Limited Energy Sources Research Articles

Bounded consensus tracking of second-order multi-agent systems using rectangular impulsive control

In this paper, the problem of bounded consensus tracking for second-order multi-agent systems is addressed with fixed and randomly switching directed topologies, wherein the leader is stimulated by an unknown time-varying but bounded external input. A novel distributed rectangular impulsive control strategy is developed, which only utilizes casual sampled position data of the neighboring agents. The proposed protocol is beneficial to the limited bandwidth and energy source. By virtue of graph and matrix theories, necessary and sufficient conditions are established, which guarantee the bounded consensus tracking under fixed topology and the mean-square bounded consensus under randomly switching topologies. The proposed algorithms incorporate the performance of the Dirac impulsive control and the sampled-data control. Finally, numerical examples are delivered to validate the effectiveness of the theoretical results.

Design and analysis of PV fed SRM system

Renewable energy sources supplied motor applications are being studied widely by researchers. As it is especially focused on design and control of such systems, studies on performance analysis approach is limited. It is vital to determine the operating behaviour of motor loads when they are supplied by limited energy sources like photovoltaic (PV) systems. According to this necessity, in this study, a switched reluctance motor (SRM) which is supplied by a PV system is analysed in terms of speed, current and torque data. Because of its advantages as it can be controlled over a wide range, its reliability and stability, SRM was used for analysis. Such data are observed in two cases, PV system irradiance change and fault conditions. System is designed as direct-fed, which is not include any storage unit. Therefore, any changes at supply system directly affect motor parameters. These effects and results are discussed by using the graphs that obtained from various points of system for both cases.

Guest Editorial: Next Generation Wireless Computing Systems

The three papers in this special section focus on next generation wireless computing systems. An important aspect of the next generation wireless computing to ensure a high computing performance is the quality of service (QoS). Wireless communications hold specific characteristics such as frequent disconnections, channel variation, modest available resources, limited energy sources, inefficient security, and fluctuating quality of service. This Special Issue presents state-of-the art QoS solutions for future generations of wireless networks for improved use of various computing systems. Design, development, analysis, and optimization of communication protocols and some perspective solutions for improved performance of Next Generation Wireless Computing Systems in terms of QoS and energy efficiency are the subject of papers included in this Special Issue. The three papers selected here broadly cover specific areas among the above topics with the consideration of providing high-quality research and practical initiatives in the field.

Optimal Hop Lengths to Ensure Minimum Energy Consumption in Wireless Sensor Networks

In wireless sensor networks, nodes have a low computing capacity, a small antenna and a very limited energy source; thereby batteries are considered as a critical resource and should be used efficiently. On the other hand, the antennas are the biggest consumers of energy, therefore, and their use must be very efficient to minimize energy consumption. In a dense WSN, each node may route messages to destination nodes either through short-hops or long-hops, by using a short or a long radio range. Thus, the hop length optimization can save energy. In this article, the authors propose a theorem to optimize the hop lengths and a routing algorithm to improve the WSN power consumption. The theorem establishes a simple condition to ensure the optimal hop lengths which guarantees the minimum energy consumption. And the proposed algorithm based on that condition is used to find the optimal routing path. The simulation results are obtained by applying the condition and the algorithm on WSNs and reveals a high performance regarding WSNs energy consumption and network lifetime.

The IoT Energy Challenge: A Software Perspective

The Internet of Things (IoT) sparks a whole new world of embedded applications. Most of these applications are based on deeply embedded systems that have to operate on limited or unreliable sources of energy, such as batteries or energy harvesters. Meeting the energy requirements for such applications is a hard challenge, which threatens the future growth of the IoT. Software has the ultimate control over hardware. Therefore, its role is significant in optimizing the energy consumption of a system. Currently, programmers have no feedback on how their software affects the energy consumption of a system. Such feedback can be enabled by energy transparency, a concept that makes a program's energy consumption visible, from hardware to software. This paper discusses the need for energy transparency in software development and emphasizes on how such transparency can be realized to help tackling the IoT energy challenge.

Trust-based multi-hop cooperative spectrum sensing in cognitive radio networks

Cooperative spectrum sensing is one of the solutions for cognitive radio networks, which can resolve the uncertainty of stand-alone spectrum sensing. It means that each secondary user senses defined spectrum bands for the unused spectrum detection and shares its sensing results with the others to improve the accuracy of spectrum sensing. Due to the presence of malicious secondary users and their fake sensing reports, various forms of attacks will be encountered that reduce the performance of cooperative spectrum sensing. Spectrum sensing data falsification attack (SSDF) is one of the attacks that some research works have been presented to defend against it, based on trust and reputation management (TRM). Previous works assume that all the secondary users are in the transmission range of each other and one-hop sensing reports are provided. However, multi-hop dissemination of sensing reports is a necessary scenario for the secondary users with limited energy sources and its security attacks are very challenging to be encountered. In this paper, a trust-based multi-hop cooperative spectrum sensing method is proposed to deal with SSDF attack. Simulation results show that this scheme improves spectrum sensing accuracy and reduces.

