Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

Recently,energy harvesting wireless sensor networks(EHWSN)have increased significant attention among research communities.By harvesting energy from the neighboring environment,the sensors in EHWSN resolve the energy constraint problem and offers lengthened network lifetime.Clustering is one of the proficient ways for accomplishing even improved lifetime in EHWSN.The clustering process intends to appropriately elect the cluster heads(CHs)and construct clusters.Though several models are available in the literature,it is still needed to accomplish energy efficiency and security in EHWSN.In this view,this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks(CROC-SEHWSN)model.The presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in EHWSN.The CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization(RO)algorithm.Besides,the CROC-SEHWSN model derives a fitness function(FF)involving seven distinct parameters connected to WSN.To accomplish security,trust factor and link quality metrics are considered in the FF.The design of RO algorithm for secure clustering process shows the novelty of the work.In order to demonstrate the enhanced performance of the CROC-SEHWSN approach,a wide range of simulations are carried out and the outcomes are inspected in distinct aspects.The experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.

Comparison of Energy Harvesting Systems for Wireless Sensor Networks

Wireless sensor networks (WSNs) offer an attractive solution to many environmental,security,and process monitoring problems.However,one barrier to their fuller adoption is the need to supply electrical power over extended periods of time without the need for dedicated wiring.Energy harvesting provides a potential solution to this problem in many applications.This paper reviews the characteristics and energy requirements of typical sensor network nodes,assesses a range of potential ambient energy sources,and outlines the characteristics of a wide range of energy conversion devices.It then proposes a method to compare these diverse sources and conversion mechanisms in terms of their normalised power density.

Bidirectional secondary transmissions with energy harvesting in cognitive wireless sensor networks

To the existing spectrum sharing schemes in wireless-powered cognitive wireless sensor networks,the protocols are limited to either separate the primary and the secondary transmission or allow the secondary user to transmit signals in a time slot when it forwards the primary signal.In order to address this limitation,a novel cooperative spectrum sharing scheme is proposed,where the secondary transmission is multiplexed with both the primary transmission and the relay transmission.Specifically,the process of transmission is on a three-phase time-switching relaying basis.In the first phase,a cognitive sensor node SU1 scavenges energy from the primary transmission.In the second phase,another sensor node SU2 and primary transmitter simultaneously transmit signals to the SU1.In the third phase,the node SU1 can assist the primary transmission to acquire the opportunity of spectrum sharing.Joint decoding and interference cancellation technique is adopted at the receivers to retrieve the desired signals.We further derive the closed-form expressions for the outage probabilities of both the primary and secondary systems.Moreover,we address optimization of energy harvesting duration and power allocation coefficient strategy under performance criteria.An effective algorithm is then presented to solve the optimization problem.Simulation results demonstrate that with the optimized solutions,the sensor nodes with the proposed cooperative spectrum sharing scheme can utilize the spectrum in a more efficient manner without deteriorating the performance of the primary transmission,as compared with the existing one-directional scheme in the literature.

Advances in Triboelectric Nanogenerators for Blue Energy Harvesting and Marine Environmental Monitoring

Blue energy,which includes rainfall,tidal current,wave,and water-flow energy,is a promising renewable resource,although its exploitation is limited by current technologies and thus remains low.This form of energy is mainly harvested by electromagnetic generators(EMGs),which generate electricity via Lorenz force-driven electron flows.Triboelectric nano genera tors(TENGs)and TENG networks exhibit superiority over EMGs in low-frequency and high-entropy energy harvesting as a new approach for blue energy harvesting.A TENG produces electrical outputs by adopting the mechanism of Maxwell’s displacement current.To date,a series of research efforts have been made to optimize the structure and performance of TENGs for effective blue energy harvesting and marine environmental applications.Despite the great progress that has been achieved in the use of TENGs in this context so far,continuous exploration is required in energy conversion,device durability,power management,and environmental applications.This review reports on advances in TENGs for blue energy harvesting and marine environmental monitoring.It introduces the theoretical foundations of TENGs and discusses advanced TENG prototypes for blue energy harvesting,including TENG structures that function in freestanding and contact-separation modes.Performance enhancement strategies for TENGs intended for blue energy harvesting are also summarized.Finally,marine environmental applications of TENGs based on blue energy harvesting are discussed.

Cross Layered MAC Design for RF Energy Harvesting Sensor Network

The main research objective in wireless sensor networks (WSN) domain is to develop algorithms and protocols to ensure minimal energy consumption with maximum network lifetime. In this paper, we propose a novel design for energy harvesting sensor node and cross-layered MAC protocol using three adjacent layers (Physical, MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to re-energize the neighboring nodes using the radio frequency (RF) energy transmitted by the active nodes. This can be achieved by designing new energy harvesting sensor node and redesigning the MAC protocol. The results show that the proposed cross layer CL_EHSN improves the life time of the WSN by 40%.

Cost Minimization of Wireless Sensor Networks with Unlimited-lifetime Energy for Monitoring Oil Pipelines

Cyber-physical-system (CPS) has been widely used in both civil and military applications. Wireless sensor network (WSN) as the part and parcel of CPS faces energy problem because sensors are battery powered, which results in limited lifetime of the network. To address this energy problem, we take advantage of energy harvesting device (EHD) and study how to indefinitely prolong oil pipeline monitoring network lifetime by reasonable selecting EHD. Firstly, we propose a general strategy worst case-energy balance strategy (WC-EBS), which defines worst case energy consumption (WCEC) as the maximum energy sensor node could expend for oil pipeline monitoring WSN. When the energy collected by EHD is equal or greater than WCEC, network can have an unlimited lifetime. However, energy harvesting rate is proportional to the price of EHD, WC-EBS will cause high network cost. To reduce network cost, we present two optimization strategies, optimization workloadenergy balance strategy (OW-EBS ) and optimization first nodeenergy balance strategy (OF-EBS). The main idea of OW-EBS is to cut down WCEC by reducing critical node transmission workload; OF-EBS confirms critical node by optimizing each sensor node transmission range, then we get the optimal energy harvesting rate in OF-EBS. The experimental results demonstrate that OF-EBS can indefinitely extend network lifetime with lower cost than WC-EBS and OW-EBS, and energy harvesting rate P in each strategy satisfies POF-EBS ≤POW-EBS ≤PWC-EBS. © 2014 Chinese Association of Automation.

Power Allocation for Energy Harvesting in Wireless Body Area Networks

Wireless Body Area Networks(WBANs) are expected to achieve high reliable communications among a large number of sensors.The outage probability can be used to measure the reliability of the WBAN.In this paper,we optimize the outage probability with the harvested energy as constraints.Firstly,the optimal transmit power of the sensor is obtained while considering a single link between an access point(AP) located on the waist and a sensor attached on the wrist over the Rayleigh fading channel.Secondly,an optimization problem is formed to minimize the outage probability.Finally,we convert the non-convex optimization problem into convex solved by the Lagrange multiplier method.Simulations show that the optimization problem is solvable.The outage probability is optimized by performing power allocation at the sensor.And our proposed algorithm achieves minimizing the outage probability when the sensor uses energy harvesting.We also demonstrate that the average outage probability is reduced with the increase of the harvested energy.

Combined spatial-temporal energy harvesting and relay selection for cognitive wireless powered networks

In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.

Distributed Algorithms for Maximizing Lifetime in Clustered Wireless Sensor Networks Using Energy-harvesting Relay Nodes

Motivated by recent developments in wireless sensor networks(WSNs),we present distributed clustering algorithms for maximizing the lifetime of WSNs,that is,the duration until the first node dies.We study the joint problem of prolonging network lifetime by introducing clustering techniques and energy-harvesting(EH)nodes.First,we propose a distributed clustering algorithm for maximizing the lifetime of clustered WSN,which includes EH nodes,serving as relay nodes for cluster heads(CHs).Second,graph-based and LP-based EH-CH matching algorithms are proposed which serve as benchmark algorithms.Extensive simulation results show that the proposed algorithms can achieve optimal or suboptimal solutions efficiently.

Approximation Designs for Energy Harvesting Relay Deployment in Wireless Sensor Networks

Energy harvesting technologies allow wireless devices to be recharged by the surrounding environment, providing wireless sensor networks (WSNs) with higher performance and longer lifetime. However, directly building a wireless sensor network with energy harvesting nodes is very costly. A compromise is upgrading existing networks with energy harvesting technologies. In this paper, we focus on prolonging the lifetime of WSNs with the help of energy harvesting relays (EHRs). EHRs are responsible for forwarding data for sensor nodes, allowing them to become terminals and thus extending their lifetime. We aim to deploy a minimum number of relays covering the whole network. As EHRs have several special properties such as the energy harvesting and depletion rate, it brings great research challenges to seek an optimal deployment strategy. To this end, we propose an approximation algorithm named Effective Relay Deployment Algorithm, which can be divided into two phases: disk covering and connector insertion using the partitioning technique and the Steinerization technique, respectively. Based on probabilistic analysis, we further optimize the performance ratio of our algorithm to (5 + 6/K) where K is an integer denoting the side length of a cell after partitioning. Our extensive simulation results show that our algorithm can reduce the number of EHRs to be deployed by up to 45% compared with previous work and thus validate the efficiency and effectiveness of our solution.

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WSNs may comprise thousands of Internet of Things(IoT)devices to sense and collect data from its surrounding,process the data and take an automated and mechanized decision.On the other side the proliferation of these devices will soon cause radio spectrum shortage.So,to facilitate these networks,we integrate Cognitive Radio(CR)functionality in these networks.CR can sense the unutilized spectrum of licensed users and then use these empty bands when required.In order to keep the IoT nodes functional all time,continuous energy is required.For this reason the energy harvested techniques are preferred in IoT networks.Mainly it is preferred to harvest Radio Frequency(RF)energy in the network.In this paper a region based multi-channel architecture is proposed.In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region.The Secondary User(SU)that are the licensed user is IoT enabled with Cognitive Radio(CR)techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy.To harvest energy efficiently and to reduce the energy consumption during sensing,the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel.From the experimental analysis,it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel.We also show that channel load can be highly reduced and channel utilization is proved to be more proficient.Thus,this proves the proposed architecture cost-effective and energy-efficient.

Ultra-Low Power High-Efficiency UHF-Band Wireless Energy Harvesting Circuit Design and Experiment

In this paper,an ultra-low power high-efficiency ultra-high frequency(UHF)-band wireless energy harvesting circuit based on the diode SMS7360 is designed and experimentally demonstrated,being operated in all released Global System for Mobile Communications(GSM)bands in China(GSM900 band:0.87-0.96 GHz and GSM1800 band:1.71-1.86 GHz).This UHF-band wireless energy harvesting circuit can harvest energy at 0.87-0.96 GHz and 1.71-1.86 GHz bands simultaneously in outdoor or indoor environment.The test results show that a radio-frequency(RF)-to-direct-current(DC)conversion efficiency in the range of 20%-63.2% is obtained for an available input power of-22 dBm to 1 dBm in GSM900 band and that in the range of 13.8%-55.5% is achieved for an available input power of-22 dBm to 3 dBm in GSM1800 band.The harvested RF energy is converted into DC energy and be stored in a 6.8 mF super capacitor through the energy management circuit.This super capacitor’s capacity is more than 20 mJ,which can meet the demand of high-speed broadband wireless communication transceivers.This ultra-low power highefficiency UHF-band wireless energy harvesting circuit could be used to achieve the low power wireless sensor network node(tag).

Scalable Distributed State Estimation over Binary Sensor Networks with Energy Harvester

This paper deals with distributed state estimation problem for discrete time-varying systems over binary sensor networks,where every binary sensor is equipped with an energy harvester.The input of every binary sensor considers the randomly occurring missing measurements.The differences between the real and estimated inputs of binary sensor are employed to derive useful information in order to address the insufficient information for estimation purpose.The information from neighboring nodes is transmitted only if its energy level is positive,where a random variable is introduced to formulate the energy level.By means of the available information,distributed estimator is constructed for each binary sensor and the desirable performance constraints is given for the dynamic characteristics of estimation errors within anite time horizon.Sucient conditions are established for the existence of desired distribution estimation quantities through local performance analysis methods.Also,the desired distributed estimator gains are calculated recursively,which means the desirable scalability.Ultimately,the viability and efficiency of the distributed scheme are exhibited through a practical illustration.

An Optimal Lifetime Utility Routing for 5G and Energy-Harvesting Wireless Networks

Harvesting energy from environmental sources such as solar and wind can mitigate or solve the limited-energy problem in wireless sensor networks. In this paper, we propose an energy-harvest-aware route-selection method that incorporates harvest availability properties and energy storage capacity limits into the routing decisions. The harvest-aware routing problem is formulated as a lin- ear program with a utility-based objective function that balances the two conflicting routing objectives of maximum total and maxi- mum minimum residual network energy. The simulation results show that doing so achieves a longer network lifetime, defined as the time-to-first-node-death in the network. Additionally, most existing energy-harvesting routing algorithms route each traffic flow independently from each other. The LP formulation allows for a joint optimization of multiple trafic flows. Better residual energy statistics are also achieved by such joint consideration compared to independent optimization of each commodity.

Improving throughput in SWIPT-based wireless multirelay networks with relay selection and rateless codes

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer(SWIPT)-based multi-relay network with a direct link.To achieve high throughput in the network,a novel protocol is first developed,in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission(SRS-CT)mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes(RCs).Then,under this protocol,an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode.The formulated problem is difficult to solve because not only does the noncausal Channel State Information(CSI)cause the problem to be stochastic,but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation.Assuming that noncausal CSI is available,the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming,where the complicated energy state evolution issue is addressed by a layered optimization method.Then,based on a finite-state Markov channel model and assuming that CSI statistical properties are known,the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case.Finally,a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties.The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40%throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

An Efficient Energy Aware Routing Mechanism for Wireless Body Area Networks

The accelerated development of wireless network technology has resulted in the emergence of Wireless Body Area Network(WBAN),which is a technology commonly used in the medical field.WBAN consists of tiny sensor nodes that interconnect with each other and set in the human body to collect and transmit the patient data to the physician,to monitor the patients remotely.These nodes typically have limited battery energy that led to a shortage of network lifetime.Therefore,energy efficiency is considered one of the most demanding challenges in routing design for WBAN.Many proposed routing mechanisms inWBAN did not cover the source node energy and energy harvesting techniques.Therefore,this study proposes an Efficient Energy Aware Routing(EEAR)mechanism.This paper constructs a path cost function that considers three parameters:residual energy,number of hops to the sink,and the distance between the nodes.Besides,data aggregationwith filtration and hybrid energy harvesting technique are used to extend the network lifetime,reduce the network traffic load,andmaintain the source node energy.Extensive simulations using MATLAB have been performed to evaluate the performance of the proposed mechanism.EEAR is contrasted with the two latest schemes,called Priority-based Congestion-avoidance Routing Protocol(PCRP)and Energy Efficient Routing Protocol(EERP).The results show the significant performance of theEEARmechanism in terms of network lifetime,residual energy,network stability,and throughput.

Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

In recent years,high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year.During the machining process,the high-end equipment failure may have a great impact on the product quality.It is necessary to monitor the status of equipment and to predict fault diagnosis.At present,most of the condition monitoring devices for mechanical equipment have problems of large size,low precision and low energy utilization.A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed.Based on rotor sensing technology,a sensor is made to mount on the tool holder and build the related circuit.Firstly,the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 Vfor the subsequent circuit.The lithium battery supplies the system with additional power and monitors’the power of the energy storage circuit in real-time.Secondly,a three-axis acceleration sensor is used to collect,analyze and filter a series of signal processing operations of the vibration signal in the environment.The signal is sent to the upper computer by wireless transmission.The host computer outputs the corresponding X,Y,and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring.The KEIL5 platform is used to develop the system software.The small-size piezoelectric vibration sensor with high-speed,high-energy utilization,high accuracy,and easy installation is used for spindle monitoring.The experiment results show that the sensor system is available and practical.

Recharging Sensor Nodes Using Implicit Actor Coordination in Wireless Sensor Actor Networks

Wireless sensor actor networks are composed of sensor and actor nodes wherein sensor nodes outnumber resource-rich actor nodes. Sensor nodes gather information and send them to a central node (sink) and/or to actors for proper actions. The short lifetime of energy-constrained sensor nodes can endanger the proper operation of the whole network when they run out of power and partition the network. Energy harvesting as well as minimizing sensor energy consumption had already been studied. We propose a different approach for recharging sensor nodes by mobile actor nodes that use only local information. Sensor nodes send their energy status along with their sensed information to actors in their coverage. Based on this energy information, actors coordinate implicitly to decide on the timings and the ordering of recharges of low energy sensor nodes. Coordination between actors is achieved by swarm intelligence and the replenishment continues during local learning of actor nodes. The number of actors required to keep up such networks is identified through simulation using VisualSense. It is shown that defining the appropriate number of actor nodes is critical to the success of recharging strategies in prolonging the network lifetime.

An Extension to ns-3 for Simulating Mobile Charging with Wireless Energy Transfer

Many theoretical derivation of the energy model requires extensive simulation in Internet of Things (IoT). Network Simulator 3 (ns-3) provides a simulation platform for various experimental studies including energy harvest.However, the function of charge schedule and wireless energy transfer model is not yet implemented. To address this problem, in this paper we propose an extension to ns-3 for simulating mobile charging with wireless energy transfer.First, we utilize a WET Harvest Class to harvest energy from the environment and a Charge Schedule Class for the mobile charger to choose the optimal node charging in the charging request queue in ns-3. Second, we use Charge Energy Model to judge what the mobile charger will do next when the energy of current node is higher or lower than energy threshold. Evaluation results show that our improvements are feasible and helpful with charge schedule and energy model in ns-3.

基于SWIPT的能量收集WSN吞吐量性能分析及优化

针对能量收集无线传感器网络(wireless sensor network,WSN)中的两跳多中继传输问题,构建无线射频能量站(power beacon,PB)辅助的能量收集无线携能通信(simultaneous wireless information and power transfer,SWIPT)中继模型.在中继节点具有捕获源节点、环路自干扰和PB信号能量的特性下,推导目的节点采用选择式合并(selection combining,SC)、最大比合并(maximal ratio combining,MRC) 2种不同接收策略下的中断概率和吞吐量,继而在保障通信服务质量(quality of service,QoS)、PB发射功率、能量转化效率等多约束条件下,提出一种以吞吐量最大化为目标的联合优化时隙切换因子与功率分配因子的中继选择算法.仿真和数值结果显示:PB发射功率、时隙切换因子、天线数目、功率分配因子等参数对系统中断概率和吞吐量性能影响显著;当给定PB发射功率为6 dBW,天线数目为3根时,与随机中继选择算法和最大最小中继选择算法相比,本文算法在SC策略下的系统吞吐量增益分别为0.29、0.15 bit/(s·Hz),MRC策略下的吞吐量增益分别为0.32、0.16 bit/(s·Hz).