Showing papers on "Sensor node published in 2018"

Flight Time Minimization of UAV for Data Collection Over Wireless Sensor Networks

Abstract: In this paper, we consider a scenario where an unmanned aerial vehicle (UAV) collects data from a set of sensors on a straight line. The UAV can either cruise or hover while communicating with the sensors. The objective is to minimize the UAV’s total flight time from a starting point to a destination while allowing each sensor to successfully upload a certain amount of data using a given amount of energy. The whole trajectory is divided into non-overlapping data collection intervals, in each of which one sensor is served by the UAV. The data collection intervals, the UAV’s speed, and the sensors’ transmit powers are jointly optimized. The formulated flight time minimization problem is difficult to solve. We first show that when only one sensor is present, the sensor’s transmit power follows a water-filling policy and the UAV’s speed can be found efficiently by bisection search. Then, we show that for the general case with multiple sensors, the flight time minimization problem can be equivalently reformulated as a dynamic programming (DP) problem. The subproblem involved in each stage of the DP reduces to handle the case with only one sensor node. Numerical results present the insightful behaviors of the UAV and the sensors. Specifically, it is observed that the UAV’s optimal speed is proportional to the given energy of the sensors and the inter-sensor distance, but it is inversely proportional to the data upload requirement.

Energy-Harvesting Wireless Sensor Networks (EH-WSNs): A Review

Abstract: Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have limited energy in their primary power storage unit, and this energy may be quickly drained if the sensor node remains operational over long periods of time. Therefore, the idea of harvesting ambient energy from the immediate surroundings of the deployed sensors, to recharge the batteries and to directly power the sensor nodes, has recently been proposed. The deployment of energy harvesting in environmental field systems eliminates the dependency of sensor nodes on battery power, drastically reducing the maintenance costs required to replace batteries. In this article, we review the state-of-the-art in energy-harvesting WSNs for environmental monitoring applications, including Animal Tracking, Air Quality Monitoring, Water Quality Monitoring, and Disaster Monitoring to improve the ecosystem and human life. In addition to presenting the technologies for harvesting energy from ambient sources and the protocols that can take advantage of the harvested energy, we present challenges that must be addressed to further advance energy-harvesting-based WSNs, along with some future work directions to address these challenges.

Energy Consumption Model for Sensor Nodes Based on LoRa and LoRaWAN

Abstract: Energy efficiency is the key requirement to maximize sensor node lifetime. Sensor nodes are typically powered by a battery source that has finite lifetime. Most Internet of Thing (IoT) applications require sensor nodes to operate reliably for an extended period of time. To design an autonomous sensor node, it is important to model its energy consumption for different tasks. Each task consumes a power consumption amount for a period of time. To optimize the consumed energy of the sensor node and have long communication range, Low Power Wide Area Network technology is considered. This paper describes an energy consumption model based on LoRa and LoRaWAN, which allows estimating the consumed power of each sensor node element. The definition of the different node units is first introduced. Then, a full energy model for communicating sensors is proposed. This model can be used to compare different LoRaWAN modes to find the best sensor node design to achieve its energy autonomy.

A Robust and Energy Efficient Authentication Protocol for Industrial Internet of Things

Abstract: The Internet of Things (IoT) is an emerging technology and expected to provide solutions for various industrial fields. As a basic technology of the IoT, wireless sensor networks (WSNs) can be used to collect the required environment parameters for specific applications. Due to the resource limitation of sensor node and the open nature of wireless channel, security has become an enormous challenge in WSN. Authentication as a basic security service can be used to guarantee the legality of data access in WSN. Recently, Chang and Le proposed two authentication protocols for WSN for different security requirements. However, their protocol cannot provide proper mutual authentication and has other security and functionality defects. We present a three-factor user authentication protocol for WSN to remove the weaknesses of previous protocols. The security of the proposed protocol is analyzed, and the security, functionality and performance of our protocol are compared with other related protocols. The comparison results and simulation results by NS-3 show that the proposed protocol is robust and energy efficient for IoT applications.

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

Abstract: Summary In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering-based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.

