International Journal of Distributed Sensor Networks The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . All rights reserved. Force-Sensing Glove System for Measurement of Hand Forces during Motorbike Riding Sun, 29 Nov 2015 14:14:25 +0000 Accurate measurement of hand forces in motorbike riding is highly desirable for studies of safe riding. In this paper, we implement a force-sensing glove system for measuring real-time hand forces during motorbike riding with the aim of giving feedback to the riders. It consists of a pair of gloves with tactile sensors suitably mounted and configured for data acquisition via a wireless smartphone. A novel calibration method is developed for dynamic calibration considering force measurement in natural operation and environments. Consequently, a series of data classification algorithms ensure accurate hand performance feedbacks for motorbike riders. The feedback data could potentially alert the riders to predict and prevent accidents. Validation tests demonstrate that this force-sensing glove system has a strong potential as a tool for hand performance monitoring in real environment. Qiang Ye, MirHojjat Seyedi, Zibo Cai, and Daniel T. H. Lai Copyright © 2015 Qiang Ye et al. All rights reserved. PIR Sensors Deployment with the Accessible Priority in Smart Home Using Genetic Algorithm Thu, 26 Nov 2015 11:17:00 +0000 In smart home, location estimation based on PIR sensors is very popular. Existing methods by various sensors technologies and intelligent algorithms are used to achieve a high accuracy. In fact, how to deploy the PIR sensor is directly related to the accuracy. In this paper, we present an approach to deploying the PIR sensor based on the accessible priority by genetic algorithm. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the PIR sensor deployment for smart home. The fitness function of GA is based on the accessible priority of indoor areas. The accessible priority value of different area is set according to the indoor environment and daily accessible habits. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of accessible frequency. Dan Yang, Kaiyou Rao, Bin Xu, and Weihua Sheng Copyright © 2015 Dan Yang et al. All rights reserved. Cognitive Radio Enabled Wireless Sensor Networks and Survivability Challenges Thu, 26 Nov 2015 06:25:56 +0000 Shamik Sengupta, Walid Saad, and Abhishek Roy Copyright © 2015 Shamik Sengupta et al. All rights reserved. Adaptive Sensing Private Property Protection Protocol Based on Cloud Wed, 25 Nov 2015 14:28:23 +0000 Private property refers to something carrying private information, or expensive items; these items are very important for companies or individuals. The proposed private property protection system uses adaptive sensing technology to protect private materials in real time. In this paper, we propose an adaptive sensing private property authentication scheme which can be applied in the cloud computing. Considering a relatively safe room with a remote reader, there are several valuable items in the room. Each item is labeled with a unique tamper-evident adaptive sensor and the reader can simultaneously read a plurality of sensors. Encrypted information of items, sensors, and readers is stored in the cloud. The reader reads sensors and uploads the collected data to the cloud for further processing in real time. The proposed scheme is under the cloud environment to protect the user privacy and prevent synchronized attacks. Compared with some traditional schemes, our scheme is economical, practical, and easy to be expanded. Furthermore, it pays attention to privacy protection with real-time monitoring. Kai Fan, Wei Wang, Hui Li, and Yintang Yang Copyright © 2015 Kai Fan et al. All rights reserved. Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing Wed, 25 Nov 2015 12:02:48 +0000 The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. However, the sparsity of raw sensed data in some case is not straightforward. In this paper, we present reshuffling cluster compressed sensing based data gathering (RCCSDG) method to achieve both energy efficiency and reconstruction accuracy in WSNs. By incorporating CS into the cluster protocol, RCCSDG is able to reduce the energy consumption and support larger networks. Moreover, the sparsity of raw sensed data can be greatly improved by reshuffling pretreatment. A theoretical analysis to energy consumption of cluster head is performed, and the cost of the pretreatment is small enough to be neglected. Based on these natures, the raw sensed data can be recovered from fewer samples. Also, considering the sensed data to be of excellent temporal stability in a short time, we reshuffle them just one time in this stable period to further reduce the energy consumption of