Showing papers on "Sensor node published in 2022"

Fundamentals of Wireless Sensor Networks

Abstract: The continuous technological upgradations in the RF (radio frequency), processors, nanotechnology, and microelectromechanical systems (MEMS) domains have fostered the growth of wireless sensor networks (WSN), which in turn allowed to develop a wide range applications based on it, for instance, the technological breakthrough in the semiconductor industry stimulated to produce low-power, low-cost, and small-sized processors with high computational capacities. Speaking in more clear words, the miniaturization of sensing and computing devices enabled the development of tiny, low-cost, and low-power sensors, controllers, and actuators. Basically WSNs consist of a large number of tiny and low-cost sensor nodes that are networked via low-power wireless communication links. These networks allow to closely observe ambient environment of interest at an economical cost much lower than other possible technological solutions. Each sensor node in WSN has sensing, communication, and computation capabilities. By exploiting appropriate advanced mesh networking protocols, these nodes form a sea of connectivity that covers the physical environmental area under observation. In WSN the transmitting node opt out possible communication paths by hopping sensed data of interest from node to node toward its destination. Although the capability of single sensor node is minimal, the composition of hundreds or thousands of such nodes offers very high new technological possibilities for wide variety of applications. The power of WSN lies in the possibility of heavy deployment of large numbers of tiny nodes, which can assemble and configure on their own. Stating in simple words, these nodes have networking capability, which facilitates coordination, cooperation, and collaboration among them to meet the requirements of the underlying application. The WSN can also provide a robust service in hostile or inaccessible environments, wherein human intervention may be too dangerous or almost not possible. This new technology is exciting with unlimited potential for numerous application areas, including environmental, medical, military, transportation, entertainment, crisis management, disaster relief operations, homeland defense, and smart spaces. It is envisioned that in the near future the WSN will be an integral as well as essential aspect of our lives.

Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks

Abstract: : The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols.

A Cost-Efficient Radiation Monitoring System for Nuclear Sites: Designing and Implementation

Abstract: Radiation monitoring is essential for examining and refraining the unwanted situations in the vicinity of nuclear plants as high levels of radiation are quite dangerous for human beings. Meanwhile, Wireless Sensor Networks (WSNs) are proved to be an auspicious candidate to address that issue. Actually, WSNs are pretty beneficial to monitor an area with the aim of avoiding undesirable situations. In this paper, we have designed and implemented a cost-efficient radiation and the temperature monitoring system. We have used ZigBee to develop the sensor nodes, and the sensor nodes are instilled with the radiation and the temperature sensors. In addition, the Geiger Muller Tube (GM Tube), which is usually a reliable detector to monitor nuclear sites, is used to monitor the radiations. The designed system consists of two sensor nodes and the main node. The experimental results validate the designed system, where the communication between the nodes and the main node along with the inter-nodal communication are examined in order to ensure the smooth-running operation of the designed system.

Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm

Abstract: Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance in a gas sensor system using Convolutional Neural Network (CNN) with a smaller number of gas sensor elements. We have identified redundant gas sensor elements in a gas sensor array and removed them to reduce the power consumption without significant deviation in the node’s performance. The inevitable variation in the performance due to removing redundant sensor elements has been compensated using specialized data pre-processing (zero-padded virtual sensors and spatial augmentation) and CNN. The experiment is demonstrated to classify and quantify the four hazardous gases, viz., acetone, carbon tetrachloride, ethyl methyl ketone, and xylene. The performance of the unoptimized gas sensor array has been taken as a “baseline” to compare the performance of the optimized gas sensor array. Our proposed approach reduces the power consumption from 10 Watts to 5 Watts; classification performance sustained to 100 percent while quantification performance compensated up to a mean squared error (MSE) of 1.12 × 10−2. Thus, our power-efficient optimization paves the way to “computation on edge”, even in the resource-constrained 6G-IoT paradigm.