RF Energy Harvesting with Multiple Sources in Wireless Mesh Network

Energy harvesting (EH) module for wireless sensor network has become a promising feature to prolong the conventional battery inside the devices. This emerging technology is gaining interest from sensor manufacturers as well as academicians across the globe. The concept of employing EH module must be cost effective and practical. In such, the use of EH module type besides RF is more realistic due to the size of the scavenger module, the availability of the resources and conversion efficiency. Most of the oil and gas plants have some drawbacks in scavenging RF from surrounding (i.e. router, Wi-Fi, base station, cell phone) due to its placement in remote area and thus limited energy sources could be a threat in this application. Multiple sources, including co-channel interference (CCI) in any constraint nodes is a feasible way of scavenging several wastes from ambient RF energy via wireless mesh topology. In this paper, a 3-node decode-and-forward (DF) model is proposed where the relay node is subject to an energy constraint. Multiple primary sources and CCI are added in the system model known as Multiple-Source and Single-Relay (MSSR). A mathematical model is derived in Time Switching Relaying (TSR) and Power Splitting Relaying (PSR) schemes to obtain an average system throughput at a destination. Numerical simulation with respect to the average throughput and EH ratio was performed and compared with the Single-Source and Single-Relay (SSSR) and ideal receiver. By applying multiple sources and CCI as an energy enhancement at the constraint node, the optimal value of EH ratio for TSR can be reduced significantly by 10% as compared to the ideal receiver whereas the optimal value of EH ratio for PSR is outweigh TSR in terms of overall system throughput.

On the Lightweight Structural Design for Electric Road and Railway Vehicles using Fiber Reinforced Polymer Composites – A Review

The main challenging issues of vehicles with electric propulsion are on the limited energy source due to relatively low battery capacity and low excitation of power traction. They can be tackled down by designing lightweight structures for frameworks and bodies of the vehicles. Composite materials which have a high strength to weight ratio are the best choice for designing and manufacturing the lightweight structures. A review of recent progress in utilization of the composite materials for electric vehicle structures is presented. It focuses on how the structures can support the electric vehicles to compete with internal combustion engine vehicles regarding their performance on the road. The utilization of composite material for structures of railway vehicles is also summarized. Furthermore, discussions are extended to the key technologies required for applying the composite materials in Indonesia such as composite–metal joint technology, fiber and matrix production technology, and numerical analysis competency for modeling the composite.

Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions

In light of increasing alerts about limited energy sources and environment degradation, it has become essential to search for alternatives to thermal engine-based vehicles which are a major source of air pollution and fossil fuel depletion. Hybrid electric vehicles (HEVs), encompassing multiple energy sources, are a short-term solution that meets the performance requirements and contributes to fuel saving and emission reduction aims. Power management methods such as regulating efficient energy flow to the vehicle propulsion, are core technologies of HEVs. Intelligent power management methods, capable of acquiring optimal power handling, accommodating system inaccuracies, and suiting real-time applications can significantly improve the powertrain efficiency at different operating conditions. Rule-based methods are simply structured and easily implementable in real-time; however, a limited optimality in power handling decisions can be achieved. Optimization-based methods are more capable of achieving this optimality at the price of augmented computational load. In the last few years, these optimization-based methods have been under development to suit real-time application using more predictive, recognitive, and artificial intelligence tools. This paper presents a review-based discussion about these new trends in real-time optimal power management methods. More focus is given to the adaptation tools used to boost methods optimality in real-time. The contribution of this work can be identified in two points: First, to provide researchers and scholars with an overview of different power management methods. Second, to point out the state-of-the-art trends in real-time optimal methods and to highlight promising approaches for future development.

Use of MCDM techniques for energy policy and decision-making problems: A review

Energy consumption increases all over the world as a result of industrialization in recent years. In this context, it has become important to meet increasing energy demand. It is significant to find alternative energy sources because of limited nonrenewable energy sources such as coal, petroleum, and natural gas. At this point, renewable energy sources have an important role to meet energy requirement. As a result, decision and policy making for energy is completely critical issue for countries. Various technical, economic, environmental, and social criteria are used to solve energy policy and decision-making problems such as evaluation of energy projects, selection among energy alternatives, power plant site selection, and determining energy policy. Multicriteria decision-making (MCDM) methods are used as effective tools to help decision makers while solving energy problems. There are a large number of studies including articles, conference papers, and book chapters, which examine energy problems by using MCDM methods in the literature. Therefore, analyzing these studies according to different features such as publication year, MCDM method, document type, statistical analyses, country, and published journal can be beneficial for leading researchers who study in energy decision-making field. In this study, published papers, which use traditional MCDM methods to handle energy problems, are examined systematically. By the way, it is aimed to lead to researchers regarding MCDM methods which are utilized in energy applications. It also conducted some statistical analyses to obtain trends between years and MCDM methods. Besides, recent developments in energy field are presented through this comprehensive literature review.

