everything (IoE) applications. The aim of this work is to provide circuits with high integrability and a low cost-per-node, so as to facilitate the implementation of sensor nodes in low-cost IoT applications. In order to demonstrate the feasibility of implementing a WuR with commercially available off-chip components, the design of an RFED WuR in a PCB mount is presented. The circuit is validated in a real scenario by testing the WuR in a system with a pattern recognizer (AS3933), an MCU (MSP430G2553 from TI), a transceiver (CC1101 from TI) and a T/R switch (ADG918). The WuR has no active components and features a sensitivity of about −50 dBm, with a total size of 22.5 × 51.8 mm². To facilitate the integration of the WuR in compact systems and low-cost applications, two designs in a commercial UMC 65 nm CMOS process are also explored. Firstly, an RFED WuR with integrated transformer providing a passive voltage gain of 18 dB is demonstrated. The circuit achieves a sensitivity as low as −62 dBm and a power consumption of only 528 nW, with a total area of 634 × 391 μm². Secondly, so as to reduce the area of the circuit, a design of a tuned-RF WuR with integrated current-reuse active inductor is presented. In this case, the WuR features a sensitivity of −55 dBm with a power consumption of 43.5 μW and a total area of 272 × 464 μm², obtaining a significant area reduction at the expense of higher power consumption. The alternatives presented show a very low die footprint with a performance in line with most of the state-of-the-art contributions, making the topologies attractive in scenarios where high integrability and low cost-per-node are necessary.

Efficient and Facile Electrochemical Process for the Production of High-Quality Lithium Hexafluorophosphate Electrolyte

The global consumption for lithium hexafluorophosphate (LiPF₆) has increased dramatically with the rapid growth of Li-ion batteries (LIBs) for large-scale electric energy storage applications. Conventional LiPF₆ production has a high cost and high energy consumption due to complicated separation and purification processes. Here, based on the electrode materials of LiMn₂O₄ and polyaniline (PANI), we propose a facile electrochemical extraction/release process for LiPF₆ electrolyte production. This new technology consists of two independent steps: a PF₆^-- and Li⁺-extracting step using a PANI/Li_xMn₂O₄ cell in aqueous solution (an ion extraction step) and a LiPF₆ electrolyte production step from the charged LiMn₂O₄/PANI⁺PF₆^- cell in an organic electrolyte (an ion release step). This new process can effectively avoid the contamination of HF residue in the final product, providing a great possibility to create a facile, energy-efficient, and low-cost LiPF₆ electrolyte production.

Anomaly Detection Based Latency-Aware Energy Consumption Optimization For IoT Data-Flow Services

The continuous data-flow application in the IoT integrates the functions of fog, edge, and cloud computing. Its typical paradigm is the E-Health system. Like other IoT applications, the energy consumption optimization of IoT devices in continuous data-flow applications is a challenging problem. Since the anomalous nodes in the network will cause the increase of energy consumption, it is necessary to make continuous data flows bypass these nodes as much as possible. At present, the existing research work related to the performance of continuous data-flow is often optimized from system architecture design and deployment. In this paper, a mathematical programming method is proposed for the first time to optimize the runtime performance of continuous data flow applications. A lightweight anomaly detection method is proposed to evaluate the reliability of nodes. Then the node reliability is input into the optimization algorithm to estimate the task latency. The latency-aware energy consumption optimization for continuous data-flow is modeled as a mixed integer nonlinear programming problem. A block coordinate descend-based max-flow algorithm is proposed to solve this problem. Based on the real-life datasets, the numerical simulation is carried out. The simulation results show that the proposed strategy has better performance than the benchmark strategy.

Reinforcement Learning (RL)-Based Energy Efficient Resource Allocation for Energy Harvesting-Powered Wireless Body Area Network