IoT-Based Remote Pain Monitoring System: From Device to Cloud Platform

Abstract: Facial expressions are among behavioral signs of pain that can be employed as an entry point to develop an automatic human pain assessment tool. Such a tool can be an alternative to the self-report method and particularly serve patients who are unable to self-report like patients in the intensive care unit and minors. In this paper, a wearable device with a biosensing facial mask is proposed to monitor pain intensity of a patient by utilizing facial surface electromyogram (sEMG). The wearable device works as a wireless sensor node and is integrated into an Internet of Things (IoT) system for remote pain monitoring. In the sensor node, up to eight channels of sEMG can be each sampled at 1000 Hz, to cover its full frequency range, and transmitted to the cloud server via the gateway in real time. In addition, both low energy consumption and wearing comfort are considered throughout the wearable device design for long-term monitoring. To remotely illustrate real-time pain data to caregivers, a mobile web application is developed for real-time streaming of high-volume sEMG data, digital signal processing, interpreting, and visualization. The cloud platform in the system acts as a bridge between the sensor node and web browser, managing wireless communication between the server and the web application. In summary, this study proposes a scalable IoT system for real-time biopotential monitoring and a wearable solution for automatic pain assessment via facial expressions.

EAPC: Energy-Aware Path Construction for Data Collection Using Mobile Sink in Wireless Sensor Networks

Abstract: Data collection is one of the paramount concerns in wireless sensor networks. Many data collection algorithms have been proposed for collecting data in particular monitoring regions. However, the efficiency of the paths for such data collection can be improved. This paper proposes an energy-aware path construction (EAPC) algorithm, which selects an appropriate set of data collection points, constructs a data collection path, and collects data from the points burdened with data. EAPC is intended to prolong the network lifetime, it accounts for the path cost from its current data collection point to the next point and the forwarding load of each sensor node. Performance evaluation reveals that the proposed EAPC has more efficient performance than existing data collection mechanisms in terms of network lifetime, energy consumption, fairness index, and efficiency index.

Coverage and Connectivity in WSNs: A Survey, Research Issues and Challenges

Abstract: Wireless Sensor Networks (WSNs) consist of several battery powered sensor nodes. The sensing coverage of the Field of Interest (FoI) is an important function of the sensor nodes in connected WSNs. A FoI is said to be covered if each point in the FoI is monitored by at least one sensor node. Due to small size, battery power supply, simple architecture, and light weight Operating System of the sensor nodes, maintaining the desired coverage of the FoI consists various issues and challenges in a connected WSN. This paper surveys the existing work done to address various issues and challenges for solving the coverage and connectivity problems in WSNs. Our discussion emphasis on sensing models, classification of coverage, research issues in WSNs and practical challenges in deployment of WSNs. We review a brief but complete overview of the various solutions of coverage problems in connected WSNs and describing insights into issues and challenges for research in this area.

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context.

Abstract: This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented.

A low power IoT network for smart agriculture

Abstract: Traditional agriculture is transforming into smart agriculture due to the prominence of the Internet of Things (IoT). Low-cost and low-power are the key factors to make any IoT network useful and acceptable to the farmers. In this paper, we have proposed a low-power, low-cost IoT network for smart agriculture. For monitoring the soil moisture content, we have used an in-house developed sensor. In the proposed network, the IITH mote is used as a sink and sensor node which provides low-power communication. We have evaluated our network with state of the art networks, proposed for agriculture monitoring. Power and cost are the two metrics used for evaluation of these networks. Results show that the proposed network consumes less power and has on average 83% prolonged lifetime at a lower cost compared to previously proposed network in the agriculture field.

