J. Sens. Actuator Netw., Volume 8, Issue 2 (June 2019) – 18 articles

Monitoring and interpreting structural response using structural-identification methodologies improves understanding of civil-infrastructure behavior. New sensing devices and inexpensive computation has made model-based data interpretation feasible in engineering practice. Many data-interpretation methodologies, such as Bayesian model updating and residual minimization, involve strong assumptions regarding uncertainty conditions. While much research has been conducted on the scientific development of these methodologies and some research has evaluated the applicability of underlying assumptions, little research is available on the suitability of these methodologies to satisfy practical engineering challenges. For use in practice, data-interpretation methodologies need to be able, for example, to respond to changes in a transparent manner and provide accurate model updating at minimal additional cost. This facilitates incremental and iterative increases in understanding of structural behavior as more information becomes available. In this paper, three data-interpretation methodologies, Bayesian model updating, residual minimization and error-domain model falsification, are compared based on their ability to provide robust, accurate, engineer-friendly and computationally inexpensive model updating. Comparisons are made using two full-scale case studies for which multiple scenarios are considered, including incremental acquisition of information through measurements. Evaluation of these scenarios suggests that, compared with other data-interpretation methodologies, error-domain model falsification is able to incorporate, iteratively and transparently, incremental information gain to provide accurate model updating at low additional computational cost. Full article

A wireless Underground Sensor Network (WUSN) is a group of sensors that collectively communicate through the underground medium. Radio Frequency (RF) signal transmission of the sensors through the ground is the most challenging aspects of a WUSN due to the high attenuation of the electromagnetic (EM) signal in the soil. Signals are often required to travel through soils with a high density or water content and generally through a non-isotropic and non-homogenous soil mixture with different boundaries, both of which can attenuate the signal sharply. The variability of the these conditions and complexity of the behaviour of signal attenuation with respect to these parameters makes accurate estimation of EM signal attenuation in soil challenging. Two main EM signal attenuation models exist to estimate attenuation (modified-Friis and Complex Refractive Index Model-Fresnel (CRIM-Fresnel). These were reviewed and a methodology was developed in order to measure the attenuation of the EM signals in the laboratory. Results from the laboratory measurements were compared with the estimation values calculated from the attenuation models. These comparisons showed a large difference between the estimated values by the models. In addition, analysis of the comparison tests showed that the CRIM-Fresnel model provides a better estimation of attenuation in samples with lower permittivity values while the modified-Friis model had a higher accuracy in samples with higher clay/water content which have higher permittivity values. Full article

A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost. Full article

Continuous monitoring of breathing activity plays a major role in detecting and classifying a breathing abnormality. This work aims to facilitate detection of abnormal breathing syndromes, including tachypnea, bradypnea, central apnea, and irregular breathing by tracking of thorax movement resulting from respiratory rhythms based on ultrasonic radar detection. This paper proposes a non-contact, non-invasive, low cost, low power consumption, portable, and precise system for simultaneous monitoring of normal and abnormal breathing activity in real-time using an ultrasonic PING sensor and microcontroller PIC18F452. Moreover, the obtained abnormal breathing syndrome is reported to the concerned physician’s mobile telephone through a global system for mobile communication (GSM) modem to handle the case depending on the patient’s emergency condition. In addition, the power consumption of the proposed monitoring system is reduced via a duty cycle using an energy-efficient sleep/wake scheme. Experiments were conducted on 12 participants without any physical contact at different distances of 0.5, 1, 2, and 3 m and the breathing rates measured with the proposed system were then compared with those measured by a piezo respiratory belt transducer. The experimental results illustrate the feasibility of the proposed system to extract breathing rate and detect the related abnormal breathing syndromes with a high degree of agreement, strong correlation coefficient, and low error ratio. The results also showed that the total current consumption of the proposed monitoring system based on the sleep/wake scheme was 6.936 mA compared to 321.75 mA when the traditional operation was used instead. Consequently, this led to a 97.8% of power savings and extended the battery life time from 8 h to approximately 370 h. The proposed monitoring system could be used in both clinical and home settings. Full article

