Low-power Sensor Nodes Research Articles

Real Time Monitoring of Wireless Fire Detection Node

This work presents the design of low rate and low power sensor node in wireless based sensor network for early detection and monitoring of fire in environment. It uses the DHT11 digital temperature – humidity sensor for measurement and MSP430 microcontroller for processing and implementing best algorithm from the comparison algorithm and DST algorithm using Dempster-Shaffer Theory for fire detection. The detected information is transmitted to the computer system through XBeepro for short distance wirelessly. The performance of algorithms are analyzed and tested with the metric un_detect fire. The information is shared in real time to the owner/ fire station/ police and all other responsible persons by the computer system using teamviewer software through Internet. The DST has more software design complexity than comparison algorithm. But it gives better performance than comparison.

A Novel Energy Efficient Clustering Mechanism in Wireless Sensor Network

The area of wireless sensor networks (WSNs) is one of the emerging and fast growing fields in the scientific world. This has brought about developing low cost, low-power and multi-function sensor nodes. However, the major fact that sensor nodes run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the longevity of the network. This is the reason why routing techniques in wireless sensor network focus mainly on the accomplishment of power conservation. Most of the recent publications have shown so many protocols mainly designed to minimize energy consumption in sensor networks. This paper proposes a hierarchical routing technique which shows energy efficiency. Our technique selects cluster head with highest residual energy in each communication round of transmission and also takes into account, the shortest distance to the base station from the cluster heads. Simulation results show that hierarchical routing technique with different level of hierarchy prolongs the lifetime of the network compared to other clustering scheme and the energy residual mean value after some communication rounds of simulation increases significantly.

An Energy Efficient Approach for Routing in Wireless Sensor Networks

Wireless Networks are becoming popular due to the concept of “3 any”-any person, anywhere and anytime. Technological advancements in wireless communication paved way to the development of tiny low-cost, low-power and multifunctional sensor nodes in wireless sensor networks. The network layer deals with routing issues in sensor networks. Since radio transmission and reception consumes large amount of energy, power is an important factor to be investigated on. Energy conservation is thus a key issue in wireless sensor networks. Ongoing research involves designing routing protocols that requires less energy during communication thereby extending the networks lifetime. For most of the applications, a replacement of energy is too expensive. An energy harvesting wireless sensor networks make use of nodes that are able to harvest energy from environment. This paper provides a survey on energy efficient routing. A comparison between Modified LEACH and Mobile Sink improved energy-efficient PEGASIS-based routing protocol is done using MATLAB. Paper also introduces the energy harvesting concept.

A Configurable 12–237 kS/s 12.8 mW Sparse-Approximation Engine for Mobile Data Aggregation of Compressively Sampled Physiological Signals

Compressive sensing (CS) is a promising technology for realizing low-power and cost-effective wireless sensor nodes (WSNs) in pervasive health systems for 24/7 health monitoring. Due to the high computational complexity (CC) of the reconstruction algorithms, software solutions cannot fulfill the energy efficiency needs for real-time processing. In this paper, we present a 12—237 kS/s 12.8 mW sparse-approximation (SA) engine chip that enables the energy-efficient data aggregation of compressively sampled physiological signals on mobile platforms. The SA engine chip integrated in 40 nm CMOS can support the simultaneous reconstruction of over 200 channels of physiological signals while consuming $ of a smartphone’s power budget. Such energy-efficient reconstruction enables two-to-three times energy saving at the sensor nodes in a CS-based health monitoring system as compared to traditional Nyquist-based systems, while providing timely feedback and bringing signal intelligence closer to the user.

Fuzzy trust-based aggregator sensor node election in internet of things

Wireless sensor networks WSNs act as a fundamental digital backbone, providing a virtual layer where the information about the physical world can be accessed by any computational system, which have limited resources to survive. One of the most important ingredients of the internet of things IoT paradigm is the integration of the web-like network with low power sensor nodes lead to lots of research challenges. Since a large-scale of WSN is to be completely integrated into the IoT, it is necessary to consider the various security challenges that come with the integration and is also important to identify and block the malicious nodes in the WSN to defend against network attacks. This paper proposed a fuzzy trusted-based aggregator FTBA node election technique for wireless sensor networks. The FTBA scheme performs decision-making function to authenticate the sensor nodes of the network to act as a trusted aggregator by four factors namely, physical factor, remoteness, reputation and aggregation intelligence. The proposed FTBA outperform when compared with existing approaches like LEACH, PEGASIS, and direct transmission in parameters like aggregation ratio, network life time, average node's residual energy and false positive rate of the aggregator election.