Game Theory-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

Abstract: Energy efficiency is one of the critical challenges in wireless sensor networks (WSNs). WSNs collect and transmit data through sensor nodes. However, the energy carried by the sensor nodes is limited. The sensor nodes need to save energy as much as possible to prolong the network lifetime. This paper proposes a game theory-based energy-efficient clustering algorithm (GEC) for wireless sensor networks, where each sensor node is regarded as a player in the game. According to the length of idle listening time in the active state, the sensor node can adopt favorable strategies for itself, and then decide whether to sleep or not. In order to avoid the selfish behavior of sensor nodes, a penalty mechanism is introduced to force the sensor nodes to adopt cooperative strategies in future operations. The simulation results show that the use of game theory can effectively save the energy consumption of the sensor network and increase the amount of network data transmission, so as to achieve the purpose of prolonging the network lifetime.

A Batteryless RFID Sensor Architecture With Distance Ambiguity Resolution for Smart Home IoT Applications

Abstract: In this article, a novel batteryless wireless sensor design is proposed and demonstrated. The proposed passive wireless sensor node integrates a ultrahigh-frequency (UHF) radio-frequency identification (RFID) chip, a filter, and a reactive sensor to enable the reading of environmental conditions wirelessly, without increasing the complexity of a typical RFID chip and substantial loss of the read range. The sensor changes the phase of the reflected RFID signal based on the sensed parameter; whereas, the filter helps in resolving any phase ambiguity that may arise due to the placement of the node at different distances. The phase change is detected at the reader using a noncoherent IQ demodulator. The design can easily integrate any type of sensors, such as temperature, humidity, and water-level sensor. A flood sensor and a temperature sensor were used to demonstrate the performance of the proposed design in a home and office environment.

An energy-saving data aggregation method for wireless sensor networks based on the extraction of extrema points

Abstract: The wireless sensor network (WSN) has been among the fast-growing areas in recent years in different fields, like health applications, military applications, the operations of disaster relief, etc. In an unattended, even hostile environment, nodes in WSNs are commonly deployed. What is worse, these nodes are fitted with minimal resources for communication, computation, storage and battery. It is also impossible to guarantee the lifespan of WSNs without reducing their network performance. A massive volume of application-specific data is produced by WSNs. Such data must be processed and sent to the base station by sensor nodes, which is an expensive matter. As the resources of sensor nodes are constrained, the key challenges facing WSNs are effective data processing and energy conservation. To tackle those challenges, data aggregation can be used, which is a popular approach that filters redundant data in-network and speeds up the extraction of knowledge. In this paper, we propose an energy-saving data aggregation method for WSNs based on the extraction of extrema points (DAEP) to greatly minimize the energy consumption of each node and boost the higher lifespan of WSN. The efficiency of the proposed method was measured by performing multiple simulation experiments based on real sensor readings collected in Intel Berkeley laboratories and comparing the results achieved with some work in the literature. The results show the ability of the proposed method to reduce the load on the sensor nodes in terms of reducing the amount of transmitted data by up to 69-80%, energy consumed by 73-77% while maintaining an acceptable level of accuracy compared to some existing works.

E-Health Tracker: An IoT-Cloud Based Health Monitoring System

Abstract: Health Management and its Monitoring during Pandemic is one of the major issues in not only our country, but the whole world. People are losing their lives due to the ignorance of their body's vitals (symptoms or signs of any disease). It is really important for one to keep track of their health, not only for themselves but also for those around them as well. Keeping this in mind, a proposed system titled E-Health Tracker was designed and constructed. Using ESP8266 Node MCU Wi-Fi Module, DS18B20 Temperature sensor probe, MAX 30100 Pulse Oximetry sensor and DHT-11 Temperature and Humidity sensor. A 0.96″ OLED screen is used to display all the readings from the sensors processed by the Node MCU ESP8266. In addition to that an Open-Source IOT Web API service called ThingSpeak which allows to aggregate, visualize, and analyze live data streams in the Cloud is utilized. A user can create a Channel by signing up and naming the Channel along with the Fields where the user wants to display the sensor data.