Energy-Efficient Data Collection Over AUV-Assisted Underwater Acoustic Sensor Network

Abstract: Most applications of underwater cyber-physical system (UCPS) demand reliable data collection in an efficient and timely manner. However, the energy-constrained characteristic on acoustic communication makes it challenging to collect data. In this paper, we study the energy-efficient data collection for UCPS over autonomous underwater vehicle (AUV) assisted underwater acoustic sensor network. The sensor nodes perceive local physical parameters, whose lifetime is strictly restricted by local power. The AUV that has relatively sufficient energy is adopted to retrieve data from sensor nodes. To balance energy consumption and prolong underwater network lifetime, the energy optimization problem is formulated as minimizing the sum of edge lengths of a particular graph. Then, a min-weighted rigid graph based topology optimization scheme is developed for sensor deployment. With the optimized network topology, a local routing decision algorithm is developed for each sensor node to relay the collected data to the data collectors (sinks). A dynamic value-based path planning strategy is also designed for the AUV to dynamically visit data collectors to maximize the value of information (VoI) within a given time. Finally, simulation results demonstrate that the network lifetime with the topology optimization scheme can be prolonged, and the dynamic value-based path planning strategy can improve the VoI on AUV.

Recursive Distributed Filtering for a Class of State-Saturated Systems With Fading Measurements and Quantization Effects

Abstract: This paper is concerned with the distributed filtering problem over wireless sensor networks for a class of state-saturated systems subject to fading measurements and quantization effects. Each sensor node in the network communicates with its neighbors according to the network topology described by a directed graph. The fading phenomena of measurements are assumed to occur in a random way and the attenuation coefficients of the fading measurements are described by a set of random variables with known stochastic properties. By solving two sets of matrix difference equations, an upper bound for the filtering error covariance is presented. Subsequently, with the topology information of the sensor network, such an upper bound is minimized by properly designing the filter parameters. Moreover, the performance of the proposed filter is investigated through establishing sufficient conditions ensuring that the trace of the upper bound is bounded. The relationship between the filter performance and the mean of attenuation coefficient is also discussed. A numerical simulation is exploited to demonstrate the effectiveness of the proposed filtering method.

Internet of Things (IoT) for Precision Agriculture Application

Abstract: Internet is experiencing a very explosive growth nowadays with the amount of the devices connecting to it. Earlier we had only personal computers (pCs) and Mobile handset connected to internet but now with Internet of Things i.e. IoT concept of connecting things with internet, millions of device are connecting with it. This development of IoT leads to the idea of machine to machine communication which means that two machines can communicate to each other and also all the data which was previously with private server can now is available on internet so the user can access it remotely. Application of IoT is feasible in almost all industries particularly where speed of communication is not an issue. This paper proposes the application of cloud based IoT in the agriculture domain. Precision agriculture is basically a concept which insists to provide right amount of resources at and for exact duration of time. These resources can be any things such as water, light, pesticides etc. To implement precision agriculture the benefits of IOT has been utilized in the proposed paper. The fundamental idea is to sense all the required parameter from the agriculture field and take required decision to control the actuator. These agriculture parameters are Soil Moisture, Temperature & Relative Humidity around plant, Light intensity. Based on the reading sensed by the sensor suitable action is taken i.e. irrigation valve is actuated based on soil moisture readings, valve for fogger (for spraying water droplet) is actuated based on the Relative humidity(RH) readings etc. This paper proposed the development of the sensor node capable of measuring all these parameter and creating the actuation signal for all the actuator. On top of that sensor nodes are also capable of sending this data to cloud. An Android application is also developed in order to access all these agricultural parameter.

IoT based smart home automation system using sensor node

Abstract: In recent years, the advancements in Information and Communication Technology (ICT) are mainly focused on the Internet of Things (IoT). In a real-world scenario, IoT based services improve the domestic environment and are used in various applications. Home automation based IoT is versatile and popular applications. In home automation, all home appliances are networked together and able to operate without human involvement. Home automation gives a significant change in humans life which gives smart operating of home appliances. This motivated us to develop a new solution which controls some home appliances like light, fan, door cartons, energy consumption, and level of the Gas cylinder using various sensors like LM35, IR sensors, LDR module, Node MCU ESP8266, and Arduino UNO. The proposed solution uses the sensor and detects the presence or absence of a human object in the housework accordingly. Our solution also provides information about the energy consumed by the house owner regularly in the form of message. Also, it checks, the level of gas in the gas cylinder if it reaches lesser than the threshold, it automatically books the gas and sends a reference number as a message to the house owner. The proposed solution is deployed and tested for various conditions. Finally, in this paper, the working model of our proposed solution is developed as a prototype and explained as a working model.