WSNs. In addition, the delay of RCCSDG is analyzed based on TDMA2 scheduling scheme. We carry out simulations on real sensor datasets. The results show that the RCCSDG can effectively compress the data transmission and decrease energy consumption of WSNs while ensuring the reconstruction accuracy. Lu Zhu, Baishan Ci, Yuanyuan Liu, and Zhizhang (David) Chen Copyright © 2015 Lu Zhu et al. All rights reserved. Optimal Report Strategies for WBANs Using a Cloud-Assisted IDS Wed, 25 Nov 2015 09:49:15 +0000 Applying an Intrusion Detection System (IDS) to Wireless Body Area Networks (WBANs) becomes a costly task for body sensors due to their limited resources. To solve this problem, a cloud-assisted IDS framework is proposed. We adopt a new distributed-centralized mode, where IDS agents residing in body sensors will be triggered to launch. All IDS agents are only responsible for reporting the monitored events, not intrusion decision that is processed in the cloud platform. We then employ the signaling game to construct an IDS Report Game (IDSRG) depicting interactions between a body sensor and its opponent. The pure- and mixed-strategy Bayesian Nash Equilibriums (BNEs) of the stage IDSRG are achieved, respectively. As two players interact continually, we develop the stage IDSRG into a dynamic multistage game in which the belief can be updated dynamically. Upon the current belief, the Perfect Bayesian Equilibrium (PBE) of the dynamic multistage IDSRG is attained, which helps the IDS-sensor select the optimal report strategy. We afterward design a PBE-based algorithm to make the IDS-sensor decide when to report the monitored events. Experiments show the effectiveness of the dynamic multistage IDSRG in predicting the type and optimal strategy of a malicious body sensor. Shigen Shen, Keli Hu, Longjun Huang, Hongjie Li, Risheng Han, and Qiying Cao Copyright © 2015 Shigen Shen et al. All rights reserved. Mixed and Continuous Strategy Monitor-Forward Game Based Selective Forwarding Solution in WSN Wed, 25 Nov 2015 09:47:14 +0000 Wireless sensor networks are often deployed in unattended and hostile environments. Due to the resource limitations and multihop communication in WSN, selective forwarding attacks launched by compromised insider nodes are a serious threat. A trust-based scheme for identifying and isolating malicious nodes is proposed and a mixed strategy and a continuous strategy Monitor-Forward game between the sender node and its one-hop neighboring node is constructed to mitigate the selective dropping attacks in WSN. The continuous game will mitigate false positives on packet dropping detection on unreliable wireless communication channel. Simulation results demonstrate that continuous Monitor-Forward game based selective forwarding solution is an efficient approach to identifying the selective forwarding attacks in WSN. Hongmei Liao and Shifei Ding Copyright © 2015 Hongmei Liao and Shifei Ding. All rights reserved. Experiencing Commercialized Automated Demand Response Services with a Small Building Customer in Energy Market Wed, 25 Nov 2015 09:01:23 +0000 An Automated Demand Response is the most fundamental energy service that contributes to balancing the power demand with the supply, in which it realizes extensive interoperations between the power consumers and the suppliers. The OpenADR specification has been developed to facilitate the service communications, and several facilities offer primitive forms of services in a retail market. However, few researches have reported the details of such a real-world service yet, and thus we are still unaware of how it works exactly. Instead, we rely on our textbooks to design next generations of the ADR service. To overcome the discrepancy of our understanding, this paper shares our hand-on experiences on the commercialized ADR service. In particular, we deploy smart submeters to manage energy loads and install an energy management system in a small commercial facility, helping the owner participate in the ADR service that a local utility offers. The building owner makes a service contract with a qualified load aggregator based on her curtailment rate, a reference point that decides the success of her load curtailment. With the rate, the customer facility participates in three DR events for tests that last for 2, 1, and 3 hours, respectively. Our experimental results are illustrated with discussions on various aspects of the service. Eun-Kyu Lee Copyright © 2015 Eun-Kyu Lee. All rights reserved. A Novel M2M Backbone Network Architecture Tue, 24 Nov 2015 13:52:13 +0000 Network architecture analysis is a curial issue for a large scale Machine-To-Machine (M2M) network. Considering an M2M backbone network which consists of distributed satellite clusters in