The paper addresses the problem of localization based on hybrid received signal strength (RSS) and time of arrival (TOA) measurements, in the presence of synchronization errors among all the nodes in a wireless network, and assuming all parameters are unknown. In most existing schemes, in fact, knowledge of the model parameters is postulated to reduce the high dimensionality of the cost functions involved in the position estimation process. However, such parameters depend on the operational wireless context, and change over time due to the presence of dynamic obstacles and other modification of the environment. Therefore, they should be adaptively estimated “on the field”, with a procedure that must be as simple as possible in order to suit multiple real-time re-calibrations, even in low-cost applications, without requiring human intervention. Unfortunately, the joint maximum likelihood (ML) position estimator for this problem does not admit a closed-form solution, and numerical optimization is practically unfeasible due to the large number of nuisance parameters. To circumvent such issues, a novel two-step algorithm with reduced complexity is proposed: A first calibration phase exploits nodes in known positions to estimate the unknown RSS and TOA model parameters; then, in a second localization step, an hybrid TOA/RSS range estimator is combined with an iterative least-squares procedure to finally estimate the unknown target position. The results show that the proposed hybrid TOA/RSS localization approach outperformed state-of-the-art competitors and, remarkably, achieved almost the same accuracy of the joint ML benchmark but with a significantly lower computational cost. Full article

This work proposes a novel approach for tracking a moving target in non-line-of-sight (NLOS) environments based on range estimates extracted from received signal strength (RSS) and time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act as an improper antenna array and the range estimates, angle of arrival (AOA) of the signal emitted by the target is first estimated at each reference point. We then show how to take advantage of these angle estimates to convert the problem into a more convenient, polar space, where a linearization of the measurement models is easily achieved. The derived linear model serves as the main building block on top of which prior knowledge acquired during the movement of the target is incorporated by adapting a Kalman filter (KF). The performance of the proposed approach was assessed through computer simulations, which confirmed its effectiveness in combating the negative effect of NLOS bias and superiority in comparison with its naive counterpart, which does not take prior knowledge into consideration. Full article

The rabid growth of today’s technological world has led us to connecting every electronic device worldwide together, which guides us towards the Internet of Things (IoT). Gathering the produced information based on a very tiny sensing devices under the umbrella of Wireless Sensor Networks (WSNs). The nature of these networks suffers from missing sharing among them in both hardware and software, which causes redundancy and more budget to be used. Thus, the appearance of Shared Sensor Networks (SSNs) provides a real modern revolution in it. Where it targets making a real change in its nature from domain specific networks to concurrent running domain networks. That happens by merging it with the technology of virtualization that enables the sharing feature over different levels of its hardware and software to provide the optimal utilization of the deployed infrastructure with a reduced cost. This article is concerned with surveying the idea of SSNs, the difference between it and the traditional WSNs, the requirements for its construction, challenges facing it, and the opportunities that are provided by it, then describing our proposed architectures. As a result of using virtualization technology as a basic block in building SSNs, using different types of virtualization will produce different types of SSNs that will give different usages to it. This article proposes a novel approach of taxonomy for SSNs that is based on the used virtualization techniques, and it describes the needs and usages of each one. It presents a wide array of previously proposed solutions comparing them to each other and a brief description of the issues addressed by each category of that taxonomy. Additionally, the shared sensor architecture and shared network architecture were depicted. Finally, some of its applications in some daily life fields are listed. Full article

In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments. Full article

Thanks to their arising abilities to influence the human lifestyle, along with reducing the healthcare systems’ cost, wireless body area networks (WBANs) still form a strongly growing research field. Recent advances focus on the opportunities of coexistence and communication between a group of WBANs, that will forward the sensing data, using persons as network relays, until reaching a remote analysis server or cloud servers via the Internet, forming thus a body-to-body network (BBN). Such new-style networks support a range of innovative and promising applications, including ubiquitous healthcare (U-health), interactive games, and military, to cite a few. In this paper, we first present the evolution of the single WBAN concept to the cooperative network of multiple WBANs, giving rise to the BBN concept. A synopsis of the WBAN and BBN respective standards and applications is given, and the emerging BBN challenges are highlighted. Then, we present and discuss the existing WBAN proposals, especially the candidate WBAN protocols that could be adapted and used in BBNs, focusing on four intrinsically related axes of great importance for BBN design: energy efficiency, mobility prediction, quality of service (QoS) and security. Further BBN open issues are also investigated, namely, the wireless propagation between humans carrying wearable devices, the interference, storage and privacy issues as well as the heterogeneity of BBN devices and traffic. Full article