WE-Safe: A Self-Powered Wearable IoT Sensor Network for Safety Applications Based on LoRa

Abstract: Poor environmental conditions can lead to severe health problems. It is essential to develop effective, reliable, and fast response systems for people working in hazardous environments. This paper presents a wearable Internet of Things sensor network aimed at monitoring harmful environmental conditions for safety applications via a Lora wireless network. The proposed sensor node, called the WE-Safe node, is based on a customized sensor node, which is self-powered, low-power, and supports multiple environmental sensors. Environmental data is monitored by the sensor node in real-time and transmitted to a remote cloud server. The data can be displayed to users through a web-based application located on the cloud server and the device will alert the user via a mobile application when an emergency condition is detected. The experimental results indicate that the presented safety monitoring network works reliably using energy harvesting.

Defending ON–OFF Attacks Using Light Probing Messages in Smart Sensors for Industrial Communication Systems

Abstract: Industrial communication systems (ICSs) have become an important part of many automated applications. Smart sensors for ICSs have attracted much attention. Using smart sensors for ICSs can allow the surrounding world to connect with the production equipment to reduce human resource requirements. However, due to their operating nature, smart sensors are often unattended and prone to different kinds of attacks. An on–off attack is one behavior that can cause serious damage to wireless sensor networks in ICSs. To ensure network security, a trust joint light probe based defense (TLPD) mechanism is proposed in which each smart sensor node selects a smart sensor node with high trust as the next hop to improve network security. The TLPD scheme is constituted by three major components, including light probe routing, trust estimation, and trust-aware routing. Light probe routing is adopted for increasing the operation times of malicious nodes, and a trust evaluation scheme evaluates nodes trust according to operation behavior of nodes. Thus, the discrimination degree of node trust between temporary errors and disguised malicious behaviors can be increased compared to existing trust evaluation schemes. Thus, a malicious smart sensor node can be quickly and easily identified. The analytical results of the TLPD mechanism assessed are with a simulation experiment.

A uW Backscatter-Morse-Leaf Sensor for Low-Power Agricultural Wireless Sensor Networks

Abstract: Nowadays, the monitoring of plant water stress is of high importance in smart agriculture Instead of the traditional ground soil-moisture measurement, the leaf sensing is a new technology, which is used for the detection of plants needing water In this paper, a novel, low-cost, and low-power system for leaf sensing using a new plant backscatter sensor node/tag is presented The latter, can result in the prevention of water waste (water-use efficiency), when is connected to an irrigation system Specifically, the sensor measures the temperature differential between the leaf and the air, which is directly related to the plant water stress Next, the tag collects the information from the leaf sensor through an analog-to-digital converter, and then, communicates remotely with a low-cost software-defined radio reader using monostatic backscatter architecture The tag consists of the sensor board, a microcontroller, an external timer, and an RF front-end for communication The timer produces a subcarrier frequency for simultaneous access of multiple tags The proposed work could be scaled and be a part of a large backscatter wireless sensor network The communication protocol exploits the low-complexity Morse code modulation on a 868 MHz carrier signal The presented novel proof-of-consent prototype is batteryless and was powered by a flexible solar panel consuming power around $20~\mu \text{W}$ The performance was validated in an indoors environment where wireless communication was successfully achieved up to 2 m distance

Multi-Source Energy Harvesting and Storage for Floating Wireless Sensor Network Nodes With Long Range Communication Capability

Abstract: Wireless sensor networks are widely used for environmental monitoring in remote areas. They are mainly composed of wireless sensor nodes, usually powered by batteries with limited capacity, but are expected to communicate in long range and operate for extended time periods. To overcome these limitations, many energy harvesting techniques are proposed to power wireless nodes for prolonged operation, whereas multihop techniques are utilized to extend the communication range. In this paper, a novel floating device with multisource energy harvesting technology that can be used as a wireless sensor node is proposed. The long range communication between wireless sensor nodes and a gateway is established through LoRa technology. In addition to conventional solar panels, an energy harvesting technique based on thermoelectric generators exploiting thermal differences created between water surface and materials exposed to sunlight is proposed. Energy generated from photovoltaic and thermoelectric generators is combined to power the wireless sensor node. This floating device consumes 6.6216 Wh per day when used as a wireless sensor node for the collection and transmission of environmental data. The sensor node can operate on a water surface for at least 9.6 days when it is not exposed to sunlight. During a sunny day, the floating device can harvest 8.375 Wh from solar panels and 0.425 Wh from thermoelectric generation. In other words, the floating device harvests sufficient energy to be self-sustaining during sunny days.