geosynchronous orbit (GEO), a new distributed satellite cluster network (DSCN) hybrid topology architecture is proposed in this paper. To the best of the authors’ knowledge, the conceptions of domains, strong/weak link, hubs, small world, and degree realizability are proposed for the first time in the DSCN based M2M backbone networks. How these features affect the network is given through analysis and simulation. By employing Network Science Theory, a strong constraint DSCN topology is presented. In addition, we compare the DSCN with several typical network topologies. Results show that the proposed hybrid architecture realizes a stunning trade-off between the efficiency and robustness. Feihong Dong, Qinfei Huang, Hongjun Li, Bo Kong, and Wei Zhang Copyright © 2015 Feihong Dong et al. All rights reserved. A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup Tue, 24 Nov 2015 13:10:39 +0000 Radio Frequency Identification (RFID) is a solution for automated inventory and object detection applications. However, if RFID tags are attached to metal objects, detection errors may occur due to Foucault currents and interferences caused by multiple simultaneous reflections. Errors may increase if metal objects are moving. The paper presents a novel algorithm using RFID low-level reader variables, such as RSSI (Received Signal Strength Indicator), phase angle, and Doppler shift, to detect and trace metal objects. The algorithm was designed to identify if a tag is static or moving and, in the latter case, to compute its speed and direction. The algorithm differs from previous approaches since it uses a simple setup with one commercial portal reader coupled with one single element antenna. Experiments employed one tag located on one metal moving object and 12 static interferer tags, in both outdoor and indoor locations. Results show that the algorithm identifies static tags with no errors. For moving tags, the algorithm shows a maximum 12% error. The algorithm correctly estimates direction and computes object speed. Test conditions emulate fork lift speeds when carrying objects in an industrial warehouse. Wendy Navarro, Juan C. Velez, Norelli Schettini, and Maria Calle Copyright © 2015 Wendy Navarro et al. All rights reserved. Enhancing Internet and Distributed Computing Systems with Wireless Sensor Networks Tue, 24 Nov 2015 08:22:31 +0000 Giancarlo Fortino, Raffaele Gravina, Wenfeng Li, Mohammad Mehedi Hassan, and Antonio Liotta Copyright © 2015 Giancarlo Fortino et al. All rights reserved. QoS Routing RPL for Low Power and Lossy Networks Tue, 24 Nov 2015 07:54:36 +0000 Energy conservation, while ensuring an adequate level of service, is a major concern in Low power and Lossy Networks (LLNs), because the nodes are typically deployed and are not replaced in case of failure. Several efforts have recently led to the standardization of a routing protocol for LLNs. The standard provides several criteria that can be used as a routing metric. The working group RoLL of the IETF developed a routing protocol for 6LoWPAN sensor network (IPv6 over IEEE 802.15.4) (Ko et al., 2011), RPL, recently standardized. Using this protocol could become common and standard in IPv6 sensor networks in the future. Most implementation of the protocol makes use of the transmission rate successfully (ETX) as metric and focuses on the reliability of links. In this paper we present the use of the residual energy and the transmission delay as routing metric in the next hop selection process for the RPL protocol. We design an objective function for this metric based on ant colony optimization (ACO), and then we compare the results of experiments realized with the RPL based on ETX. Belghachi Mohamed and Feham Mohamed Copyright © 2015 Belghachi Mohamed and Feham Mohamed. All rights reserved. Data Analysis with a Wireless Multisensory Toxic Gas Detection System Tue, 24 Nov 2015 06:45:41 +0000 This paper proposes a wireless multisensory toxic gas detection system. The system allows remote wireless detection of four types of toxic gases, specifically Cl2, CO, NO2, and SO2, using gas detection technologies and wireless communication technologies such as ZigBee and Wi-Fi. Further, we analyze the data collected from sensors to determine a correspondence between the sensors and the gases and establish recognition models for different gases. Through multiple data calibration levels and industrial experiments, we have verified the feasibility of the system, along with its gas detection accuracy and long-term stability. Qiong Wu and Yunbo Shi Copyright © 2015 Qiong Wu and Yunbo Shi. All rights reserved. FloorLoc-SL: Floor Localization System with Fingerprint Self-Learning Mechanism Mon, 23 Nov 2015 16:53:35 +0000 Nowadays, a mobile phone plays an