Wireless body area networks (WBANs) have attracted great attention from both industry and academia as a promising technology for continuous monitoring of physiological signals of the human body. As the sensors in WBANs are typically battery-driven and inconvenient to recharge, an energy efficient resource allocation scheme is essential to prolong the lifetime of the networks, while guaranteeing the rigid requirements of quality of service (QoS) of the WBANs in nature. As a possible alternative solution to address the energy efficiency problem, energy harvesting (EH) technology with the capability of harvesting energy from ambient sources can potentially reduce the dependence on the battery supply. Consequently, in this paper, we investigate the resource allocation problem for EH-powered WBANs (EH-WBANs). Our goal is to maximize the energy efficiency of the EH-WBANs with the joint consideration of transmission mode, relay selection, allocated time slot, transmission power, and the energy constraint of each sensor. In view of the characteristic of the EH-WBANs, we formulate the energy efficiency problem as a discrete-time and finite-state Markov decision process (DFMDP), in which allocation strategy decisions are made by a hub that does not have complete and global network information. Owing to the complexity of the problem, we propose a modified Q-learning (QL) algorithm to obtain the optimal allocation strategy. The numerical results validate the effectiveness of the proposed scheme as well as the low computation complexity of the proposed modified Q-learning (QL) algorithm.

Giant and Reversible Inverse Barocaloric Effects near Room Temperature in Ferromagnetic MnCoGeB0.03

Hydrostatic pressure represents an inexpensive and practical method of driving caloric effects in brittle magnetocaloric materials, which display first-order magnetostructural phase transitions whose large latent heats are traditionally accessed using applied magnetic fields. Here, moderate changes of hydrostatic pressure are used to drive giant and reversible inverse barocaloric effects near room temperature in the notoriously brittle magnetocaloric material MnCoGeB_0.03 . The barocaloric effects compare favorably with those observed in barocaloric materials that are magnetic. The inevitable fragmentation provides a large surface for heat exchange with pressure-transmitting media, permitting good access to barocaloric effects in cooling devices.

TAEO-A Thermal Aware & Energy Optimized Routing Protocol for Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are in the spotlight of researchers and engineering industries due to many applications. Remote health monitoring for general as well as military purposes where tiny sensors are attached or implanted inside the skin of the body to sense the required attribute is particularly prominent. To seamlessly accomplish this procedure, there are various challenges, out of which temperature control to reduce thermal effects and optimum power consumption to reduce energy wastage are placed at the highest priority. Regular and consistent operation of a sensor node for a long-time result in a rising of the temperature of respective tissues, where it is attached or implanted. This temperature rise has harmful effects on human tissues, which may lead to the tissue damage. In this paper, a Temperate Aware and Energy Optimized (TAEO) routing protocol is proposed that not only deals with the thermal aspects and hot spot problem, but also extends the stability and lifetime of a network. Analytical simulations are conducted, and the results depict better performance in terms of the network lifetime, throughput, energy preservation, and temperature control with respect to state of the art WBAN protocols.

Microwave assisted henna organic dyeing of polyester fabric: a green, economical and energy proficient substitute

The proposed work, aims to provide a "green" and cutting-edge technique for the mordanting and dyeing of polyester fabric with natural henna dye using the advanced technology of micro waves. For providing a complete "green" and ecofriendly dyeing process, lemon was used as a natural bio mordant with micro waves and results were compared with conventional mordanting method followed by the natural henna dyeing of polyester fabric with microwave. Color properties were analyzed in detail. Scanning electron microscope (SEM), WIDE ANGLE X-RAY DIFFRACTION (WAXD) and Fourier transform infrared spectrometer (ATR-FTIR) studies provide the details of surface and structural changes induced by microwave lemon mordanting and henna dyeing of polyester. Microwave technique clearly reduced the mordanting and dyeing time upto 60-65% with improved fixation and color characteristics.

Towards Void Hole Alleviation by Exploiting the Energy Efficient Path and by Providing the Interference-Free Proactive Routing Protocols in IoT Enabled Underwater WSNs

Nowadays, the Internet of Things enabled Underwater Wireless Sensor Network (IoT-UWSN) is suffering from serious performance restrictions, i.e., high End to End (E2E) delay, low energy efficiency, low data reliability, etc. The necessity of efficient, reliable, collision and interference-free communication has become a challenging task for the researchers. However, the minimum Energy Consumption (EC) and low E2E delay increase the performance of the IoT-UWSN. Therefore, in the current work, two proactive routing protocols are presented, namely: Bellman⁻Ford Shortest Path-based Routing (BF-SPR-Three) and Energy-efficient Path-based Void hole and Interference-free Routing (EP-VIR-Three). Then we formalized the aforementioned problems to accomplish the reliable data transmission in Underwater Wireless Sensor Network (UWSN). The main objectives of this paper include minimum EC, interference-free transmission, void hole avoidance and high Packet Delivery Ratio (PDR). Furthermore, the algorithms for the proposed routing protocols are presented. Feasible regions using linear programming are also computed for optimal EC and to enhance the network lifespan. Comparative analysis is also performed with state-of-the-art proactive routing protocols. In the end, extensive simulations have been performed to authenticate the performance of the proposed routing protocols. Results and discussion disclose that the proposed routing protocols outperformed the counterparts significantly.

