International Journal of Sensor Networks (19 papers in press)
Recent Advances in Wireless Sensor Networks with Environmental Energy Harvesting
by Lei Shu, Wanjiun Liao, Jaime Lloret, Lei Wang
Centroid determination hardware algorithm for star trackers
by Gabriel Mariano Marcelino, Victor Hugo Schulz, Laio Oriel Seman, Eduardo Bezerra
Abstract: The execution of centroid extraction algorithms using a microprocessor consumes considerable resources when compared to the other steps involved in star trackers. This paper presents a method to identify star centroids in star trackers by pre-processing the pixels using an FPGA directly in the stream transmitted by an image sensor. The dedicated hardware filters the star pixels and transmits them to a processor, which computes the centroids of the respective image using an infinite impulse response filter. Thus, there is a substantial decrease in memory consumption and a reduction of the processor usage during the attitude determination computation, making the process more attractive for small satellites. A hardware-in-the-loop simulation is presented to test the performance of the system. It was possible to achieve a subpixel precision in the centroid coordinates' estimation, and also lower execution times in comparison with methods based on the processing of whole images.
Keywords: Embedded Systems; Nanosatellites; Attitude Determination; Star Trackers; Centroid Determination; FPGA.
Low-Cost Localization Considering LOS/NLOS Impacts in Challenging Indoor Environments
by Vahideh Moghtadaiee, Nasim Alikhani, Seyed Ali Ghorashi
Abstract: One popular localization method in Wireless Sensor Networks (WSN) and Wireless Local Area Networks (WLAN) is fingerprinting technique, in which Received Signal Strength (RSS) values are measured by smart-phone internal sensors at some Reference Points (RPs) and stored in a radio map. However, constructing the radio map is time-consuming and labor-intensive. In this paper, we propose a novel method to decrease the training cost by building a simulated radio map using an improved path-loss model in which the impacts of Line of Sight (LOS) and Non-Light-of-Sight (NLOS) propagations are taken into account. Including LOS/NLOS effects also improves distance estimation. Furthermore, the simulated radio map helps assess and improve the fingerprinting area and network parameters prior to the actual positioning. For performance evaluation, three kinds of radio maps are created using simulation and a test field experiment and then compared based on deterministic and probabilistic algorithms. The results indicate that the improved model outperforms the typical path-loss model and the localization error gets closer to the actual error of the fingerprinting network.
Keywords: Indoor localization; Fingerprinting; Received Signal Strength (RSS); LOS; NLOS.
Using Neural Networks to Reduce Sensor Cluster Interferences and Power Consumption in Smart Cities
by Per Lynggaard
Abstract: In the future smart cities, billions of communicating IoT devices are expected which communicate wirelessly in the limited spectrum offered by 5G and long-range technologies. This means that a huge amount of interferences must be overcome by new agile technologies without wasting power resources in the IoT nodes. In this paper, these challenges are addressed by a neural-network-based machine learning system that is based on frequency-domain features extracted from the communication channel. This machine learning system predicts the needed transmit power to overcome the interferences by a predefined margin. Extensive system simulations have been performed on a real-world dataset that shows power savings in the range of 35 to 83 percent and a packet receive-ratio of at least 95 percent. Similarly, it has been found that the system converts after approximately 50 supervised samples, which supports efficient tracking of parameter variations in the communication channel.
Keywords: Smart buildings; IoT networks; interferences; neural-networks; transmit-power regulation; decentralized control schemes.
A Key Management Scheme Realizing Location Privacy Protection for Heterogeneous Wireless Sensor Networks
by Erdong Yuan, Liejun Wang
Abstract: Key management is the core of wireless sensor network security management technology. At present, the protection of the source location information of nodes has also received great attention. In this paper, we combine identity-based encryption (IBE) algorithm with Elliptic curve cryptography (ECC) based digital signature authentication to achieve more secure authentication. Then we use the double encryption method to realize the location privacy protection. Finally, we adopt a new routing update scheme to prevent attackers from initiating sinkhole attacks. In addition, we add timestamps to messages transmitted between nodes to defend against resend attacks. The scheme we proposed occupies a small amount of key storage space, consumes relatively more energy to protect the location information of nodes in the heterogeneous sensor network (HSN), and prevents attackers from initiating sinkhole attacks and resend attacks, thereby enhancing network security.
Keywords: Key management; Location privacy protection; Sinkhole attacks; IBE algorithm; HSN.