important role in daily life. There are many applications developed for mobile phones. Location service application is one kind of mobile application that serves location information. GPS receiver is embedded on a mobile phone for localization. However, GPS cannot provide localization service over indoor scenario efficiently. This is because obstacles and structures of building block GPS signal from the satellites. Many indoor localization systems have been proposed but most of them are developed over single-floor scenario only. The dimension of altitudes in localization results will be missed. In this paper, we propose floor localization system. The proposed system does not need any site survey and any support from back-end server. It has a self-learning algorithm for creating fingerprint in each floor. The self-learning algorithm utilizes sensors on the mobile phone for detecting trace of mobile phone user. This algorithm is low computation complexity, which can be operated on any mobile phones. Moreover, the mobile phone can exchange fingerprints with others via virtual ad hoc network instead of learning all floor fingerprints by themselves only. Our proposed floor localization system achieves 87% of accuracy. Kornkanok Khaoampai, Kulit Na Nakorn, and Kultida Rojviboonchai Copyright © 2015 Kornkanok Khaoampai et al. All rights reserved. NDSL: Node Density-Based Subregional Localization in Large Scale Anisotropy Wireless Sensor Networks Mon, 23 Nov 2015 14:09:39 +0000 Localization is emerging as a fundamental component in wireless sensor network and is widely used in the fields of environmental monitoring, national defense and military, transportation, and so on. Current positioning system, however, can only locate an object’s position in isotropy wireless sensor network with high accuracy but cannot locate it accurately in anisotropy wireless sensor network. Besides, past proposals only mentioned anisotropy to show that connectivity of network is different in each direction. However, how to quantify the degree of anisotropy is not clearly pointed out. This paper introduces NDSL (node density-based subregional localization), a positioning system that is used in anisotropy wireless sensor network. The network is divided into many subregions where the nodes density is relatively uniform and then corrects the single-hop distance for each beacon node to locate unknown nodes. We also use nodes distribution and signals distribution to build a model to evaluate the degree of anisotropy for anisotropy network. Through the analysis of the degree of anisotropy for different topologies, the results show that the model is consistent with the facts. Results from actual deployments and simulation experiments show that the accuracy of NDSL algorithm obviously improves compared with DV-Hop algorithm. Zhanyong Tang, Jie Zhang, Liang Wang, Jinzhi Han, Dingyi Fang, and Anwen Wang Copyright © 2015 Zhanyong Tang et al. All rights reserved. Stackelberg Game Based Power Control with Outage Probability Constraints for Cognitive Radio Networks Mon, 23 Nov 2015 12:23:20 +0000 This paper firstly investigates the problem of uplink power control in cognitive radio networks (CRNs) with multiple primary users (PUs) and multiple second users (SUs) considering channel outage constraints and interference power constraints, where PUs and SUs compete with each other to maximize their utilities. We formulate a Stackelberg game to model this hierarchical competition, where PUs and SUs are considered to be leaders and followers, respectively. We theoretically prove the existence and uniqueness of robust Stackelberg equilibrium for the noncooperative approach. Then, we apply the Lagrange dual decomposition method to solve this problem, and an efficient iterative algorithm is proposed to search the Stackelberg equilibrium. Simulation results show that the proposed algorithm improves the performance compared with those proportionate game schemes. Helin Yang, Xianzhong Xie, and Athanasios V. Vasilakos Copyright © 2015 Helin Yang et al. All rights reserved. Pworm: Passive and Real-Time Wormhole Detection Scheme for WSNs Mon, 23 Nov 2015 08:29:53 +0000 Wormhole attack is one of the severe threats to wireless sensor and ad hoc networks. Most of the existing countermeasures either require specialized hardware or demand high network overheads in order to capture the specific symptoms induced by the wormholes, which in result limits their applicability. In this paper, we exploit an inevitable symptom of wormholes and present Pworm, a passive wormhole detection and localization system based upon the key observation that a large amount of network traffic will be attracted by the wormholes. The proposed scheme is passive, real-time, and