Energy-Efficient Sensor Data Collection Approach for Industrial Process Monitoring

Abstract: The use of wireless sensor network for industrial applications has attracted much attention from both academic and industrial sectors. It enables a continuous monitoring, controlling, and analyzing of the industrial processes, and contributes significantly to finding the best performance of operations. Sensors are typically deployed to gather data from the industrial environment and to transmit it periodically to the end user. Since the sensors are resource constrained, effective energy management should include new data collection techniques for an efficient utilization of the sensors. In this paper, we propose adaptive data collection mechanisms that allow each sensor node to adjust its sampling rate to the variation of its environment, while at the same time optimizing its energy consumption. We provide and compare three different data collection techniques. The first one uses the analysis of data variances via statistical tests to adapt the sampling rate, whereas the second one is based on the set-similarity functions, and the third one on the distance functions. Both simulation and real experimentations on telosB motes were performed in order to evaluate the performance of our techniques. The obtained results proved that our proposed adaptive data collection methods can reduce the number of acquired samples up to 80% with respect to a traditional fixed-rate technique. Furthermore, our experimental results showed significant energy savings and high accurate data collection compared to existing approaches.

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

Abstract: The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.

Roadside Magnetic Sensor System for Vehicle Detection in Urban Environments

Abstract: Intelligent Transportation Systems (ITS) are widely researched to improve the traffic situation. In ITS, vehicle detection system plays a significant role. At present, vehicle detection is often conducted by inductive loops, which are very expensive and inconvenient to install and maintain. Video camera is another frequently used detector, but it needs high computing power. In order to solve these problems, this paper focuses on the development of a roadside magnetic sensor system for vehicle detection. The device is installed at the side of the road and measures traffic in the adjacent lane (the closest lane to the sensor node). The data are transmitted by the IEEE 802.15.4 communication protocol. A novel adapted threshold state machine algorithm is proposed to detect vehicles. Since false judgments created by large vehicles passing in the nonadjacent lane (the lane next to the closest lane to the sensor node) are frequent in urban environments, a novel feature extracted by fusion of three magnetic sensor signals are proposed to reduce this error. The developed magnetic sensor system is wireless, compact, and cost-effective. The experimental results show that the proposed system achieves high accuracy and is viable in urban environments.

Trust evaluation method for clustered wireless sensor networks based on cloud model

Abstract: Trust Management has been proved to be an effective method to detect malicious nodes and ensure security in Wireless Sensor Networks (WSNs). While, most existing trust management methods are not good at dealing with uncertainty of trust relationship such as randomness, fuzziness in WSNs, which leads to inaccurate trust metric. In this paper, a trust evaluation method for clustered wireless sensor networks based on cloud model is proposed and evaluated, which implements the conversion between qualitative and quantitative of sensor nodes’ trust metrics in order to achieve better trust evaluation. Firstly, the method considers multi-factors including communication factor, message factor and energy factor and builds mathematical model for each trust factor to get factor trust cloud. Secondly, immediate trust cloud is calculated by assigning adjustive weights for each factor trust cloud and combining them. Thirdly, recommendation trust cloud and immediate trust cloud are synthesized according to time sensitive factor in order to get final trust cloud. Furthermore, the final trust cloud of sensor node is converted to trust grade by trust cloud decision-making. Verification Experiments manifest that the proposed method has feasibility and accuracy in the aspect of evaluating sensor nodes’ trust. Moreover, comparison experiments under different attacks show that our method is sensitive to multiple attacks, it outperforms other trust evaluation methods not only in the accuracy of detecting malicious nodes, but also in the tolerance of abnormal conditions.