Solar Wireless Sensor Nodes for Condition Monitoring of Freight Trains

Abstract: The objective of this work is to present the design and testing of a Wireless Sensor Network, powered by solar energy, to be installed on freight trains with the purpose of performing on-board monitoring operations. A complete Wireless Sensor Network requires a certain number of Wireless Sensor Nodes, installed in significant points of a vehicle, provided with sensors and capable of elaborating raw data, transmitting them via wireless network as synthesis information to an on-board control unit. The on-board control unit periodically communicates the data gathered from different sensors to a ground central control unit through the Internet. Each Wireless Sensor Node needs to be powered independently. To achieve this purpose a small solar panel was used to provide the Wireless Sensor Node with the necessary amount of energy. Integrated circuits were designed for power management, acquisition, elaboration and wireless transmission of data and analyzed in terms of performances and energy consumption. The communication protocol between the Wireless Sensor Node and the control unit was first laboratory-tested and finally the whole system was installed on a real wagon, and on-field tests were conducted for a period of almost one year.

Measurement Outlier-Resistant Target Tracking in Wireless Sensor Networks With Energy Harvesting Constraints

Abstract: In this paper, the measurement outlier-resistant target tracking problem is investigated in wireless sensor networks (WSNs) with energy harvesting constraints. Each WSN node can acquire energy stochastically from surroundings. No matter whether the WSN node acquires energy or not, the WSN node’s measurement can be transmitted if the energy amount of the WSN node is greater than zero. In such a case, the sensor energy-induced missing measurement (SE-IMM) phenomenon may occur. The objective of this paper is to develop a solution for the considered target tracking problem by devising the filter including a saturation constraint such that, in the simultaneous presence of outliers and the SE-IMM phenomenon, the tracking performance can meet the given performance index. Firstly, the relation between the energy level of the WSN node and its probability distribution is computed recursively. Then, an upper bound of the tracking error covariance is derived which is minimized by appropriately choosing the filter parameter. Finally, the feasibility of the proposed target tracking scheme is validated by conducting a set of comparative experiments and the relationship between the energy of the WSN node and the tracking performance is also disclosed.

An Investigation on Energy Consumption in Wireless Sensor Network

Abstract: Wireless Sensor Networks (WSNs) has gained undisputed importance in the past decade in wide range of applications. WSN consists of densely deployed sensor nodes to monitor the environment. The sensed and collected data is communicated to the end user via the sink node using multi-hop transmission. There are several constraints in the construction of a sensor node such as processing power, memory and battery capacity. When the sensor nodes spend energy in an inefficient manner, it will reduce the network lifetime (NL) and hence the components of sensor node and the protocols governing the network must be optimally designed to extend its lifetime by reducing energy consumption. Many investigators have done their work in identifying energy consumed by the various activities carried out in WSNs. A detailed study is required for complete analysis of energy consumed by various elements in the WSN for the development of efficient protocols. This paper summarizes the energy consumed in a WSN and provides an insight for further research in WSN.

Combined sensor selection and node location optimization for reducing the localization uncertainties in wireless sensor networks

Abstract: Local Positioning Systems (LPS) address the limitations of Global Navigation Satellite Systems in harsh environments. LPS must attain the optimal location of their sensors in space for optimal performance, which is known as the Node Location Problem. In addition, not all the sensors under coverage present the best performance for determining the location. For this purpose, the optimal selection of the best combination of nodes requires addressing the Sensor Selection Problem. In this paper, for the first time in the literature, we present a methodology for the combined optimization of both problems which may attain improved results than separated optimizations. Results show that the consideration of SSP based sensor selection strategies during the NLP suppose a reduction up to 10% in the localization uncertainties with respect to traditional baseline sensor selection strategies of the NLP, thus proving the effectiveness of the devised technique.