efficient against both active and passive wormholes. Our approach silently observes the variations in network topology to infer the wormhole existence and solely relies on network routing information. It does not necessitate specialized hardware or poses rigorous assumptions on network features. We evaluate our scheme through extensive simulations of 100 to 800 nodes for various network scales and show that Pworm is well suited for false alarms, scalability, and time delay in terms of activation as well as detection latencies. Li Lu, Muhammad Jawad Hussain, Guoxing Luo, and Zhigang Han Copyright © 2015 Li Lu et al. All rights reserved. Enabling Technologies for Next-Generation Sensor Networks: Prospects, Issues, Solutions, and Emerging Trends Sun, 22 Nov 2015 08:22:00 +0000 Muhammad Imran, Sana Ullah, Ansar-Ul-Haque Yasar, Athanasios Vasilakos, and Sajid Hussain Copyright © 2015 Muhammad Imran et al. All rights reserved. Efficient Aerial Data Collection with UAV in Large-Scale Wireless Sensor Networks Sun, 22 Nov 2015 06:48:47 +0000 Data collection from deployed sensor networks can be with static sink, ground-based mobile sink, or Unmanned Aerial Vehicle (UAV) based mobile aerial data collector. Considering the large-scale sensor networks and peculiarity of the deployed environments, aerial data collection based on controllable UAV has more advantages. In this paper, we have designed a basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network. We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal of a Fast Path Planning with Rules (FPPWR) algorithm based on grid division, to increase the efficiency of path planning, while guaranteeing the length of the path to be relatively short. We have designed and implemented a simulation platform for aerial data collection from sensor networks and have validated performance efficiency of the proposed framework based on the following parameters: time consumption of the aerial data collection, flight path distance, and volume of collected data. Chengliang Wang, Fei Ma, Junhui Yan, Debraj De, and Sajal K. Das Copyright © 2015 Chengliang Wang et al. All rights reserved. Exploration of Prominent Frequency Wave in EEG Signals from Brain Sensors Network Wed, 18 Nov 2015 13:39:34 +0000 We investigated the signals regularity of electroencephalography (EEG) channels separately and determined the energy of selected frequency waves, such as, δ, θ, α, β, and γ. The goal of this research is to identify the prominent frequency band from selected frequencies. We recorded the EEG signal data of 30 controlled subjects with 18 EEG channels. These subjects are all males with an average age of 24 years. Emotional stimuli related to different emotions were presented to each of selected candidates. EEG data were extracted and further processed for artifact removal, filtering, epoch selection and averaging of the signals. We designed and tested our method for exploring the frequency waves of all EEG channels. We also employed the Hjorth parameters to measure the signal regularity in time and frequency domain. The detailed physiological response of human subjects is also presented in this paper. Our results showed that the energy level of delta wave is mostly high in all cases. Raja Majid Mehmood and Hyo Jong Lee Copyright © 2015 Raja Majid Mehmood and Hyo Jong Lee. All rights reserved. Smart One-Channel Sensor Node for Ambient Vibration Test with Applications to Structural Health Monitoring of Large Civil Infrastructures Tue, 17 Nov 2015 11:11:39 +0000 Dynamic characteristics of structures have been monitored for safe operation and efficient maintenance of large civil infrastructures. For vibration data measurement, the conventional system uses cables, which cause very expensive costs and inconvenient installation. Therefore, various wireless sensor nodes have been developed to replace the conventional wired system. However, there still remain lots of issues to be resolved such as time synchronization between sensor nodes, data loss, data security, and power supply. In this study, Smart One-Channel Sensor Node (SOSN) was developed to measure vibration data, which can practically solve the issues on installation, time synchronization, and data storage. It is designed for temporal measurement with a limited capacity to operate for several hours using embedded batteries. Laboratory tests were carried out to verify the performance of the developed SOSN compared with conventional wired system. Its practical advantages were investigated through three full-scale tests on large civil infrastructures. Three field applications revealed that SOSN is a very practical tool for short-term monitoring of large civil infrastructures with respect to traffic control, installation time and