Energy Efficiency TDMA/CSMA Hybrid Protocol with Power Control for WSN

Wireless sensors network (WSN) is widely used in the Internet of Things at present. However, limited energy source is a critical problem in the improvement and practical applications of WSN, so it is necessary to improve the energy efficiency. As another important evaluation criterion of transmission performance, throughput should be improved too. To mitigate both of the problems at the same time, by taking the advantages of Time Division Multiple Access (TDMA) and Carrier Sense Multiple Access (CSMA) at the medium access control (MAC) layer of WSN, we propose a hybrid TDMA/CSMA MAC layer protocol. Meanwhile, we design a novel power control scheme to further reduce the energy consumption and optimize the transmission slots. The simulation results demonstrate that the proposed protocol significantly improves the throughput and energy efficiency.

Energy-Efficient Architecture for Wireless Sensor Networks in Healthcare Applications

The need to deploy wireless sensor networks (WSNs) for real-world applications, such as mobile multimedia for healthcare organizations, is increasing spectacularly. However, the energy problem remains one of the core barriers preventing an increase in investment in this technology. In this paper, we propose a new technique to resolve the problems due to limited energy sources. Using a quaternary transceiver (in the architecture on a sensor node), instead of a binary one, which will use the amplitude/phase, modulator/demodulator units to increase the number of bits transmitted per symbol. The system will reduce the consumption of energy in the transmission phase due to the increased bits transmitted per symbol. Moreover, neural network static random access memory (NN-SRAM) implementation in a clustering-based system for energy-constrained WSNs is proposed. The scheme reduces the total amount of energy consumption in storage and transmissions during the data dissemination process. Through simulation results based on MATLAB and Spice software tools, it is shown that the neural network static random access memory implementation in a clustering-based system reduces the energy consumption of the entire system by about 76.99%.

Survey on Algorithms for Energy Efficient Cluster Head Selection in Wireless Sensor Networks

Wireless Sensor Network (WSN) is a large collection of tiny self-aware, battery-operated, analyzable sensor network which integrates sensing, computation and communication in a single tiny device. These tiny devices can be used for ample number of remote sensing applications. Increasing network life time is one of the major design problems in Wireless Sensor Network as they have limited energy source. Clustering the nodes is one of the effective approaches to minimize energy consumption. Clustering is group of nodes in independent clusters and each cluster comprises of one or more cluster head based on network size. The nodes transmit sensed data to the respective cluster heads which in turn transmit the aggregated data to base station. Clustering algorithms enhance the lifetime of networks by avoiding long distance communication of nodes to base station. In this literature survey, various clustering approaches are discussed with working of few Clustering algorithms and distinguish them based on performance of algorithm.

Control of Hydraulic Manipulator with Consideration of Power Limitations On-Board Energy Source

In the paper we present results of theoretical and experimental research of properties of manipulators with electro hydraulic servo drives with energy sources of limited power. The danger of overloading the power sources and associated functional failures of the drive system are discussed. In order to solve the problem we propose a new structure of the control system and algorithms. This allows to effectively distribute available power between hydraulic drives. These control algorithms are based on a system with variable structure with actual fluid flow feedback. This paper presents analysis of the amplitude of the first harmonic and of oscillation frequency of the total flow in the steady state. This allows to give recommendations how to improve dynamic properties of a hydraulic manipulator. The proposed control laws solve the problem of coordination of motion of links of the manipulator for automatic distribution of power resources. Besides this, it creates favorable conditions for functioning of biotechnical system "human operator - hydraulic manipulator" with limited energy source.

An electrophysiological model of working memory performance

Working memory (WM) enables us to keep a limited amount of information in active mode. It is believed that attention refreshes necessary information in WM and prevents their forgetting. Despite a plethora of models offered, it is not fully understood that what factors may be involved in forgetfulness and in the required time for refreshing the information. In this study, an electrophysiological model of WM is proposed that consists of several resistor-capacitor units. Inspired of the “resource capacity theory,” attention as a limited source of energy refreshes the voltage level of these units. According to the “time-based resource sharing theory,” only one of these units is allowed to use the limited source of attention at each moment. The source of attention is shared between active units. This model mimics the pattern of several well-known observations of WM such as the recall interval, the word length, and the serial position effect. Some suggestions have been provided about influencing factors in WM performance. Model parameters give the ability of investigating the possible effect of some other factors on WM performance and also a probable prediction about how much information can we chunk?