The increasing demand for location-dependent services in wireless sensor networks (WSNs) calls for solutions capable of handling the diversified demands and the unique challenges presented in WSNs. In most applications, nodes need to determine their locations in a reliable manner while operating under stringent constraints in computation, communication, and energy resources. This paper offers a novel solution to bridge the gap between the high accuracy demand and low resources available for range-based localization. We propose KickLoc, a fully distributed scheme, which considers the uncertainty of the distance measurements to minimize localization errors introduced from the range measurement, and leverages information from all neighboring nodes for better position estimations. Our work is evaluated via extensive simulations, with comparisons to other well-known localization schemes, and the Cramér-Rao lower bound (CRLB). In addition, we implement and evaluate the proposed system on sensor platforms with different range measurement mechanisms. The results show that this localization solution outperforms existing methods in various scenarios, while remains lightweight and suitable for small, low resources WSNs. Full article

The Internet of Things (IoT) is the global network of interrelated physical devices such as sensors, actuators, smart applications, objects, computing devices, mechanical machines, and people that are becoming an essential part of the internet. In an industrial environment, these devices are the source of data which provide abundant information in manufacturing processes. Nevertheless, the massive, heterogeneous, and time-sensitive nature of the data brings substantial challenges to the real-time collection, processing, and decision making. Therefore, this paper presents a framework of an IoT-based Industrial Data Management System (IDMS) which can manage the huge industrial data, support online monitoring, and control smart manufacturing. The framework contains five basic layers such as physical, network, middleware, database, and application layers to provide a service-oriented architecture for the end users. Experimental results from a smart factory case study demonstrate that the framework can manage the regular data and urgent events generated from various factory devices in the distributed industrial environment through state-of-the-art communication protocols. The collected data is converted into useful information which improves productivity and the prognosis of production lines. Full article

Thanks to IEEE 802.15.4 defining the operation of low-rate wireless personal area networks (LR-WPANs), the door is open for localizing sensor nodes using tiny, low power digital radios such as Zigbee. In this paper, we propose a three-dimensional (3D) localization scheme based on well-known loop invariant for division algorithm. Parametric points are proposed by using the reference anchor points bounded in an outer region named as Parametric Loop Division (PLD) algorithm. Similar to other range-based localization methods, PLD is often influenced by measurement noise which greatly degrades the performance of PLD algorithm. We propose to adopt extended Kalman filtering (EKF) to refine node coordinates to mitigate the measurement noise. We provide an analytical framework for the proposed scheme and find the lower bound for its localization accuracy. Simulation results show that compared with the existing PLD algorithm, our technique always achieves better positioning accuracy regardless of network topology, communication radius, noise statistics, and the node degree of the network. The proposed scheme PLD-EKF provides an average localization accuracy of 0.42 m with a standard deviation of 0.26 m. Full article

Ultra-Dense Network (UDN) deployment is considered a key element to achieve the requested capacity in future fifth-generation (5G) mobile networks. Backhaul networks in UDNs are formed by heterogeneous links with multi-hop connections and must handle massive traffic. Backhauling in future 5G networks may represent the capacity bottleneck. Therefore, there is the need for efficient and flexible routing schemes able to handle the dynamism of the traffic load in capacity-limited networks. Toward this goal, the emerging Software-Defined Network (SDN) paradigm provides an efficient solution, transferring the routing operation from the data plane switches to a central controller, thus achieving more flexibility, efficiency, and faster convergence time in comparison to conventional networks. This paper proposes and investigates an SDN-approach for an efficient routing in a capacity-limited backhaul network that carries data and control traffic of a heterogeneous UDN. The routing algorithm is centralized in the SDN controller and two different types of traffic flow are considered: data and control plane coordination traffic. The goal is to reduce or even to avoid the amount of traffic that the backhaul network is not able to support, distributing in a fair way the eventual lack of bandwidth among different access points. Simulation results show that with the considered approach the performance significantly improves, especially when there is an excess of traffic load in the network. Moreover, thanks to the SDN-based design, the network can reconfigure the traffic routing depending on the changing conditions. Full article