Simultaneous Spark Plasma Sintering of Multiple Complex Shapes

This work addresses the two great challenges of the spark plasma sintering (SPS) process: The sintering of complex shapes and the simultaneous production of multiple parts. A new controllable interface method is employed to concurrently consolidate two nickel gear shapes by SPS. A graphite deformable sub-mold is specifically designed for the mutual densification of both complex parts in a unique 40 mm powder deformation space. An energy efficient SPS configuration is developed to allow the sintering of a large-scale powder assembly under electric current lower than 900 A. The stability of the developed process is studied by electro-thermal-mechanical (ETM) simulation. The ETM simulation reveals that homogeneous densification conditions can be attained by inserting an alumina powder at the sample/punches interfaces, enabling the energy efficient heating and the thermal confinement of the nickel powder. Finally, the feasibility of the fabrication of the two near net shape gears with a very homogeneous microstructure is demonstrated.

Exploiting Layered Multi-Path Routing Protocols to Avoid Void Hole Regions for Reliable Data Delivery and Efficient Energy Management for IoT-Enabled Underwater WSNs

The key concerns to enhance the lifetime of IoT-enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are energy-efficiency and reliable data delivery under constrained resource. Traditional transmission approaches increase the communication overhead, which results in congestion and affect the reliable data delivery. Currently, many routing protocols have been proposed for UWSNs to ensure reliable data delivery and to conserve the node's battery with minimum communication overhead (by avoiding void holes in the network). In this paper, adaptive energy-efficient routing protocols are proposed to tackle the aforementioned problems using the Shortest Path First (SPF) with least number of active nodes strategy. These novel protocols have been developed by integrating the prominent features of Forward Layered Multi-path Power Control One (FLMPC-One) routing protocol, which uses 2-hop neighbor information, Forward Layered Multi-path Power Control Two (FLMPC-Two) routing protocol, which uses 3-hop neighbor information and 'Dijkstra' algorithm (for shortest path selection). Different Packet Sizes (PSs) with different Data Rates (DRs) are also taken into consideration to check the dynamicity of the proposed protocols. The achieved outcomes clearly validate the proposed protocols, namely: Shortest Path First using 3-hop neighbors information (SPF-Three) and Breadth First Search with Shortest Path First using 3-hop neighbors information (BFS-SPF-Three). Simulation results show the effectiveness of the proposed protocols in terms of minimum Energy Consumption (EC) and Required Packet Error Rate (RPER) with a minimum number of active nodes at the cost of affordable delay.

Designing Transmission Strategies for Enhancing Communications in Medical IoT Using Markov Decision Process

The introduction of medical Internet of Things (IoT) for biomedical applications has brought about the era of proactive healthcare. Such advanced medical supervision lies on the foundation of a network of energy-constrained wearable or implantable sensors (or things). These miniaturized battery-powered biosensor nodes are placed in, on, or around the human body to measure vital signals to be reported to the sink. This network configuration deployed on a human body is known as the Wireless Body Area Network (WBAN). Strategies are required to restrict energy expenditure of the nodes without degrading performance of WBAN to make medical IoT a green (energy-efficient) and effective paradigm. Direct communication from a node to sink in WBAN may often lead to rapid energy depletion of nodes as well as growing thermal effects on the human body. Hence, multi-hop communication from sources to sink in WBAN is often preferred instead of direct communication with high transmission power. Existing research focuses on designing multi-hop protocols addressing the issues in WBAN routing. However, the ideal conditions for multi-hop routing in preference to single-hop direct delivery is rarely investigated. Accordingly, in this paper an optimal transmission policy for WBAN is developed using Markov Decision Process (MDP) subject to various input conditions such as battery level, event occurrence, packet transmission rate and link quality. Thereafter, a multi-hop routing protocol is designed where routing decisions are made following a pre-computed strategy. The algorithm is simulated, and performance is compared with existing multi-hop protocol for WBAN to demonstrate the viability of the proposed scheme.

Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol

This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate.

A Distributed and Context-Aware Task Assignment Mechanism for Collaborative Mobile Edge Computing

Mobile edge computing (MEC) is an emerging technology that leverages computing, storage, and network resources deployed at the proximity of users to offload their delay-sensitive tasks. Various existing facilities including mobile devices with idle resources, vehicles, and MEC servers deployed at base stations or road side units, could act as edges in the network. Since task offloading incurs extra transmission energy consumption and transmission latency, two key questions to be addressed in such an environment are (i) should the workload be offloaded to the edge or computed in terminals? (ii) Which edge, among the available ones, should the task be offloaded to? In this paper, we formulate the task assignment problem as a one-to-many matching game which is a powerful tool for studying the formation of a mutual beneficial relationship between two sets of agents. The main goal of our task assignment mechanism design is to reduce overall energy consumption, while satisfying task owners’ heterogeneous delay requirements and supporting good scalability. An intensive simulation is conducted to evaluate the efficiency of our proposed mechanism.

An Effective Delay Reduction Approach through a Portion of Nodes with a Larger Duty Cycle for Industrial WSNs

For Industrial Wireless Sensor Networks (IWSNs), sending data with timely style to the stink (or control center, CC) that is monitored by sensor nodes is a challenging issue. However, in order to save energy, wireless sensor networks based on a duty cycle are widely used in the industrial field, which can bring great delay to data transmission. We observe that if the duty cycle of a small number of nodes in the network is set to 1, the sleep delay caused by the duty cycle can be effectively reduced. Thus, in this paper, a novel Portion of Nodes with Larger Duty Cycle (PNLDC) scheme is proposed to reduce delay and optimize energy efficiency for IWSNs. In the PNLDC scheme, a portion of nodes are selected to set their duty cycle to 1, and the proportion of nodes with the duty cycle of 1 is determined according to the energy abundance of the area in which the node is located. The more the residual energy in the region, the greater the proportion of the selected nodes. Because there are a certain proportion of nodes with the duty cycle of 1 in the network, the PNLDC scheme can effectively reduce delay in IWSNs. The performance analysis and experimental results show that the proposed scheme significantly reduces the delay for forwarding data by 8.9~26.4% and delay for detection by 2.1~24.6% without reducing the network lifetime when compared with the fixed duty cycle method. Meanwhile, compared with the dynamic duty cycle strategy, the proposed scheme has certain advantages in terms of energy utilization and delay reduction.

Energy-Efficient Data Collection Method for Sensor Networks by Integrating Asymmetric Communication and Wake-Up Radio

In large-scale wireless sensor networks (WSNs), nodes close to sink nodes consume energy more quickly than other nodes due to packet forwarding. A mobile sink is a good solution to this issue, although it causes two new problems to nodes: (i) overhead of updating routing information; and (ii) increased operating time due to aperiodic query. To solve these problems, this paper proposes an energy-efficient data collection method, Sink-based Centralized transmission Scheduling (SC-Sched), by integrating asymmetric communication and wake-up radio. Specifically, each node is equipped with a low-power wake-up receiver. The sink node determines transmission scheduling, and transmits a wake-up message using a large transmission power, directly activating a pair of nodes simultaneously which will communicate with a normal transmission power. This paper further investigates how to deal with frame loss caused by fading and how to mitigate the impact of the wake-up latency of communication modules. Simulation evaluations confirm that using multiple channels effectively reduces data collection time and SC-Sched works well with a mobile sink. Compared with the conventional duty-cycling method, SC-Sched greatly reduces total energy consumption and improves the network lifetime by 7.47 times in a WSN with 4 data collection points and 300 sensor nodes.

An Advanced IoT-based System for Intelligent Energy Management in Buildings

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings’ energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building’s data (e.g., energy management systems), energy production, energy prices, weather data and end-users’ behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.