Cost-effective Routing as a Service (RaaS) in Sensor-Cloud
by BIPLAB SEN, Anupam Sarkar, Sunimal Khatua, Rajib Das
Abstract: Sensor-cloud is a collaborative platform which allows multiple Wireless Sensor Networks (WSN) to pull their resources together for better utilisation and efficiency. In this work, we consider a set of applications, each characterised by the set of targets it intends to cover and our aim is to provide Routing as a Service to all these applications in the Sensor-cloud. Each application is served by a virtual sensor network that may span multiple WSNs. We should be able to run data gathering for each application parallelly with the minimum use of Sensor-cloud resources. This is achieved by creating a collection of data gathering trees, each rooted at a different base station. We have proposed an algorithm where a minimal set of sensors are selected to cover the required targets and a spanning forest connecting them is obtained so that total energy cost of all the trees in the forest is minimized. Then we show that by applying a sequence of alterations, the cost can be further reduced. Experimental results demonstrate the advantages of serving the applications by a Sensor-cloud over standalone WSNs in terms of the usage of resources (active sensor nodes as well as energy cost per round).
Keywords: Sensor-cloud; Wireless Sensor Network; Virtualization; Data gathering; Routing-as-a-Service.
A MQTT-API-Compatible IoT Security-Enhanced Platform
by Hung-Yu Chien, Yi-Jui Chen, Guo-Hao Qiu, Jian Fu Liao, Ruo-Wei Hung, Pei-Chih Lin, Xi-An Kou, Mao-Lun Chiang, Chunhua Su
Abstract: Owing to its lightweight and easiness, the Message Queue Telemetry Transport (MQTT) has become one of the most popular communication protocols in the Internet-of-Things (IoT) and in the Machine-To-Machine (M2M) communications. However, the security supports in the MQTT are very weak, and the gap between the supported functions and the desirable security functions raises a big security threat to these deployments. In this paper, we systematically examine the security requirements of a MQTT-based IoT system, identify the gap between the requirements and the supported functions, and design a security-enhanced MQTT framework that facilitates device authentication, key agreement, and policy authorization. Additionally, it is desirable that any MQTT-security enhancements should be compatible with existent MQTT Application Programming Interfaces (API). We propose a two-phase authentication approach that can smoothly integrate secure key agreement schemes with the current MQTT-API. To evaluate its effectiveness and efficiency, we integrate the classic Challenge-and-Response (CR) technology and the MQTT CONNECT API. Compared to its counterparts, the results show the merits of improved communication performance, MQTT-API compliance, and security robustness.
Keywords: Transport Layer Issues; Security and Privacy; MQTT; Internet of Things; authentication.
Continuous-variable quantum network coding protocol based on butterfly network model
by Zhiguo Qu, Zhexi Zhang, Mingming Wang, Shengyao Wu, Xiaojun Wang
Abstract: With the development of quantum network, the need to improve the efficiency and security of network transmission is becoming more and more obvious. It is difficult in producing and detecting single photon, while quantum continuous-variables have practical significance of improving communication, as a result this paper proposes a new continuous-variable quantum network coding protocol (CVQNC) based on the butterfly network model and the properties of quantum continuous-variables. In this paper, the hybrid channel of quantum channel and classical channel is adopted to realize the cross transmission of quantum information and classical information through the corresponding operation in the intermediate node. Considering the high cost and difficulty of the implementation of quantum channel, we take advantage of classical channel, which is in accordance with the existing network resources. The new protocol not only is conducive to the realization of quantum network, but also can reduce the communication cost of quantum network effectively. It can be seen from the throughput and fidelity analysis that this protocol has a higher throughput than discrete-variable quantum network encoding scheme and classical information network encoding scheme. The ceiling of fidelity in this protocol is 4/9. According to the analysis of simple intercept attack and spectroscope attack, it is secure for the protocol to transmit quantum information and classical information by resisting on the eavesdropping attack of the third-party effectively.