Development of 6LoWPAN in Embedded Wireless System

In the proposed system, implementation of the low power sensor nodes is proposed. 6LoWPAN is an acronym of IPv6 over Low power Wireless Personal Area Network was developed to enable the Wireless Embedded Internet by simplifying IPv6 functionality, defining very compact header formats and taking the nature of wireless networks into account. Our solution contains two types of nodes Wireless Sensor Node and Border Router/Gateway Node. Wireless Sensor Node: These nodes have sensors integrated and are used to gather the information and send to the Border Router/Gateway Node. They create a mesh network among them, forwarding the packets of other nodes in order to make the information reach the Border Router/Gateway Node. Each Wireless Sensor Node is equipped with a 6LoWPAN (802.15.4) radio, sensors and a battery. It can be either a microcontroller based or Linux based embedded platforms. Border Router/Gateway Node: This node takes the information sent by the Wireless Sensor Nodes and sends it to the Tunneling IPv4 / IPv6 server by using the Ethernet IPv4 interface. Each Border Router/Gateway Node is equipped with a Linux based Single Board Computer, 6LoWPAN (802.15.4) radio and an Ethernet interface and a battery.

A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

The fusion of Wireless Sensor Networks (WSNs) and Cognitive Radio Networks (CRNs) into Cognitive Radio Sensor Networks (CRSNs) is quite an attractive proposal, because it allows a distributed set of low-powered sensor nodes to opportunistically access spectrum bands that are underutilized by their licensed owners (called primary users (PUs)). In addition, when the PUs are actively transmitting in their own bands, sensor nodes can switch to energy harvesting mode to obtain their energy needs (for free), to achieve almost perpetual life. In this work, we present a novel and fully distributed MAC protocol, calledS-LEARN, that allows sensor nodes in a CRSN to entwine their RF energy harvesting and data transmission activities, while intelligently addressing the issue of disproportionate difference between the high power necessary for the node to transmit data packets and the small amount of power it can harvest wirelessly from the environment. The presented MAC protocol can improve both the network throughput and total harvested energy, while being robust to changes in the network configuration. Moreover, S-LEARN can keep the cost of the system low, and it avoids the pitfalls from which centralized systems suffer.

AR-RBFS: Aware-Routing Protocol Based on Recursive Best-First Search Algorithm for Wireless Sensor Networks

Energy issue is one of the most important problems in wireless sensor networks. They consist of low-power sensor nodes and a few base station nodes. They must be adaptive and efficient in data transmission to sink in various areas. This paper proposes an aware-routing protocol based on clustering and recursive search approaches. The paper focuses on the energy efficiency issue with various measures such as prolonging network lifetime along with reducing energy consumption in the sensor nodes and increasing the system reliability. Our proposed protocol consists of two phases. In the first phase (network development phase), the sensors are placed into virtual layers. The second phase (data transmission) is related to routes discovery and data transferring so it is based on virtual-based Classic-RBFS algorithm in the lake of energy problem environments but, in the nonchargeable environments, all nodes in each layer can be modeled as a random graph and then begin to be managed by the duty cycle method. Additionally, the protocol uses new topology control, data aggregation, and sleep/wake-up schemas for energy saving in the network. The simulation results show that the proposed protocol is optimal in the network lifetime and packet delivery parameters according to the present protocols.

An Approach to Locate Nasty Node and to Prevent Selective Dropping in WSN

The fast growth in wireless communication and digital electronics has led to the development of low-cost and lowpower sensor nodes that are small in size and may communicate over short distances. Sensor nodes are deployed in hostile environment in large number, which makes their physical protection against tampering difficult or more prone to be compromised by an adversary force. By doing that, an adversary can modify the behavior of the compromised nodes and launch routing misbehavior attacks. One most common type of such attacks is gray hole attack. Adhoc On Demand Distance Vector (AODV) in its pure form does not have any mechanism to deal with such type of attack. In this paper, we simulate gray hole attack on AODV routing protocol and evaluate AODV’s performance by considering different metrics and scenarios. NS2 simulator has been used to conduct simulation of gray hole attack. Our simulation results show the influence of gray hole attack on the performance of AODV which suffers from decreased delivery ratio and increased packet loss. Furthermore, some countermeasures against gray hole attack are also provided.