convenience, secure data gathering, and so forth. Young-Soo Park, Sehoon Kim, Sung-Han Sim, Ki-Young Koo, Wontae Lee, and Jong-Jae Lee Copyright © 2015 Young-Soo Park et al. All rights reserved. A Review of the Role of Sensors in Mobile Context-Aware Recommendation Systems Mon, 16 Nov 2015 12:24:09 +0000 Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios. Sergio Ilarri, Ramón Hermoso, Raquel Trillo-Lado, and María del Carmen Rodríguez-Hernández Copyright © 2015 Sergio Ilarri et al. All rights reserved. A Framework and Classification for Fault Detection Approaches in Wireless Sensor Networks with an Energy Efficiency Perspective Mon, 16 Nov 2015 08:56:13 +0000 Wireless Sensor Networks (WSNs) are more and more considered a key enabling technology for the realisation of the Internet of Things (IoT) vision. With the long term goal of designing fault-tolerant IoT systems, this paper proposes a fault detection framework for WSNs with the perspective of energy efficiency to facilitate the design of fault detection methods and the evaluation of their energy efficiency. Following the same design principle of the fault detection framework, the paper proposes a classification for fault detection approaches. The classification is applied to a number of fault detection approaches for the comparison of several characteristics, namely, energy efficiency, correlation model, evaluation method, and detection accuracy. The design guidelines given in this paper aim at providing an insight into better design of energy-efficient detection approaches in resource-constraint WSNs. Yue Zhang, Nicola Dragoni, and Jiangtao Wang Copyright © 2015 Yue Zhang et al. All rights reserved. A Gradient-Assisted Energy-Efficient Backpressure Scheduling Algorithm for Wireless Sensor Networks Mon, 16 Nov 2015 08:35:37 +0000 Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work. Zhenzhen Jiao, Rui Tian, Baoxian Zhang, and Cheng Li Copyright © 2015 Zhenzhen Jiao et al. All rights reserved. DYSSS: A Dynamic and Context-Aware Security System for Shared Sensor Networks Sun, 15 Nov 2015 13:35:48 +0000 In recent years, we have witnessed the emergence of Shared Sensor Networks (SSNs) as a core component of cyber-physical systems for diverse applications. As Wireless Sensor and Actuator Networks (WSANs) design starts shifting from application-specific platforms to shared system infrastructures, a pressing research challenge is security. In scenarios involving unprotected hostile outdoor areas, SSNs are prone to different types of attacks that can compromise reliability, integrity, and availability of the sensor data traffic and sensor lifetime as well. In this work we propose a Dynamic Security System to be applied in the shared sensor network context. Its basic feature is the nodes neighborhood monitoring and collaboration (through the use of the Byzantine algorithm) to identify an attack and enhance security. The proposed security system is dynamic since it is able to manage the availability, integrity, and confidentiality of multiple applications according to the current execution context. It is also resilient, since it is able to support the continuous network operation even in the presence of malicious or faulty nodes. Its resilience is achieved for the capacity of gathering information from several nodes, thus inferring the countermeasures using context information. Claudio M. de Farias, Luci Pirmez, Luiz F. R. C. Carmo, Davidson Boccardo, Flávia C. Delicato, Igor L. dos Santos, Renato Pinheiro, and Rafael O. Costa Copyright © 2015 Claudio M. de Farias et al. All rights reserved. Wireless Coexistence and Spectrum Sensing in Industrial Internet of Things: An Experimental Study Sun, 15 Nov 2015 08:00:20 +0000 The adoption of dense wireless sensor networks in industrial plants is mandatorily paired with the development of methods and tools for connectivity prediction. These are needed to certify the quality (or reliability) of the network information flow in industrial scenarios which are typically characterized by harsh propagation conditions. Connectivity prediction must account for the possible coexistence of heterogeneous radio-access technologies, as part of the Industrial Internet of Things (IIoT) paradigm, and easily allow postlayout validation steps. The goal of this paper is to provide a practical evaluation of relevant coexistence problems that may occur between industrial networks employing standards such as WirelessHART IEC 62591, IEEE 802.15.4, and IEEE 802.11. A number of coexistence scenarios are experimentally tested using different radio platforms. For each case, experimental results are analyzed to assess tolerable interference levels and sensitivity thresholds for different configurations of channel