Keywords: Continuous-Variable; Network Coding; Quantum Network Coding; Butterfly Network Model; Quantum Secure Direct Communication.
svBLOCK: Mitigating Black Hole Attack in Low-power and Lossy Networks
by Sonxay Luangoudom, Duc Tran, Tuyen Nguyen, Hai Anh Tran, Giang Nguyen, Quoc Trung Ha
Abstract: Routing Protocol for Low power and Lossy Networks (RPL) is a novel protocol that is specifically designed for the 6LoWPAN networks. Although RPL is able to avoid loop and detect inconsistencies, this protocol is still vulnerable to a variety of internal attacks. The simplest, but most effective is the black hole, whose aim is to disrupt the optimal routing structure, and hence, downgrading the network performance. In this paper, we present a novel svBLOCK scheme to handle the black hole attack. svBLOCK is based on the SVELTE Intrusion Detection System to reconstruct the DODAG and validate the node availability. It is also equipped with mechanisms to provide authenticity over its control messages and isolate black holes from the LLN. svBLOCK is implemented in Contiki OS and is evaluated under various attack scenarios. It demonstrates to achieve 98.5% True Positive Rate at a False Negative Rate of 3.7%, while improving the Packet Delivery Rate by up to 47% with respect to the original SVELTE.
Keywords: Internet of Things; RPL; network security; black hole attack.
Emperor Penguin Optimized Self-Healing Strategy For WSN Based Smart Grids
by Korra Cheena
Abstract: The cooperative and inexpensive speciality of sensor networks conveys significant benefits over conventional communication strategies utilized in recent electric power schemes. Now days, smart grid technologies make use of wireless sensor network in electric power generation, transmission and distribution systems. Use of sensor network in bulk power transmission become very fame due to special behaviour of networks like simple installation, wide coverage, sensitive line monitoring and effective fault tolerance. This paper proposes Emperor Penguin Optimized Self-Healing (EPOSH) strategy for sensor network based smart grid system. Self-healing is a process of automatically detecting and correcting faulted sensor nodes to enable uninterrupted power supply in smart grid systems. In proposed work, data generated from various nodes are forward to cluster leader and routed to base station from leader node. Routing performed based on EPOSH in proposed work which greatly reduces design complexity of Self-Healing process. Because, EPOSH works in an iterative manner to detect, eliminate faulty nodes and to find optimal alterative solution for routing with faulty nodes. Proposed EPOSH for SG networks implemented in Matlab working environment and resultant performances are compared with existing works such as AEC, GHS, GA-TBR and IGRC.
Keywords: Smart Grid; Wireless sensor network; self-healing and emperor penguin optimization.
Broadcast-Based Routing Protocol for Smart Lighting Systems
by Andrea Stajkic, Chiara Buratti, Roberto Verdone
Abstract: In this paper we consider a smart lighting system, where sensors andrnactuators are located over lamp posts in a street, generating data to be sent to a final sink, that is a 3G gateway. According to nodes location, a linear wireless network is created, devices being deployed over a line and sending data to a final destination at the end of the line. We propose a novel efficient routing protocol for this type of networks, based on broadcast transmissions. In particular, during an initial discovery phase each node identifies its neighbours and selects its best neighbour as the one being closest to the sink, that is the farthest in the line. Data is then transmitted in broadcast, by prioritising the best neighbour selected as forwarder, in order to reduce overhead. The protocol allows data packets to reach the sink through a small number of hops and, as a consequence, to improve throughput and packet delivery probability with respect to existing solutions. The proposed protocol has been implemented on theEuWIn platform, developed in the framework of the EC-funded Network of Excellence, NEWCOM#. The protocol has been tested and compared to standard solutions, based on IEEE 802.15.4 and Zigbee. Experimental results, in terms of packet loss rate, throughput and number of hops to reach the sink, show the improvement achieved with the proposed solution with respect to the existing ones.
Keywords: Smart Lighting Systems; Linear Wireless Networks; Broadcast-rnBased Protocol; Experimentation.
Modelling a Smart Non-invasive Adrenaline Sensor
by Noha MM., Nahla F. Omran, Abdelmageid A. Ali, Fatma A. Omara
Abstract: Adrenaline hormone may effect on cholesterol and glucose levels in the human body which may cause different diseases such as stroke. On the other hand, numerous biomedical research relies on bio-impedance technique because it possesses a lot of features such as the ability to analyze the blood components to identify different diseases. Therefore, this study aims to measure the adrenaline level non-invasive based on bio-impedance technique using a new proposed sensor to measure the adrenaline, cholesterol and glucose levels. The proposed sensor has been interfaced with a 3D model of two electrodes which used to send the current (I) to the earlobe and measure the produced voltage (V). It is simulated by COMSOL MULTIPHYSICS 5.0, and the impedance was measured at each frequency. Then the adrenaline, cholesterol and glucose values are computed using the equations. Finally, the obtained results from the simulator and the equations show that the proposed sensor would be a better choice for designing a real non-invasive medical Sensor.