As Internet of Things (IoT) involvement increases in our daily lives, several security and privacy concerns like linkability, unauthorized conversations, and side-channel attacks are raised. If they are left untouched, such issues may threaten the existence of IoT. They derive from two main reasons. One is that IoT objects are equipped with limited capabilities in terms of computation power, memory, and bandwidth which hamper the direct implementation of traditional Internet security techniques. The other reason is the absence of widely-accepted IoT security and privacy guidelines and their appropriate implementation techniques. Such guidelines and techniques would greatly assist IoT stakeholders like developers and manufacturers, paving the road for building secure IoT systems from the start and, thus, reinforcing IoT security and privacy by design. In order to contribute to such objective, we first briefly discuss the primary IoT security goals and recognize IoT stakeholders. Second, we propose a comprehensive list of IoT security and privacy guidelines for the edge nodes and communication levels of IoT reference architecture. Furthermore, we point out the IoT stakeholders such as customers and manufacturers who will benefit most from these guidelines. Moreover, we identify a set of implementation techniques by which such guidelines can be accomplished, and possible attacks against previously-mentioned levels can be alleviated. Third, we discuss the challenges of IoT security and privacy guidelines, and we briefly discuss digital rights management in IoT. Finally, through this survey, we suggest several open issues that require further investigation in the future. To the best of the authors’ knowledge, this work is the first survey that covers the above-mentioned objectives. Full article

A new positioning algorithm for distance measurement systems is outlined herein. This algorithm utilizes a non-linear error function which allows us to improve the positioning accuracy in highly difficult indoor environments. The non-linear error function also allows us to adjust the performance of the algorithm to the particular environmental conditions. The well-known positioning algorithms have limitations, mentioned by their authors, which make them unsuitable for positioning in an indoor environment. In this article, there is a brief discussion about the most popular positioning algorithms with consideration of the indoor environment. The new positioning algorithm is described in detail and a comparative performance analysis of the well-known algorithms and the proposed one is conducted. Those research results are achieved with the utilization of real distance measurement data, collected inside a few different buildings, and they show that the proposed algorithm outperforms the Chan and Foy algorithms in indoor environments. In this article the Automatic Person Localization System (SALOn) is also presented, which was utilized to collect measurement data. Full article

The term smart grid (SG) has been used by many government bodies and researchers to refer to the new trend in the power industry of modernizing and automating the existing power system. SGs must utilize assets optimally by making use of the information, like equipment capacity, voltage drop, radial network structure, minimizing investment and operating costs, minimizing energy loss and reliability indices, and so on. One way to achieve this is to re-route or reconfigure distribution systems (DSs). Distribution systems are reconfigured to choose a switching combination of branches of the system that optimize certain performance parameters of the power supply, while satisfying some specified constraints. In this paper, a blended biased and unbiased weightage (BBUW) multiple attribute decision-making (MADM) method is proposed for finding the compromised best configuration and compared it with other decision-making methods, such as the weighted sum method (WSM), weighted product method (WPM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The BBUW method is implemented for two distribution systems, and the result obtained shows a good co-relationship between BBUW and other decision-making methods. Further weights obtained from the BBUW method are used for the WSM, WPM and TOPSIS methods for decision making. Examples of the distribution system are worked out in this paper to demonstrate the validity and effectiveness of the method. Full article

Fifth-generation (5G) mobile systems are a necessary step toward successfully achieving further increases in data rates. As the use of higher-order quadrature amplitude modulation (QAM) is expected to increase data rates within a limited bandwidth, we propose a method for orthogonal frequency division multiplexing (OFDM)-based 1024- and 4096-QAM transmission with soft-decision Viterbi decoding for use in 5G mobile systems. Through evaluation of the transmission performance of the proposed method over multipath fading channels using link-level simulations, we determine the bit error rate (BER) performance of OFDM-based 1024- and 4096-QAM as a function of coding rate under two multipath fading channel models: extended pedestrian A (EPA) and extended vehicular A (EVA). We also demonstrate the influence of phase error on OFDM-based 1024- and 4096-QAM and clarify the relationship between phase error and the signal-to-noise ratio (SNR) penalty required to achieve a BER of 1 × 10⁻². This work provides an effective solution for introducing higher-order modulation schemes in 5G and beyond. Full article