Enhanced on Demand ECRSEP Protocol using Improved Cluster Head Selection

Sensor network consists of large amount of low power sensor nodes generally deployed in hostile and harsh environment to sense, collect and transmit data to the sink situated at some distance. Clustering has been widely studied to enhance the lifetime of WSN by reducing the number of packet transmission. In clustering, the nodes selected as cluster head, often suffer from high overload and thus consume more energy. In this paper, we have proposed a new on demand Energy Consumption rate stable election protocol for heterogeneous WSN that uses an improved cluster head selection criteria. The improved selection criterion utilizes average remaining energy and average distance of each node which is not considered in existing protocols. Furthermore the proposed protocol being reactive improves the stability period and network lifetime. The experimental analysis depicts that the proposed algorithm has shown a significant improvement over ECRSEP. Keywordsdemand, ECRSEP, clustering, heterogeneous, WSN, wireless, sensor, network.

MDFD and DFD Methods to detect Failed Sensor Nodes in Wireless Sensor Network

Wireless Sensor Network (WSN) contains many low cost and low power sensor nodes (SNs), these nodes may fail to communicate with each other according to some reasons such as battery lifetime or uncontrolled events which will lead to partition the network and reduce the Quality of Service (QoS) as well as the reliability and efficiency of the whole network. The motivation of this paper is detecting these malfunctions using Distributed Fault Detection (DFD) method considered with random proposed network model. Then a modification on DFD method (MDFD) proposed to enhance the efficiency and the reliability of the whole network and handling the error occurred with DFD method. The two methods analyzed and tested using MATLAB and they must applied with homogeneous WSNs only that contain only one type of sensors, percentage error of DFD method was about 25% (for three SNs) due to its algorithm limitations in using only half of the neighbor SNs, this percentage error reduced in MDFD method in which all neighbor SNs considered to detect the failed SN reaching full detection accuracy but with latency tradeoff. General Terms Distributed Fault Detection, Proposed Method, Failed Sensor Nodes.

Secure End to End Data Aggregation using Public Key Encryption in Wireless Sensor Network

Wireless Sensor Networks is made of a large number of lowcost and low power sensor nodes that contains strictly limited sensing, computation, as well as communication abilities. Because of resource restricted sensor nodes, it is very important to reduce the amount of data transmission so the average sensor lifespan and also the total bandwidth utilization are generally increased. Data aggregation is the process of summarizing and merging sensor data to be able to minimize the number of data transmission in the network. Cluster based Data Aggregation approach, the data sensed by the sensor nodes are transferred to the cluster head and in the cluster head performs data aggregation and forwards results to the sink. Data aggregation could conserve energy (power) as well as bandwidth of the networks. As wireless sensor networks are generally used in remote and hostile environments in order to transfer very sensitive information, sensor nodes are susceptible to node compromise attacks and security problems such as data confidentiality and integrity are extremely crucial. Therefore, Secure Data aggregation protocol, must be designed with security in mind and investigates the relationship between security and data aggregation process within wireless sensor networks. In this paper, the secure data aggregation schemes are categorized into hop by hop aggregation and end to end aggregation. Here we explore a Homomorphic aggregation system based on a public key encryption (PKE) scheme to protect sensor data secure is proposed. Security analysis shows that our proposed protocol can guarantee end-to-end confidentiality and privacy. General Terms Secure Data Aggregation, WSN, Privacy Homomorphism(PH).

AlGaAs Photovoltaics for Indoor Energy Harvesting in mm-Scale Wireless Sensor Nodes

Indoor photovoltaic energy harvesting is a promising candidate to power millimeter (mm)-scale systems. The theoretical efficiency and electrical performance of photovoltaics under typical indoor lighting conditions are analyzed. Commercial crystalline Si and fabricated GaAs and Al0.2Ga0.8As photovoltaic cells were experimentally measured under simulated AM 1.5 solar irradiation and indoor illumination conditions using a white phosphor light-emitting diode to study the effects of input spectra and illuminance on performance. The Al0.2Ga0.8As cells demonstrated the highest performance with a power conversion efficiency of 21%, with open-circuit voltages >0.65 V under low lighting conditions. The GaAs and Al0.2Ga0.8As cells each provide a power density of $\sim 100$ nW/mm $^{2}$ or more at 250 lx, sufficient for the perpetual operation of present-day low-power mm-scale wireless sensor nodes.

A low-cost sensing system for cooperative air quality monitoring in urban areas.

Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

Cluster Based Multipath Routing Protocol for Wireless Sensor Networks

Wireless Sensor Network (WSN) consists of low power sensor nodes. Energy is the main constraint associated with the sensor nodes. In this paper, we propose a cluster based multipath routing protocol, which uses the clustering and multipath techniques to reduce energy consumption and increase the reliability. The basic idea is to reduce the load of the sensor node by giving more responsibility to the base station (sink). We have implemented and compared the protocol with existing protocols and found that it is more energy-efficient and reliable.