Keywords: Sensor; Bio-impedance; Internet of Things (IoT); Non-invasive.
Hidden Markov Model Based Rotate Vector Reducer Fault Detection Using Acoustic Emissions
by Haibo An, Wei Liang, Yinlong Zhang, Jindong Tan
Abstract: The reliable fault detection of rotate vector (RV) reducer is of paramount importance for the long-term maintenance of high-precision industrial robots. This paper proposes a Hidden Markov Model (HMM) based RV reducer fault detection using Acoustic Emission (AE) measurements. Compared with the conventional faults from the common rotating machinery (such as bearings and gears), the fault from the RV reducer is more complicated and undetectable due to its inherent inline and two-stage meshing structure. To this end, this work modifies the HMM model by taking into account not only the current observations and previous states, but also the subsequent series of observations within the posteriori probability framework. Through this way, the random and unknown disturbance, which is common in the industrial scenarios, could be suppressed. Besides, the HMM is also applied to separate the AE signal bulks within one cycle that has 39 subcycles, which is a critical step for AE signal pre-processings. The proposed method has been evaluated on our collected AE signal dataset from the RV reducer in the industrial robotic platform. The experimental results and analysis validate the effectiveness and accuracy of the RV reducer fault detection model.
Keywords: Rotate Vector (RV) Reducer; Fault Detection; Hidden Markov Model (HMM); Acoustic Emission (AE).
Energy-Efficiency and Coverage Quality Management for Reliable Diagnostics in Wireless Sensor Networks
by Ahmad Farhat, Christophe Guyeux, Mohammed Haddad, Mourad Hakem
Abstract: The processing of data and signals provided by sensors aims at extracting rnrelevant features which can be used to assess and diagnose the health state rnof the monitored targets. Nevertheless, Wireless Sensor Networks (WSNs) present rna number of shortcomings that have an impact on the quality of the gathered rndata at the sink level, leading to imprecise diagnostics rnof the observed targets. To improve data accuracy, two main critical and related issues, namely the energy consumption and coverage quality, need to be considered. The goal is to maximize the network lifetime while guaranteeing the complete coverage of all the targets. Unfortunately, these performance objectives are difficult in their own and solving them together makes the problem even harder. For instance, the energy consumptionrnwill increase if we want to enhance the coverage quality, even if no actual failure happens duringrnthe monitoring activity of the deployed network. To tackle this problem, many algorithms have been proposed in the literature but none of them has studied the impact of energy saving and target coverage on the quality of the data provided by a WSN. In this paper, we present a distributed algorithm based on a theory of domination in graphs, and we study its impact on diagnostics by using six machine learning algorithms. First, we give the correctness proofs and next we assess its behavior through simulations. Obtained results show that the proposed algorithm, despite its lower complexity, exhibits better performances than its direct competitor, the Probabilistic Coverage Protocol PCP, and the optimistic solution (which is called BaseLine).
Keywords: sensor networks; distributed algorithms; lifetime optimization; coverage; diagnostics; domination in graphs.
Amputee walking mode recognition based on mel frequency cepstral coefficients using surface electromyography sensor
by Tahir Hussain, Nadeem Iqbal, Hafiz Farhan Maqbool, Mukhtaj Khan, Mehak Tahir
Abstract: Walking mode recognition through surface electromyography (sEMG) sensors is an active field of smart prostheses technologies. The sEMG signal is non-Gaussian and can be discriminatively represented by a nonlinear function. This work presents the Mel frequency cepstral coefficients of the nonlinear sEMG signals as an effective feature for the recognition of different walking modes. Mel frequency cepstral coefficients represent the individual components of sEMG signals and parameterize them to signify the discriminative features of the signal. Principal component analysis and mutual information were used for feature reduction and sEMG optimum channel selection respectively. The proposed recognition system identifies five walking modes such as normal walking, slow walking, fast walking, ramp ascending and ramp descending. The proposed method was evaluated using eleven channels of lower limb sEMG signals recorded from six subjects including four able-bodied, one unilateral transtibial and one unilateral transfemoral amputee. Several classifiers were trained with a pool of collected data. The experimental result exhibits that the proposed system achieved the highest accuracy of 97.50% using support vector machine. The promising results of this work could promote the future developments of neural-controlled lower limb prosthetics.