A Method for Preserving Battery Life in Wireless Sensor Nodes for LoRa Based IOT Flood Monitoring

Abstract: A common challenge in the implementation of Internet of Things (IOT) Wireless Sensor Networks (WSN) is that the sensor nodes are known to be power hungry devices. The energy stored in the batteries which power up these sensor nodes deplete quickly especially when more data is transmitted to the cloud or when multiple sensors are attached to a single sensor node. In the context of flood and environmental monitoring, increasing the number of sensor nodes in a Wireless Sensor Network is desirable in order to increase the spatial resolution of the data and hence achieve better representation about rising water levels and overall water quality in a particular city. However, having more sensor nodes in a Wireless Sensor Network results in more challenges for the power supply management of the overall Wireless Sensor Network. A drawback of the sensor nodes which are usually powered by Lithium Ion batteries is that there is a limited number of cycles in which a battery can be charged and discharged before the battery is considered to be fully degraded and therefore methods which can lengthen the duration of each charging and discharging cycle will be useful to increase the overall battery longevity. In this paper, a method which combines solar energy harvesting together with a fuzzy logic based algorithm for adaptive sampling is proposed in order to achieve a continuous source of energy for the sensor nodes and also increase the duration between each charging and discharging cycle resulting in batteries which can last for a longer duration. The developed sensor nodes have been deployed to measure river water levels and dissolved oxygen.

Cooperative Communication Between Two Transiently Powered Sensor Nodes by Reinforcement Learning

Abstract: Energy harvesting (EH)-powered sensor nodes can achieve theoretically unlimited lifetime by scavenging energy from ambient power sources, such as radio-frequency (RF) and kinetic energy. The nodes can collect and transmit data wirelessly with the harvested energy. However, the transmission between two sensor nodes is successful only when both nodes have enough energy at the same time. While the receiver can be actively listening, it may deplete the energy long before the sender has accumulated enough energy. Thus, given the scarce, unpredictable, and unevenly distributed energy among sensor nodes, it is challenging to ensure efficient data transmission between them. To address this challenge, we propose a sensor node architecture with multiple radios, each with different energy consumption on the sender and receiver. A node can be put into sleep when charged up and wakes up for communication when it infers that both nodes have enough energy based on its observations. What is more, two nodes can cooperatively and dynamically select different radios according to the stored energy and historical information to maximize the data throughput. To achieve cooperative communication adaptively, the communication procedure is modeled as a cooperative Markov game with partial observability on each node, and multiagent reinforcement learning (MARL) is employed to achieve the best results. Experimental results on hardware prototype and by simulation show that the proposed approaches achieve up to 89.1% of the optimal throughput and significantly outperform other online algorithms.

Deterministic Static Sensor Node Placement in Wireless Sensor Network based on Territorial Predator Scent Marking Behaviour

Abstract: An optimum sensor node placement mechanism for Wireless Sensor Network (WSN) is desirable in ensuring the location of sensor nodes offers maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement algorithm that utilizes a new biologically inspired optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). The main objectives considered in this paper are to achieve maximum coverage and minimum energy consumption with guaranteed connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm implemented in two different single objective approaches with an Integer Linear Programming based algorithm. The proposed single objective approaches of TPSMA studied in this paper are TPSMA with minimum energy and TPSMA with maximum coverage. Simulation results show that the WSN deployed using the proposed TPSMA sensor node placement algorithm is able to arrange the sensor nodes according to the objective required; TPSMA with maximum coverage offers the highest coverage ratio with fewer sensor nodes up to 100% coverage while TPSMA with minimum energy consumption utilized the lowest energy as low as around 4.85 Joules. Full connectivity is provisioned for all TPSMA approaches since the constraint of the optimization problem is to ensure the connectivity from all sensor nodes to the sink node.

A Comparative Analysis between Battery- and Solar-Powered Wireless Sensors for Soil Water Monitoring

Abstract: Wireless sensor networks (WSN) have found wide applications in many fields (such as agriculture) over last few years, and research interest is constantly increasing. However, power supply to the sensor nodes remains an issue to be resolved. Batteries are usually used to power the sensor nodes, but they have a limited lifetime, so solar energy harvesters are a good alternative solution. This study provides a comparative analysis between battery and solar energy harvesters for sensor nodes used for soil water monitoring. Experimental results show that small-sized solar panels with low-power energy harvester circuits and rechargeable batteries distinctly outperform secondary batteries in outdoor and continuous-operation applications. The power level of the energy storage device of sensor node 1, which was powered by a small PV panel, remained constantly close to 90% for all days. The power of the other three nodes, which were powered by a rechargeable battery, was initially at 100% of the charge and gradually started to reduce. Sensor node 1 performed a total of 1288 activations during the experimental period, while sensor nodes 2 and 4 behaved satisfactorily and performed a total of 781 and 803 activations, respectively. In contrast, sensor node 3 did not exhibit the same behavior throughout the experiments.

Microcontroller Unit-Based Wireless Sensor Network Nodes: A Review

Abstract: In this paper, a detailed review of microcontroller unit (MCU)-based wireless sensor node platforms from recently published research articles is presented. Despite numerous research efforts in the fast-growing field of wireless sensor devices, energy consumption remains a challenge that limits the lifetime of wireless sensor networks (WSNs). The Internet-of-Things (IoT) technology utilizes WSNs for providing an efficient sensing and communication infrastructure. Thus, a comparison of the existing wireless sensor nodes is crucial. Of particular interest are the advances in the recent MCU-based wireless sensor node platforms, which have become diverse and fairly advanced in relation to the currently available commercial WSN platforms. The recent wireless sensor nodes are compared with commercially available motes. The commercially available motes are selected based on a number of criteria including popularity, published results, interesting characteristics and features. Of particular interest is to understand the trajectory of development of these devices and the technologies so as to inform the research and application directions. The comparison is mainly based on processing and memory specifications, communication capabilities, power supply and consumption, sensor support, potential applications, node programming and hardware security. This paper attempts to provide a clear picture of the progress being made towards the design of autonomous wireless sensor nodes to avoid redundancy in research by industry and academia. This paper is expected to assist developers of wireless sensor nodes to produce improved designs that outperform the existing motes. Besides, this paper will guide researchers and potential users to easily make the best choice of a mote that best suits their specific application scenarios. A discussion on the wireless sensor node platforms is provided, and challenges and future research directions are also outlined.

Underwater optical wireless sensor network for real-time underwater environmental monitoring

Abstract: With the growing number of underwater vehicles and devices used for marine environmental monitoring, there is an urgent need for real-time and high-speed underwater wireless communication technologies to transmit huge amounts of data. This poses great challenges to conventional underwater acoustic communication technology due to its low bandwidth and high latency. Therefore, underwater wireless optical communication with high bandwidth and low latency has become a promising technology. To this end, we develop the first underwater optical wireless sensor network prototype in this work. It consists of two sensor nodes and an optical hub. There is a transceiver circuit, a pH sensor, and an integrated temperature, salinity, and conductivity sensor in the sensor nodes enabling real-time underwater environmental monitoring. There are four transceivers facing four sides in the optical hub to implement bi-directional optical wireless communication with the sensor nodes. In a laboratory testbed and a field trial conducted in an outdoor diving pool, 100% packet success rates are achieved between the optical hub and the sensor nodes at a transmission distance of 60 cm. In the field trial, one of the sensor nodes is placed 60 cm away from the optical hub for real-time underwater environmental monitoring. The other sensor node is mounted on a remotely operated vehicle to collect underwater environmental information. This prototype shows great potential in future underwater mobile sensor networks and the underwater Internet of Things.

Enhanced Energy-Efficient Routing for Wireless Sensor Network Using Extended Power-Efficient Gathering in Sensor Information Systems (E-PEGASIS) Protocol

Abstract: Recent technological advancements in wireless communication and sensors made Wireless Sensor Networks (WSNs) as one of the demanding platforms in the current scenario. In WSN, tiny sensor nodes are collecting and monitoring the biological data or physical data or environmental data and transmits to the Base Station (BS) through gateway routers. These data can be accessed anywhere and anytime. Usually, sensor nodes have restrained battery power which creates the rigorous lifetime duration issues in WSN. Sensor nodes can transmit the data with each other using various routing protocols. Data transmission devours more amounts of energy and power. So, energy preservation is an important factor in WSN. There are plenty of researches going on in designing less energy consuming protocols for data transmission which helps to increase the lifetime of WSN. In this manuscript, we have proposed Extended Power-Efficient Gathering in Sensor Information Systems (E-PEGASIS) protocol for enhanced energy-efficient data transmission based on PEGASIS protocol. In this proposed method, the average distance between the sensor nodes is considered as the criterion for chaining and fixing the outermost node’s radio range value to the base station. Later it chains the related nodes available in the radio range. Consequently, the chained node checks their distance with the next nearest end node to go on with the chaining procedure which will enhance the performance of data transmission amid the base station and sensor node. The simulation of the proposed work shows that lifetime of the network is increased when compared to the LEACH and PEGASIS protocol.

Energy Harvesting Sensors based Internet of Things System for Precision Agriculture

Abstract: This paper proposes a design of wireless sensor node based on Internet of Things mainly its power unit which is integrated to solar energy for agriculture. The sensor node is developed using NodeMCu with four different sensors namely relative humidity and temperature sensor, soil moisture sensor, soil temperature sensor and luminosity sensor to monitor key parameters related to soil and environment. A power unit of sensor node is designed with Lithium ion batteries and charging of the batteries is maintained by solar panel. The developed node is tested for 24 hours for the battery voltage which proves that the power consumption during daytime is completely maintained while it drops during night.

ReLeC: A Reinforcement Learning-Based Clustering-Enhanced Protocol for Efficient Energy Optimization in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) are a widely studied area in the field of networked embedded computing. They are made up of several sensor nodes, which keep track of a variety of physical and environmental parameters, like temperature and humidity. The nodes are autonomous, self-configuring, and wireless. A significant problem in WSNs is that sensors in these networks consume a lot of energy. Energy consumption is a big issue when it comes to the deployment of sensor networks. The reason for this is the cost of operating a sensor node and the cost incurred due to energy consumption. Energy optimization is based on intelligent energy management. This paper presents a reinforcement learning-based and clustering-enhanced method. Reinforcement learning is a set of algorithms inspired by operant conditioning in animal behavior, and clustering-based methods have been extensively used for devising energy-efficient protocols. The proposed method is able to plan and schedule the nodes to ensure an extended network lifetime. In this work, we aim to assess and increase the efficiency of power consumption and reduce sensor node energy loss. The simulation results prove that the presented protocol effectively reduces the energy consumption of sensor nodes and ensures a prolonged lifetime of the sensor network.

Wireless Capacitive Liquid-Level Detection Sensor Based on Zero-Power RFID-Sensing Architecture

Abstract: In this paper, a new method for the wireless detection of liquid level is proposed by integrating a capacitive IDC-sensing element with a passive three-port RFID-sensing architecture. The sensing element transduces changes in the liquid level to corresponding fringe-capacitance variations, which alters the phase of the RFID backscattered signal. Variation in capacitance also changes the resonance magnitude of the sensing element, which is associated with a high phase transition. This change in the reactive phase is used as a sensing parameter by the RFID architecture for liquid-level detection. Practical measurements were conducted in a real-world scenario by placing the sensor at a distance of approximately 2 m (with a maximum range of about 7 m) from the RFID reader. The results show that the sensor node offers a high sensitivity of 2.15°/mm to the liquid-level variation. Additionally, the sensor can be used within or outside the container for the accurate measurement of conductive- or non-conductive-type liquids due to the use of polyethylene coating on the sensitive element. The proposed sensor increases the reliability of the current level sensors by eliminating the internal power source as well as complex signal-processing circuits, and it offers real-time response, linearity, high sensitivity, and excellent repeatability, which are suitable for widespread deployment of sensor node applications.

Dynamic Pricing for Sensor-Cloud Platform in the Presence of Dumb Nodes

Abstract: The presence of dumb nodes in sensor-cloud environment leads to degraded system performance. In this article, we consider the presence of dumb nodes in the sensor-cloud platform, and thereafter, propose a dynamic pricing scheme, while considering the existence of such nodes in the networks. The existing literature addresses the problem of pricing in sensor-cloud with the assumption of an ideal environment with normally functioning sensor nodes. The proposed pricing model considers the realistic existence of dumb nodes in sensor-cloud platforms. Further, the dumb behavior of a sensor node is dynamic in nature, as it is dependent on environmental conditions such as the occurrence of heavy rainfall, high temperature, and the presence of fog. However, in the absence of such adverse environmental conditions, the erstwhile dumb nodes resume normal behavior. The permanent removal of a dumb node from sensor-cloud is not always a feasible solution. When a dumb node is assigned to a virtual sensor, the existing pricing scheme in sensor-cloud charges same as other normal nodes. Thus, in such a situation, a user pays the normal price for a dumb node to the Sensor-Cloud Service Provider (SCSP). Consequently, the sensor owner of dumb node earn same profit as the owner of a normal node. Therefore, we formulate a scheme for Dynamic pricing in sensor-cloud environment in the presence of dumb nodes ( DISCLOUD ). As the presence of dumb nodes in sensor-cloud affects the Quality of Service (QoS), we propose a scheme considering QoS of the sensor-cloud. The proposed scheme, DISCLOUD, enables profit maximization of the SCSP, while considering the price required to be paid by end-user based on QoS.

Power Management Unit for Solar Energy Harvester Assisted Batteryless Wireless Sensor Node

Abstract: This work describes an energy-efficient monolithic Power Management Unit (PMU) that includes a charge pump adapted to photovoltaic cells with the capability of charging a large supply capacitor and managing the stored energy efficiently to provide the required supply voltage and power to low energy consumption wireless sensor nodes such as RFID sensor tags. The proposed system starts-up self-sufficiently with a light source luminosity equal to or higher than 500 lux using only a 1.42 cm2 solar cell and integrating an energy monitor that gives the ability to supply autonomous sensor nodes with discontinuous operation modes. The system occupies an area of 0.97 mm2 with a standard 180 nm CMOS technology. The half-floating architecture avoids losses of charging the top/button plate of the stray capacitors in each clock cycle. Measurements’ results on a fabricated IC exhibit an efficiency above 60% delivering 13.14 μW over 1.8 V. The harvested energy is enough to reach the communication range of a standard UHF RFID sensor tag up to 21 m.

Detection and Prevention of Faulty Node in Heterogeneous Wireless Sensor Network

Abstract: Wireless Sensor Network [WSN] faces many issues in transmitting the data from source to sink node. The data or information must be securely transmitted. If the information is not transmitted securely, then there is a need to secure that node. In WSN, the communication takes place between one node and the other node with some energy sources. The node that communicates with the another node becomes faulty due to its low energy and less bandwidth. Hence, there is need to ensure the security of the node in order to avoid uninterrupted communication. The proposed research work detects the faulty node with the help of Honeypot nodes. The detected faulty node is provided with the suitable security to prevent it from attacks. The comparison of existing research works with the proposed work is done by using the Honeypot nodes in between the other nodes to find the best result in detecting the faulty node.

A Comprehensive Review of Distributed Coding Algorithms for Visual Sensor Network (VSN)

Abstract: Since the invention of low cost camera, it has been widely incorporated into the sensor node in Wireless Sensor Network (WSN) to form the Visual Sensor Network (VSN). However, the use of camera is bringing with it a set of new challenges, because all the sensor nodes are powered by batteries. Hence, energy consumption is one of the most critical issues that have to be taken into consideration. In addition to this, the use of batteries has also limited the resources (memory, processor) that can be incorporated into the sensor node. The life time of a VSN decreases quickly as the image is transferred to the destination. One of the solutions to the aforementioned problem is to reduce the data to be transferred in the network by using image compression. In this paper, a comprehensive survey and analysis of distributed coding algorithms that can be used to encode images in VSN is provided. This also includes an overview of these algorithms, together with their advantages and deficiencies when implemented in VSN. These algorithms are then compared at the end to determine the algorithm that is more suitable for VSN.