Efficient Data Reporting in Intelligent Transportation Systems

Recently, intelligent transportation systems (ITSs) have emerged. These systems can improve traditional transportation systems and provide traffic information to travelers. In the area of transportation, wireless sensor networks (WSNs) can replace the existing wired sensors and expensive traffic monitoring systems to mitigate the time and costs of installing such systems. However, accurate and on-time traffic information delivery is a major challenge, considering the energy constraints of sensor nodes. In this paper, we propose a two-tier architecture that includes a network of mobile objects (vehicles) in the upper layer and a hierarchical WSN in the bottom layer. Using this approach, a portion of loads on the low-power static sensor nodes can be transferred to mobile objects, such as powerful mobile devices. Moreover, to provide accurate and timely traffic information, a QoS-aware link cost function has been proposed and used for data transmission between the static sensor nodes. In addition, due to the mobility of the objects and the probability of losing packets in the mobile object tier, a reliable data forwarding mechanism has been proposed for this tier. In this mechanism, data packets are forwarded to the neighbors, which enhance the probability of the packets’ being received. The performance evaluation results indicate the effectiveness of the proposed architecture and data reporting mechanism for use in ITS applications.

A Study on Low-Power Sensor Node based on Event-based Sampling Using Renewable Energy in Greenhouse

In the paper, we proposed low-power sensor node that applied to perform events-based sampling algorithm and to harvest energy through irrigation equipment applicable in greenhouse environment. The system composition to achieve such a goal could be divided into three parts of sensors, data processing and control, and this paper suggests a solution to an unnecessary wasting energy problem by using the event-based sampling to effectively reduce data exchange between the control system composition. Sensor node based on energy harvesting are implemented through micro-hydro generators connected to the irrigation equipment and it is confirmed that transmitting or receiving stable data is possible, reducing energy consumption of sensor node by the algorithm.

Wearable Computer Network Design using Dual-Role WUSB Clustering

A recent major development in computer technology is the advent of the wearable computer system that is based on human-centric interface technology trends and ubiquitous computing environments. Wearable computer systems can be integrated with the wireless universal serial bus (WUSB) that refers to USB technology that is merged with WiMedia PHY/MAC technical specifications. A wireless body area network (WBAN) allows the integration of intelligent, miniaturized, low-power sensor nodes that monitor body functions and the surrounding environment. In this paper, we propose a method for multi-hop network extension of WUSB over WBAN protocol. Unlike a wired USB that physically separates the USB host and USB device, WUSB allows a device to separately function as both a WUSB host and WUSB device on a single transceiver; such devices are referred to as the dual role devices (DRD). By using this DRD function of WUSB protocol, we propose a WUSB clustering method to realize the multi-hop network extension of WUSB over WBAN protocol in wireless home networks. In the WUSB clustering method, a new DRD message format reserves 2-hop range private DRP (Distributed Reservation Protocol) resources. In the experiment results, efficiency of the WUSB clustering method is proven through throughput evaluation in viewpoints of medical and nonmedical multi-hop WBAN services.

English

Wireless sensor network is an emerging technology which consists of activities like sensing, computing, instrumenting and observing low power sensor nodes. In wireless sensor networks, maintaining the higher throughput is the main concern. Throughput of the network which is obtained from the wireless sensor network is vital issue which must be high which is measured in data packets per second in this context. The network of wireless sensors which is to be considered in this research mainly based on zigbee protocol and IEEE 802.15.4 standard and treated with cluster tree topology which is considered as a most suitable zigbee topology. The problem that sensors usually face in wireless sensor network is that when data packets are transferred from one node to another node, the throughput of the wireless sensor network decreases because of packet collisions and high network traffic. So we have proposed improved ABE mechanism which uses IEEE 802.15.4 slotted CSMA/CA to obtain the better throughput of zigbee based wireless sensor network.

Improving the Life of the Wireless Sensor Network using Energy Harvesting Clustering

In the modern era, Wireless sensor network (WSN) has seen new horizons among the research community. It has largest range of applications in most of the fields. Its beauty lies in its application area and it can be deployed anywhere. WSN has low cost, low power sensor nodes, can be deployed in large numbers and can be even used in hazardous environment. However, the sensor nodes in WSN do not have longer lifetime. Therefore, to meet this challenge of increasing the field lifetime of sensor nodes, the present study seeks to meet this end by using energy harvesting clustering model. Lifetime of the network increased largely by energy harvesting concept and clustering technique applied for effective use of energy. This increases the field lifetime of the sensor nodes before their complete degradation. In this way lifetime of the network improved a lot, which has seen through the experimental results in this paper. General Terms Wireless Sensor Networks, Energy harvesting.