Keywords: surface electromyography sensor; mel frequency cepstral coefficient; neurological signal; optimum channel selection; prosthesis; support vector machine; walking mode recognition; feature extraction; feature reduction; performance analysis.
Energy-Efficient MAC Protocols for Wireless Sensor Networks: A Survey
by Farhana Afroz, Robin Braun
Abstract: Wireless Sensor Network (WSN) is a network of a large number of battery-powered tiny sensor nodes wirelessly connected together to facilitate a wide range of monitoring applications. As WSN nodes are energy-constrained microelectronic devices, the primary design objective of WSNs is to minimize energy consumption to prolong the network lifetime. To achieve this goal, a range of cross-layer techniques, particularly focusing on MAC (Medium Access Control) sublayer, is proposed for various WSN applications. However, until now, no WSN MAC protocol is standardized by IEEE. The selection of MAC protocol is intrinsically application-specific, and the search for improving energy efficiency while leaving the least impact on QoS (Quality of Service) parameters, such as end-to-end packet delivery latency and throughput, is an ongoing research challenge. This paper aims to survey low-power WSN MAC protocols, proposed from 2000 to the present, emphasizing some general aspects including the issues addressed, the solutions proposed, design principles, strengths, drawbacks and target applications. With this aim, we mainly classify the MAC protocols into three categories: contention-based protocols, TDMA (Time Division Multiple Access)-based protocols and hybrid protocols, where the first category is further subdivided into subclasses. The development trends and potential research challenges are also discussed.
Keywords: WSN; MAC Protocols; Energy Efficiency; Network Lifetime; QoS; Duty Cycling; CSMA; TDMA; Hybrid.
Virtual Force Field Coverage Algorithms for Wireless Sensor Networks in Water Environments
by Wang Jun, G.U.O. Hao-yang
Abstract: Methods for underwater wireless sensor networks currently lack the ability to monitor different zones in a water area. The coverage of the main area does not produce good results when fewer nodes are deployed. An underwater wireless sensor network algorithm based on the virtual force field algorithm is designed, termed the focus virtual force field method (FVFF). The concept of the key focus area is proposed. By adjusting the force and parameters of the virtual force field algorithm nodes, the monitored waters are partitioned The virtual force field algorithm has better coverage for water with fewer nodes and guarantees the coverage rate of the main area. Moreover, the cost of the system is reduced because of the use of nodes with restricted mobility. The simulation results show that the FVFF algorithm has a higher coverage rate than the virtual force field algorithm and the random deployment node method when the number of nodes is small. FVFF has better coverage in the main area of water.
Keywords: Wireless sensor network for water environments;Coverage control;Virtual force field;obility-constrained nodes.
A (t, n) threshold quantum visual secret sharing
by Wenjie Liu, Yinsong Xu, Junxiu Chen, Ching-Nung Yang
Abstract: Secure data sharing is a deserving topic in wireless sensor networks. In order to deliver the information securely, we propose a (t, n) threshold quantum visual secret sharing (QVSS) scheme based on Naor et al.'s visual secret sharing (VSS) scheme, which consists of two phases: sharing process and recovering process. In the first process, the color information of each pixel from the original secret image is encoded into an n
Keywords: threshold; n×m-qubit superposition state; single-pixel parallel processing; visual cryptography.
A Global-to-Local Searching-Based Binary Particle Swarm Optimization Algorithm and its Applications in WSN Coverage Optimization
by Kanghsun Li, Ying Feng
Abstract: The coverage optimization problem of wireless sensor networks, also known as the minimum connectivity coverage node set problem, has always been a popular research topic. Heuristic search algorithms have been applied to the coverage optimization problem of wireless sensor networks in recent years because of their strong search ability and fast convergence speed. This paper proposes an optimization algorithm for a wireless sensor network based on improved binary particle swarm optimization. The position updating formula based on the sigmoid transformation function is adjusted, and a global-to-local search strategy is used in the global-to-local searching-based binary particle swarm optimization algorithm (GSBPSO). Furthermore, to apply GSBPSO to the optimization of wireless sensor networks, a small probability mutation replacement strategy is proposed to replace individuals who do not meet the coverage requirements in the search process. In addition, the fitness function is improved so that the network density can be adjusted by modifying the parameters in the improved fitness function. Experiments show that the proposed algorithm in this paper is effective.
Keywords: wireless sensor networks; BPSO; coverage optimization; minimum connected coverage set.