overlapping. Finally, the problem of over-the-air spectrum sensing is investigated in real scenarios with heterogeneous industrial networks to enable a cognitive resource allocation that avoids intolerable interference conditions. Jean M. Winter, Ivan Muller, Gloria Soatti, Stefano Savazzi, Monica Nicoli, Leandro Buss Becker, João C. Netto, and Carlos E. Pereira Copyright © 2015 Jean M. Winter et al. All rights reserved. Sequential Multidimensional Scaling with Kalman Filtering for Location Tracking Wed, 11 Nov 2015 10:48:38 +0000 Localization always plays a critical role in wireless sensor networks for a wide range of applications including military, healthcare, and robotics. Although the classical multidimensional scaling (MDS) is a conventionally effective model for positioning, the accuracy of this method is affected by noises from the environment. In this paper, we propose a solution to attenuate noise effects to MDS by combining MDS with a Kalman filter. A model is built to predict the noise distribution with regard to additive noises to the distance measurements following the Gaussian distribution. From that, a linear tracking system is developed. The characteristics of the algorithm are examined through simulated experiments and the results reveal the advantages of our method over conventional works in dealing with the above challenges. Besides, the method is simplified with a linear filter; therefore it suits small and embedded sensors equipped with limited power, memory, and computational capacities well. Lan Anh Trinh, Nguyen Duc Thang, Dang Viet Hung, and Tran Cong Hung Copyright © 2015 Lan Anh Trinh et al. All rights reserved. Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems Wed, 11 Nov 2015 08:42:36 +0000 We propose two new multisensory fusion predictors for an arbitrary nonlinear function of the state vector in a discrete-time linear dynamic system. Nonlinear function of the state (NFS) represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target system for automatic control. To estimate the NFS using multisensory information, we propose centralized and decentralized predictors. For multivariate polynomial NFS, we propose an effective closed-form computation procedure for the predictor design. For general NFS, the most popular procedure for the predictor design is based on the unscented transformation. We demonstrate the effectiveness and estimation accuracy of the fusion predictors on theoretical and numerical examples in multisensory environment. Ha Ryong Song, Il Young Song, and Vladimir Shin Copyright © 2015 Ha Ryong Song et al. All rights reserved. Mitigating On-Off Attacks in the Internet of Things Using a Distributed Trust Management Scheme Wed, 11 Nov 2015 08:07:02 +0000 In the Internet of Things (IoT), physical objects are able to provide or require determined services. The purpose of this work is to identify malicious behavior of nodes and prevent possible On-Off attacks to a multiservice IoT. The proposed trust management model uses direct information generated from direct communication with the nodes to evaluate trust between nodes. This distributed approach allows nodes to be completely autonomous in making decisions about the behavior of other nodes. We perform network simulations using Contiki-OS to analyze the performance of the proposed trust model. Simulation results show effectiveness against On-Off attacks and also a good performance to recognize malicious nodes in the network. Carolina V. L. Mendoza and João H. Kleinschmidt Copyright © 2015 Carolina V. L. Mendoza and João H. Kleinschmidt. All rights reserved. An Intelligent Power Outlet System for the Smart Home of the Internet of Things Wed, 11 Nov 2015 07:36:37 +0000 This paper presents an intelligent power outlet system that can be controlled wirelessly and that has been specifically designed to monitor electrical events in low-current loads. Each power outlet of the system embeds a microcontroller, a 2.4 GHz ZigBee interface, RFID (Radio Frequency Identification) reader, a relay, and a current sensor. The main features of the system include the remote control of the power outlet, real-time monitoring of the current consumption, the customization and programming of the power supply time schedule, the automatic interruption of vampire currents, and the prevention of certain types of electrical fires and electrocutions. A prototype with such features has been implemented and tested in a simple home automation network in order to validate its functionalities. The results show that the system reacts fast and avoids overconsumptions and electrocutions, being able to make the next generation of homes safer and smarter. Tiago M. Fernández-Caramés Copyright © 2015 Tiago M. Fernández-Caramés. All rights reserved.