Energy-Efficient Architecture for Wireless Sensor Networks in Healthcare Applications

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

Efficient authentication protocol for secure multimedia communications in IoT-enabled wireless sensor networks

Abstract: In current times, multimedia application includes integrated sensors, mobile networks and Internet-of-Things (IoT) services. In IoT services, if more devices are connected without much constrains, the problem of security, trust and privacy remain a challenge. For multimedia communications through Wireless Sensor Network (WSN), sensor nodes transmit confidential data to the gateway nodes via public channels. In such an environment, the security remains a serious issue from past many years. Only few works are available to support secure multimedia communications performed in IoT-enabled WSNs. Among the few works, Kumari and Om recently proposed an authentication protocol for multimedia communications in IoT-enabled WSNs, which is applicable in coal mine for safety monitoring. The authors claimed in their work that their contributory protocol strongly withstands several security threats such as, user impersonation attack, sensor node impersonation attack, sensor node anonymity issue and others technical design issues. However, this article proved that Kumari and Om’s protocol has some design flaws and is susceptible to various security attacks including, user and sensor node impersonation attacks. As a remedy, a robust authentication protocol using smartcard is constructed to solve the security issues found in Kumari and Om’s protocol. The proof of correctness of mutual authentication is performed using the BAN logic model. In addition, our further security investigation claimed strong protection against known security attacks. Our protocol is analyzed comprehensively and compared against the similar protocols and the results showed that it is efficient and robust than earlier protocols.

Theory and Experiment for Wireless-Powered Sensor Networks: How to Keep Sensors Alive

Abstract: In this paper, we investigate a multi-node multi-antenna wireless-powered sensor network (WPSN) comprised of one power beacon and multiple sensor nodes. We have implemented a real-life multi-node multi-antenna WPSN testbed that operates in real time. We propose a beam-splitting beamforming technique that enables a power beacon to split microwave energy beams toward multiple nodes for simultaneous charging. We experimentally demonstrate that the beam-splitting beamforming technique achieves the Pareto optimality. For perpetual operation of the sensor nodes, we adapt an energy neutral control algorithm that keeps a sensor node alive by balancing the harvested and consumed power. The joint beam-splitting and energy neutral control algorithm is designed by means of the Lyapunov optimization technique. In our experiments, the proposed algorithm has successfully kept all sensor nodes alive by optimally splitting energy beams toward multiple sensor nodes.

An Anonymous Mutual Authenticated Key Agreement Scheme for Wearable Sensors in Wireless Body Area Networks

Abstract: The advancement of Wireless Body Area Networks (WBAN) have led to significant progress in medical and health care systems. However, such networks still suffer from major security and privacy threats, especially for the data collected in medical or health care applications. Lack of security and existence of anonymous communication in WBAN brings about the operation failure of these networks. Recently, Li et al. proposed a lightweight protocol for wearable sensors in wireless body area networks. In their paper, the authors claimed that the protocol may provide anonymous mutual authentication and resist against various types of attacks. This study shows that such a protocol is still vulnerable to three types of attacks, i.e., the offline identity guessing attack, the sensor node impersonation attack and the hub node spoofing attack. We then present a secure scheme that addresses these problems, and retains similar efficiency in wireless sensors nodes and mobile phones.

Industrial IoT Monitoring: Technologies and Architecture Proposal.

Abstract: Dependability and standardization are essential to the adoption of Wireless Sensor Networks (WSN) in industrial applications. Standards such as ZigBee, WirelessHART, ISA100.11a and WIA-PA are, nowadays, at the basis of the main process-automation technologies. However, despite the success of these standards, management of WSNs is still an open topic, which clearly is an obstacle to dependability. Existing diagnostic tools are mostly application- or problem-specific, and do not support standard-based multi-network monitoring. This paper proposes a WSN monitoring architecture for process-automation technologies that addresses the mentioned limitations. Specifically, the architecture has low impact on sensor node resources, uses network metrics already available in industrial standards, and takes advantage of widely used management standards to share the monitoring information. The proposed architecture was validated through prototyping, and the obtained performance results are presented and discussed in the final part of the paper. In addition to proposing a monitoring architecture, the paper provides an in-depth insight into metrics, techniques, management protocols, and standards applicable to industrial WSNs.