Hydrothermal Synthesis of VO2 Polymorphs: Advantages, Challenges and Prospects for the Application of Energy Efficient Smart Windows

Vanadium dioxide (VO₂ ) is a widely studied inorganic phase change material, which has a reversible phase transition from semiconducting monoclinic to metallic rutile phase at a critical temperature of τ_c ≈ 68 °C. The abrupt decrease of infrared transmittance in the metallic phase makes VO₂ a potential candidate for thermochromic energy efficient windows to cut down building energy consumption. However, there are three long-standing issues that hindered its application in energy efficient windows: high τ_c , low luminous transmittance (T_lum ), and undesirable solar modulation ability (ΔT_sol ). Many approaches, including nano-thermochromism, porous films, biomimetic surface reconstruction, gridded structures, antireflective overcoatings, etc, have been proposed to tackle these issues. The first approach-nano-thermochromism-which is to integrate VO₂ nanoparticles in a transparent matrix, outperforms the rest; while the thermochromic performance is determined by particle size, stoichiometry, and crystallinity. A hydrothermal method is the most common method to fabricate high-quality VO₂ nanoparticles, and has its own advantages of large-scale synthesis and precise phase control of VO₂ . This Review focuses on hydrothermal synthesis, physical properties of VO₂ polymorphs, and their transformation to thermochromic VO₂ (M), and discusses the advantages, challenges, and prospects of VO₂ (M) in energy-efficient smart windows application.

An Energy-Efficient MAC Protocol for Medical Emergency Monitoring Body Sensor Networks

Medical emergency monitoring body sensor networks (BSNs) monitor the occurrence of medical emergencies and are helpful for the daily care of the elderly and chronically ill people. Such BSNs are characterized by rare traffic when there is no emergency occurring, high real-time and reliable requirements of emergency data and demand for a fast wake-up mechanism for waking up all nodes when an emergency happens. A beacon-enabled MAC protocol is specially designed to meet the demands of medical emergency monitoring BSNs. The rarity of traffic is exploited to improve energy efficiency. By adopting a long superframe structure to avoid unnecessary beacons and allocating most of the superframe to be inactive periods, the duty cycle is reduced to an extremely low level to save energy. Short active time slots are interposed into the superframe and shared by all of the nodes to deliver the emergency data in a low-delay and reliable way to meet the real-time and reliable requirements. The interposition slots can also be used by the coordinator to broadcast network demands to wake-up all nodes in a low-delay and energy-efficient way. Experiments display that the proposed MAC protocol works well in BSNs with low emergency data traffic.

A Constant Energy-Per-Cycle Ring Oscillator Over a Wide Frequency Range for Wireless Sensor Nodes

This paper presents an energy-efficient oscillator for wireless sensor nodes (WSNs). It avoids short-circuit current by minimizing the time spent in the input voltage range from V_thn to [V_dd - |V_thp|]. A current-feeding scheme with gate voltage control enables the oscillator to operate over a wide frequency range. A test chip is fabricated in a 0.18 μm CMOS process. The measurements show that the proposed oscillator achieves a constant energy-per-cycle (EpC) of 0.8 pJ/cycle over the 21-60 MHz frequency range and is more efficient than a conventional current-starved ring oscillator (CSRO) below 300 kHz at 1.8 V supply voltage. As an application example, the proposed oscillator is implemented in a switched-capacitor DC-DC converter. The converter is 11%-56% more efficient for load power values ranging from 583 pW to 2.9 nW than a converter using a conventional CSRO.

A Novel Energy-Aware Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Networks in the Mobile Environment

In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network’s running and the degree of candidate nodes’ effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime.

A review of protocol implementations and energy efficient cross-layer design for wireless body area networks

The issues inherent in caring for an ever-increasing aged population has been the subject of endless debate and continues to be a hot topic for political discussion. The use of hospital-based facilities for the monitoring of chronic physiological conditions is expensive and ties up key healthcare professionals. The introduction of wireless sensor devices as part of a Wireless Body Area Network (WBAN) integrated within an overall eHealth solution could bring a step change in the remote management of patient healthcare. Sensor devices small enough to be placed either inside or on the human body can form a vital part of an overall health monitoring network. An effectively designed energy efficient WBAN should have a minimal impact on the mobility and lifestyle of the patient. WBAN technology can be deployed within a hospital, care home environment or in the patient’s own home. This study is a review of the existing research in the area of WBAN technology and in particular protocol adaptation and energy efficient cross-layer design. The research reviews the work carried out across various layers of the protocol stack and highlights how the latest research proposes to resolve the various challenges inherent in remote continual healthcare monitoring.

An energy-efficient rate adaptive media access protocol (RA-MAC) for long-lived sensor networks

We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC) algorithm for long-lived Wireless Sensor Networks (WSNs). Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application’s link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode) on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment.