Lifetime Of Sensor Nodes Research Articles

IoT BASED SMART AND EFFICIENT WIND TURBINE MONITORING SYSTEM

Wind Turbine industry has the improved latest generation of Wind turbines with bigger flexible blades, high tower, Good efficiency & low cost repairing in all platforms of wind turbines from Small wind mills to Ocean wind turbines. The Control centre is responsible for Monitoring and Controlling wind turbines in wind power farms. Various parameters like Oil level, Gas leakage, air pressure, vibrations & linear velocity, environmental condition like rain & humidity are to be monitored and controlled for proper working of the wind turbines. In the proposed work, smart and efficient turbine network architecture is designed to automate this process. The aim of the proposed work is to monitor the different parameters of the turbine using respective sensors. The acquired sensor data are uploaded to the cloud via WiFi module for online monitoring and further data analysis. IFTTT Server of Adafruit io cloud is used to send the warning notification of the critical sensor value to the concerned person. Also the sensor node life time is taken care by implementing a proposed compression algorithm in each node that reduces the amount of data transmitted and thereby the energy consumed during transmission.

An Integrated Piezoelectric Sensor Based Energy Efficient Transmission Using Base-Station Controlled Dynamic Clustering Protocol

A piezoelectric sensor based energy efficient transmission using base station controlled dynamic clustering protocol (BSCDCP) is proposed in this work. The piezoelectric sensor design and simulation is analyzed with the help of COMSOL finite element modeling and location based energy efficient routing is estimated by BSCDCP hierarchical routing techniques. The sensor voltage 5.2 V–1 g acceleration and electrical load impedance 12 Ω is distributed uniform voltage to all the nodes and analyze piezoelectric sensor performance based on BSCDCP protocol. The number of iterations the life time of sensor node is increasing with the help of piezoelectric sensor. The numerical results show that 95% accuracy when increase the distance and number of nodes also it suggest to improve the life time of piezoelectric sensor. By using BSCDCP protocol, the optimize piezoelectric sensor frequency and generated voltage is enhance and time duration 0.5 µs is achieved and simulation done with number of nodes, which is very fast compared to existing protocol techniques. The overall protocol is best suitable for energy efficient routing for large volume with less latency and accuracy.

Design and Implementation of a Thermoelectric Energy Harvester with MPPT Algorithms and Supercapacitor

Sensor nodes currently are principally powered by batteries, however batteries life are finite. Energy harvesting aims to increase the lifetime of sensor nodes. This system takes advantage of environmental conditions in order to use or store the energy harvested by transducers, such as thermoelectric generators. In this paper, a thermoelectric energy harvesting system based in a Boost converter with four different maximum power point tracking (MPPT) algorithms that store energy in a supercapacitor is implemented . Perturb and Observe (PO), Incremental Conductance (INC), Open Circuit Voltage (OCV) and Short Circuit Current (SCC) algorithms were tested to improve the designed circuit. Finally, OCV algorithm resulted being the fastest to charge the supercapacitor.

Interface Circuits for Piezoelectric Energy Harvesting: A review of designs and methods

The rapid advancement in IC technology has enabled wireless sensor networks that are widely used in applications like health care, automobiles, smart buildings, and the predictive maintenance of structures [1] , [2] . In these settings, the use of batteries limits the lifetime of sensor nodes and results in high costs in maintenance. Therefore, harvesting ambient energy provides a feasible solution to self-sustainability.

Classifier-Based Data Transmission Reduction in Wearable Sensor Network for Human Activity Monitoring

The recent development of wireless wearable sensor networks offers a spectrum of new applications in fields of healthcare, medicine, activity monitoring, sport, safety, human-machine interfacing, and beyond. Successful use of this technology depends on lifetime of the battery-powered sensor nodes. This paper presents a new method for extending the lifetime of the wearable sensor networks by avoiding unnecessary data transmissions. The introduced method is based on embedded classifiers that allow sensor nodes to decide if current sensor readings have to be transmitted to cluster head or not. In order to train the classifiers, a procedure was elaborated, which takes into account the impact of data selection on accuracy of a recognition system. This approach was implemented in a prototype of wearable sensor network for human activity monitoring. Real-world experiments were conducted to evaluate the new method in terms of network lifetime, energy consumption, and accuracy of human activity recognition. Results of the experimental evaluation have confirmed that, the proposed method enables significant prolongation of the network lifetime, while preserving high accuracy of the activity recognition. The experiments have also revealed advantages of the method in comparison with state-of-the-art algorithms for data transmission reduction.

TCHCN: Trust Computation for Hierarchical Clustering Network to Improve Network Lifetime in Wireless Sensor Network

Network Lifetime of sensor node plays a fundamental role in Wireless Sensor Networks, since they drain out energy during the communication. The hierarchical networks assist in hindering energy loss by exchanging the information at various levels. The Hierarchical levels formed avoid overburdening of single level cluster zones and helps the network to retain energy of cluster level heads. Malicious attack disturbs the regular functionality of a routing algorithm and deviates QoS performance in the network. The existing LEACH-Mobile protocol adopts low energy clustering techniques but, falls short in providing security of the network when there is malicious attack. The proposed Trust Computation for Hierarchical Clustering Network protocol proves itself to be trustworthy by having various trust measuring metrics. It enhances the lifetime by adopting low energy hierarchical protocol and shows improvement of 12% in terms of energy consumption.

Energy efficient CLB approach to find optimum modulation scheme in wireless rechargeable sensor networks

There has been a lot of improvement in energy savings in wireless sensor networks (WSNs) resulting in increased lifespan of sensor nodes. Consequently, WSNs has gained its widespread use in various fields like medical services, security, home automation, environmental monitoring, and lot more. However, gaining successes leads to extensive acceptance of WSNs particularly at the places where human beings cannot reach. Being most acceptable, it still faces number of challenges like: battery constraint, low speed communication and harsh environment. Many researchers have come up with innovative ideas or energy management approaches to prolong the lifetime of hungry sensor nodes and to make the network more reliable and operational. In this paper, the CLB (Charging with Load Balancing) scheme is firstly proposed based on Laser power Beaming (LPB,) then it is implemented on various modulation schemes to test the optimum and robust modulation type for Wireless Rechargeable Sensor Networks (WRSNs).

The Impact of Deployment Pattern and Routing Scheme on the Lifetime in Multi-Sink Wireless Sensor Network

Extensive use of sensor and actuator networks in many real-life applications introduced several new performance metrics at the node and network level. Since wireless sensor nodes have significant battery constraints, therefore, energy efficiency, as well as network lifetime, are among the most significant performance metrics to measure the effectiveness of given network architecture. This work investigates the performance of an event-based data delivery model using a multipath routing scheme for a wireless sensor network with multiple sink nodes. This routing algorithm follows a sink initiated route discovery process with the location information of the source nodes already known to the sink nodes. It also considers communication link costs before making decisions for packet forwarding. Carried out simulation compares the network performance of a wireless sensor network with a single sink, dual sink, and multi sink networking approaches. Based on a series of simulation experiments, the lifetime aware multipath routing approach is found appropriate for increasing the lifetime of sensor nodes significantly when compared to other similar routing schemes. However, energy-efficient packet forwarding is a major concern of this work; other network performance metrics like delay, average packet latency, and packet delivery ratio are also taken into the account.

Hierarchical Protocol Based on Recursive Clusters for Smart Parking Applications Using Internet of Things (IOT)

With the increasing number of vehicles, the management of parking spaces in cities is becoming increasingly important in improving the quality of life and combating air pollution. Indeed, finding a parking space at peak times and in congested areas of the population becomes a huge challenge for drivers. To remedy this problem, most modern cities have smart parking. The equipment of these smart parking is mainly based on the implementation of wireless sensor networks (WSN) to monitor, track, and collect real-time information on the occupancy status of each parking space. This information is then made available to drivers who are looking for an available parking space. However, sensor nodes have limitations in terms of energy and communication that affect the performance and quality of the wireless sensor network. Therefore, the design of a self-organization protocol for WSN that minimizes power consumption and maximizes the longevity of the WSN network must be taken into account when implementing and developing a sustainable and viable intelligent parking system. In this paper, we propose a protocol for self-organization of wireless sensor networks (WSN) for the management of parking spaces in outdoor and urban car parks. This protocol is based on building clusters using ZigBee transmission technology for multihop communication. Each sensor node will be installed in the ground of each parking space to monitor its availability by sending the empty or busy state of that space to the gateway using cluster head nodes (CHs). This approach has a robust and efficient self-organizing algorithm that minimizes energy dissipation and increases the lifetime of sensor nodes and the WSN network. The simulation results show that parking management systems in outdoor and urban car parks using the self-organization protocol presented are efficient and sustainable in terms of energy consumption, reliability of data transmission, and the longevity of the WSN network compared to other existing parking systems that use different self-organizing protocols for wireless sensor networks.

Genetic spider monkey‐based routing protocol to increase the lifetime of the network and energy management in WSN

SummaryWireless sensor networks (WSNs) include large distributed nodes in the sensing field. However, the sensor nodes may die due to energy deficiency as they are situated in a hostile environment. Therefore, an energy‐efficient WSN routing protocol is necessary in order to better accommodate the various environmental conditions. In this paper, we have proposed a new Energy‐Efficient Genetic Spider Monkey‐based Routing Protocol (EGSMRP) to improve the stability and lifetime of sensor nodes. The operation of EGSMRP is classified into two stages: (i) setup phase and (ii) steady‐state phase. In the setup phase, GSMO‐based cluster head selection procedure is done. In this phase, the base station utilizes the GSMO algorithm as a device to generate energy‐efficient clusters. Followed with this, the steady‐state phase solves the load balancing issue by utilizing the intracluster data broadcast and dual‐hop intercluster broadcasting algorithm. Thereby, the proposed EGSMRP protocol has shown the energy‐based opportunistic broadcasting with reduced control overhead. Simulation is performed in various conditions to evaluate the effectiveness of the proposed EGSMRP protocol using different metrics such as throughput, control overhead, energy consumption, end‐to‐end delay, and network lifetime. From the simulation results, it was evident that EGSMRP has achieved a higher performance compared to other traditional approaches such as EBAR, MCTRP, IEEMARP, HMCEER, and EFTETRP.

INVESTIGATING THE EFFECT OF THE SENSOR NODE PARAMETERS ON ITS LIFETIME

The work proposed in this paper investigates the early death of the wireless sensor node owing to the limitations of the electrochemistry properties of the battery. Further, we studied the impact of the detection node parameters on the battery life of the detection node. Better choices for the sampling interval and the transmission power are found to mitigate the shortened lifetime of the battery. With the above values, the observed enhancement in the sensor node lifetime is around 35.14%.

Energy-distance & degree: multi-objective based optimized clustering and route discovery in wireless sensor network

Network lifetime (NL) and energy preserving of sensor node is the most vital problem in the deployment of wireless sensor networks (WSNs ). An approach of cluster based path establishment shows the way in which cluster heads (CHs ) collect the information with each other and transfers into the sink (nS ) via multi-hop routing. In this paper, we present path establishment and CHs selection through Energy-Distance and Degree (EDD) based clustering (EDDCH) and route discovery (EDDRD). The networks divided into multiple groups and each CHs support to each other for data forwarding also the smaller sized clusters closest to the nS and huge size clusters remote from the S increases the lifetime of the network. The simulation results compared with the existing route optimization named as Particle Swarm Optimization (PSO) in terms of residual energy (RE ) and network lifetime (NL ).

Traffic Models for Energy Harvesting Based Wireless Sensor Networks

Background: Energy consumption is an important parameter in wireless sensor networks since it affects the lifetime of sensor nodes. Methods: Battery powered wireless sensor networks cannot sustain for long hence impractical for real-time applications. With energy harvesting and relevant protocols, this issue of extending the lifetime of nodes has been solved largely. The performance can be enhanced further if proper traffic analysis and modeling are done as a proactive approach. Results: A proper understanding of the traffic dynamics provides a base for further network optimization and detection of anomalies within the network. Much of the reported work in energy harvesting based WSN till now, is to design the efficient protocols only, traffic analysis and modeling is the ignored parameter. In this paper traffic models appropriate for the energy harvesting based system have been analyzed and their performance is evaluated for a MAC protocol. Conclusion: Results show that Weibull distribution is the most useful model for traffic modeling in energy harvesting based wireless sensor networks.

ELPC-Trust Framework for Wireless Sensor Networks

Wireless Sensor Network (WSN) and its security concern play a vital part in its effecting functioning. WSN routing layer attacks pose a great threat to its functionality, whereas if a situation arises in which multiple attacks co-exist, then the scenario will become worse. In such cases the reliability of the network deployed is greatly questionable. Thus an Intrusion detection cum Trust based framework is mandatory to detect such co existing malicious activities in order to maintain the network reliability. Energy packed Cluster heads and sink nodes are utilized for this kind of trust computation process. To achieve this, an energy based abnormality detection of malicious nodes is proposed, upon which based on the packet rate and the lifetime of sensor nodes a trust value is computed. The trust framework involves two phases namely Threat Detection phase which performs attack categorization based on Energy, Packet Count and Z scores followed by the second phase which computes the trust values for each node. Trust scores are computed based on the intensity of the attack in terms of their network performance degradation. Attacks such as Gray hole, Black hole, Wormhole, Flooding and Data Modification attacks are addressed. Data Modification attacks are detected uniquely based on the Z scores values of the sensed data set and upon the location of the nodes. If any node is found to consume abnormal energy either below or above certain threshold, identified nodes are categorized into two groups based on their threshold. Hierarchical decision making is introduced, which implies only the abnormal energy consuming nodes (among the total sensor nodes deployed in the network) are considered for further packet count based attack categorization. This way we can reduce the computational overhead of traditional trust models in which each node is checked for its reliability against multiple trust factors. Upon detecting the attacks and computing the trust values of nodes, only the nodes which have a nominal trust value are included in the routing process. Simulations were carried out in NS2 Mannasim Framework with static and mobile sensor nodes. Proposed Energy-Lifetime-Packet Count (ELPC)-Trust framework was tested under five different types of attack scenarios in a co-existing manner. Performance of the network by including the proposed ELPC trust and by ignoring the detected malicious nodes increases the throughput by 500 and PDR by 40% when compared with the attack scenario. But on the other hand introduces a delay of 0.5 seconds. Network Performance is improved in case of static networks. Under mobile scenarios proposed ELPC trust incurs high amount of delay.

Self-heat controlling energy efficient OPOT routing protocol for WBAN

Recent technological advancements in miniaturization of sensor and wireless communication lead to development of Wireless Body Area Networks (WBAN). It is similar to Wireless Sensor Networks but mainly focuses on health care applications to monitor the health condition of patient continuously. It consists of implantable and wearable computing devices placed inside or outside the surface of human body for sensing and data communication. Due to continuous operation, the sensor node introduces electromagnetic radiations which causes damage to delicate human tissues as well as degrades the performance of the network. In addition, WBAN data are sensitive to delay and it is necessary to send critical patient data to the remote server in a timely manner to protect patient’s life. However, alternating the routing path of critical data leads to collision, packet loss, high power consumption, maximum delay and reduced network life time. In this paper, Optimum Path Optimum Temperature Routing Protocol is introduced to address the above issues. The proposed protocol chooses optimum routing path by determining the temperature of sensor nodes and by defining two threshold limits (minimum and maximum). It also considers the critical data signals to be sent when the temperature of node exceeds the admissible threshold limit. The obtained simulation results are compared with conventional routing protocols and was analyzed that the proposed protocol has decreased delay, minimum energy, reduced power, uniform temperature distribution and maximum lifetime of sensor node.

An Energy-Efficient Message Scheduling Algorithm with Joint Routing Mechanism at Network Layer in Internet of Things Environment

The rapid procreation of internet of things (IoT) has invigorated massive research efforts with the purpose to save and use the lifetime of battery-powered sensor nodes which ultimately increases the overall network lifetime. The erroneous and faulty states of these networks are due to the high consumption of batteries in the processing and transmission of data by these nodes. This research focuses on message scheduling in an IoT environment where things/sensors are connected to make IoT groups, where each group has a designated broker whose duty is to delivers the messages coming from the group members to the ultimate sink of the sensed data. At broker a message scheduler operating to decides which message goes first. This algorithm proposed cross layer architecture at application level and network level. The residual energy of the node and its distance is considered as a parameter while selecting broker among all nodes in new proposed methods as compared to traditional LEACH. The proposed method provides better results in terms of number of live nodes, network life time, number of brokers and total dissipated energy while stabilizing the response time of the messages in addition to it.

ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks

Energy conservation is the main issue in wireless sensor networks. Many existing clustering protocols have been proposed to balance the energy consumption and maximize the battery lifetime of sensor nodes. However, these protocols suffer from the excessive overhead due to repetitive clustering resulting in high-energy consumption. In this paper, we propose energy-aware cluster-based routing protocol (ECRP) in which not only the cluster head (CH) role rotates based on energy around all cluster members until the end of network functioning to avoid frequent re-clustering, but also it can adapt the network topology change. Further, ECRP introduces a multi-hop routing algorithm so that the energy consumption is minimized and balanced. As well, a fault-tolerant mechanism is proposed to cope up with the failure of CHs and relay nodes. We perform extensive simulations on the proposed protocol using different network scenarios. The simulation results demonstrate the superiority of ECRP compared with recent and relevant existing protocols in terms of main performance metrics.

An efficient solar energy harvesting system for wireless sensor network nodes

A wireless sensor network is a network of spatially deployed sensor nodes with constrained energy resources. This research paper focusses to design a robust solar energy harvesting system to enhance life time of sensor nodes. Proposed solar energy supply system mainly consists of a solar panel, rechargeable battery and a control circuit. To obtain sufficient voltage to charge battery, electrical energy generated through panel is boosted by boost converter. Different sensor nodes are supplied with energy from this system. An inverter is also designed for AC applications. Complete structure of the system, design of each module, details of implementation and evaluation of performance are explained in this work. Experimental results show that this compact, self-sufficient system enables outdoor based wireless sensor network nodes to operate successfully.

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

With the advancement and implementation of marine strategies in various countries, it is of great significance to collect marine data by using underwater acoustic sensor networks (UWA-SNs). Due to the difficulties in charging or replacing batteries, how to prolong the lifetime of underwater sensor nodes is one of the key problems to be solved. In this paper, we propose a new energy consumption balanced protocol, named as dynamic clustering K-means (DC-K-means) based simplified balanced energy adaptive routing (S-BEAR), to prolong the lifetime of a UWA-SN by balancing the energy consumption of underwater sensor nodes and avoiding the energy hole. First, by considering the residual energy of the underwater sensor nodes, we propose the DC-K-means algorithm to cluster the underwater sensor nodes and optimize the topology of data transmission among underwater sensor nodes so that the overall energy consumption of the system can be reduced and the problem of energy consumption balance of underwater sensor nodes can be solved. Then, the S-BEAR protocol is designed for multi-hop transmissions, where the data collected by each cluster head is transmitted to the surface receiving terminal equipment, and thus further balances and saves the energy consumption of the system. The simulation results demonstrate that the proposed DC-K-means based S-BEAR scheme has the advantages of more balanced energy consumption among sensor nodes and higher overall residual energy as compared to the state-of-the-art schemes.

A reconfigurable hardware platform for low-power wide-area wireless sensor networks

Low power, large-area wireless sensor networks (WSNs) have been experiencing rapid growth in a wide range of applications, such as environmental monitoring applications and natural disaster early warning systems. The WSN consists of numerous nodes with sensing, computation, actuation, and radio communication capabilities. Dynamically reconfigurable hardware and context-aware operation to optimize performance and functionality and to prolong the lifetime of sensor nodes are critical goals in the design of distributed sensing systems, especially for battery-based systems being deployed in complex geographic areas where are hard to approach. In recent years, Programmable System-on-Chip (PSoC) technology is emerging as an efficient solution for achieving the dynamic hardware reconfiguration of a sensor node in a single chip. That aims at optimizing the use of resources, minimizing of energy waste, and system size according to the requirements of the applications. This paper presents the implementation of a configurable hardware platform for remote sensing systems based on PSoC and LoRa technology. The proposed hardware design stands out for high performance, ultralow-power, providing long-range communication as well as reconfigurable interfaces in communicating and manipulating with various types of sensors and actuators. The experiments to evaluate the functional requirements and energy consumption of the design were investigated with positive results.