T-ROME: A simple and energy efficient tree routing protocol for low-power wake-up receivers

Wireless sensor networks are deployed in many monitoring applications but still suffer from short lifetimes originating from limited energy sources and storages. Due to their low-power consumption and their on-demand communication ability, wake-up receivers represent an energy efficient and simple enhancement to wireless sensor nodes and wireless sensor network protocols. In this context, wake-up receivers have the ability to increase the network lifetime. In this article, we present T-ROME, a simple and energy efficient cross-layer routing protocol for wireless sensor nodes containing wake-up receivers. The protocol makes use of the different transmission ranges of wake-up and main radios in order to save energy by skipping nodes during data transfer. With respect to energy consumption and latency, T-ROME outperforms existing protocols in many scenarios. Here, we describe and analyze the cross layer multi-hop protocol by means of a Markov chain model that we verify using a laboratory test setup.

Minimizing Path Loss in Medical Wireless Sensors in Wireless Body Area Sensor Networks

Objectives: To save the energy consumption of the sensors in transmission so that they may operate for longer time span. Methods/Statistical Analysis: It is suggested to use eight sensors placed on the human body and then transposition has been applied to all of these sensors to reduce the distance of each sensor from the sink. Path loss was calculated after transposition in terms of distance and results were compared with the existing schemes. Euclidean distance technique was applied to calculate the distance values and then observed for their positions. Findings: In this investigation, the main parameter is the path loss which needs to be reduced so as to make the transmission better and to make network stable. The findings are unique in the sense that with the help of the proposed values of sensor positions a routing protocols be designed which will have a better network stability and network life time and this will be achieved as the sensors will deplete less energy during transmission. The main idea behind this research is to find the most suitable sensor locations on the body where they can consume less energy during data transmission to sink and have more life to operate. Application/Improvements: The proposed scheme is applicable to body area systems which have limited energy sources due to the size of the sensors. The proposed scheme is compared with two existing schemes and there were improvements in terms of path loss parameter.

Energy-aware bee colony approach to extend lifespan of wireless sensor network

Wireless sensor networks (WSNs) consist of an immense number of tiny wireless sensor nodes deployed in a limited areas. The sensor nodes collect information from the areas and send to a central base station. The sensor nodes in such networks bring limited energy sources and in many situations, it is so difficult to recharge or replace the limited energy source of these tiny sensor nodes. For that reason, it is essential that these networks function under energy-efficient protocols and arrangements. This paper presents a novel Energy-Aware Bee Colony Approach to extend lifespan of WSN. The paper proposes an efficient clustering approach which chooses the best cluster-head with the help of bee colony approach. Through simulations, we demonstrate that our proposed solution uses the smallest amount of energy during the clustering procedure and chooses the best cluster-heads in contrast to advanced clustering approaches in WSN.

The scientific studies on smart grid in selected European countries

Smart grid is a power system consisting of many transmission and distribution systems subjected to an automation which are efficient, reliable and coordinated with each other. As a nature friendly technology, Smart grid come into prominence due to the increasing energy consumption and limited renewable energy sources around the world. In the near future, the use of renewable energy sources is not expected to grow rapidly; but the transmission and distribution systems will be enhanced by Smart grid technologies. Considering these significant benefits, the studies have been increased on Smart grid technologies to meet the energy requirement in each country. Herewith, the aim of this study is to analyse the scientific studies in developed European countries such as Italy, Germany, United Kingdom, France and Spain to find out the increment rate of the importance devoted to the Smart grid technologies in academicals manner. The scientific researches on Smart grid are achieved from the Web of Science database and the statistical analysis have been made by utilizing proper SQL queries in combination with Excel Power Pivot for these countries. The correlation between the scientific studies on smart grid and the virtual smart grid applications are also outlined for each selected country.

An Efficient Routing Protocol Adopting Enhanced Cluster Formation Technique Accompanied by Fuzzy Logic for Maximizing Lifetime of WSN

Wireless sensor networks is a system of multiple small sensors limited energy sources, used to sense any given sensing region of interest. In WSN, sensors might be required to work for a longer duration of time from the time of its deployment. Hence to optimize the utilization of energy at each node, we propose an algorithm, which can eventually enhance the lifetime and hence the reliability of the sensor nodes and the overall network. Here PSO based efficient clustering is performed and the appropriate selection of CH and SCH is done. The proposed approach outperforms the tradition F-LEAH algorithm. The result obtained through simulation shows that the proposed algorithm performs better than F-LEACH approach in terms of stability, reduced energy consumption at each node, less delay and drop at the BS and enhanced the lifetime of the network.