International Journal of Sensor Networks (31 papers in press)
Recent Advances in Wireless Sensor Networks with Environmental Energy Harvesting
by Lei Shu, Wanjiun Liao, Jaime Lloret, Lei Wang
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.
Limit Equilibrum based Landslide Prediction System using WSN
by Adel Thaljaoui, Fayez Abdulrahman ALFAYEZ, Salim El Khediri
Abstract: The increased impact of landslides, especially in emerging countries, is largely related to population growth, increasing infrastructure and human activities in landslide-prone areas. Such a problem incited us to investigate new solutions that detect the early signals preceding a landslide. The system we propose is designed around special sensors that capture each real-time change in the soil of the studied field. These changes are sent toward processing modules that compute the real-time Bishop based factor of security and compares it with limit values. Carried experimentations showed the significant response of the proposed system before the slide surface is formed which gave enough time to take appropriate procedures in order to prevent imminent landslide.
Keywords: Landslide; prediction; factor of safety; WSN.
Research on Natural Disaster Emergency Monitoring System
by Yang Jianliang, Hou Hanping, Geng Shaoqing, Qiao Shaobo, Wang Yue
Abstract: Monitoring is the main emergency information and intelligence department. The natural disaster emergency rescue decision is made on the basis of disaster monitoring information. Obtaining timely and accurate disaster information is the fundamental guarantee for emergency and rapid rescue. Based on the research status of natural disaster emergency monitoring system, this paper proposes the establishment of sky-ground integrated natural disaster emergency monitoring system based on the research method of system management theory, and analyzes quantitatively the system performance. Finally, it points out the operation mode and guarantee of the system. The mechanism provides reference for the construction of a scientific and perfect natural disaster emergency monitoring system, which really shortens the time of black box and grey box, solves the vacuum of rescue and realizes rapid rescue.
Keywords: natural disasters; emergency monitoring; information and intelligence; sky-ground integrated monitoring system.
Mobility Aware and Traffic Adaptive Hybrid MAC Protocol for Collaborative Body Sensor Networks
by Nadine Boudargham, Jacques Bou Abdo, Jacques Demerjian, Christophe Guyeux, Abdallah Makhoul
Abstract: Collaborative Body Sensor Network (CBSN) is formed of several Body Sensor Networks (BSNs) moving in a given area and able to exchange data between each other. One of the challenges in CBSN is to design a Medium Access Protocol that efficiently supports nodes mobility, and at the same time, that guarantees immediate delivery of urgent data, and maintains high energy efficiency during regular observation. In this paper, a hybrid Traffic and Mobility Aware MAC (TMA-MAC) is proposed to satisfy CBSN's traffic requirements through adopting a hybrid DS-CDMA/DTDMA technique, and to support CBSN's nodes mobility through ensuring efficient transmission of intra-cluster mobile nodes data and proposing a mechanism to handle inter-cluster nodes joining requests. TMA-MAC was compared to other existing protocols under both traffic and mobility variations. Simulations were conducted using OPNET to evaluate TMA-MAC with respect to packet delay, packet drop percentage, and energy consumption.
Keywords: MWSN; CBSN; MAC; DTDMA; DS-CDMA; Mobility; Delay; Packet Drop; Energy Consumption.
Using V2X Communications and Data Fusion to Achieve Lane-Level Positioning for Road Vehicles
by Tsu-Kuang Lee, Juyi Lin, Jen-Jee Chen, Yu-Chee Tseng
Abstract: Precise positioning is a key issue for road vehicles in navigation, safety, and autonomous driving applications. While GPS is widely accepted, it is still a challenge to achieve lane-level positioning. In this work, we consider the fusion of multi-sensory data using Particle Filter (PF), which is ?exible in integrating different information in complex outdoor environments. We focus on three types of popular sensors: Controller Area Network (CAN bus), GPS, and roadside camera. We propose a PF model that can adopt these types of sensory inputs for vehicle positioning. We show that in scenarios where vision sensory inputs are available, lane-level precision can be achieved. When there is no vision coverage, seamless localization with reasonable precision can still be supported by GPS. Field trial results are presented to validate our model.
Keywords: Data Fusion; Particle Filter; Positioning; Vehicular Network.
Managing Sensor Data Streams in a Smart Home Application
by Johan Jansson, Ismo Hakala
Abstract: A challenge in developing an ambient activity recognition system for use in elder care is finding a balance between the sophistication of the system and a cost structure that fits within the budgets of public and private sector healthcare organisations. Much activity recognition research in the context of elder care is based on dense networks of sensors and advanced methods, such as supervised machine learning algorithms. This paper presents the data processing aspects of an activity recognition system
based on a simpler, knowledge-based unsupervised approach, designed for a sparse network of sensors. By structuring sensor data management as a streaming system, we provide a simple programming model for the application logic, which facilitates
building a fault-tolerant system with the potential for distributed data management within the sensor network. The system, evaluated by a public sector healthcare organisation, constitutes an example of a system that is useful and has a sustainable cost structure.
Keywords: activity recognition; healthcare; home care; passive infrared sensor; PIR; sensor data; sensor data management; sensor data processing; sensor data streams; smart home; wireless sensor network; WSN.
Cooperative Spectrum Sensing with Energy Harvesting for Nakagami fading channels
by Raed Alhamad, Hatem Boujemaa
Abstract: The paper derives the Detection Probability (DP) of Cooperative Spectrum Sensing (CSS) algorithms with energy harvesting. There are three phases with the same duration. The first phase is dedicated to energy harvesting by Primary User (PU) and relays. They harvest energy from Radio Frequency (RF) signal received from another node H. Node H can be a Base Station. In the second phase, PU transmits its signal that will be received by relays. In the last phase, a selected relay amplifies the PU signal to a Fusion Center (FC) where spectrum sensing is performed using the energy detector. Our analysis is valid for Opportunistic Amplify and Forward (OAF), Partial(PRS) and Reactive Relay Selection (RRS). A Nakagami fading channel is assumed between all nodes. Another contribution of the paper is to show that the DP can be lower bounded using the Cumulative Distribution Function (CDF) of Signal to Noise Ratio (SNR).
Keywords: Radio Frequency (RF) Energy harvesting; Spectrum Sensing; Nakagami channels.
Early detection of foot complications using a thermal profiler of plantar surface
by M.M. Manohara Pai, Kushagra Jain, K.N. Manjunath, Sucheta V. Kolekar, Radhika M. Pai
Abstract: Foot complications in diabetic patients can become fatal. Hence early detection of the onset of foot complications becomes the need of the hour. Various techniques are being used by diabetologists to know the presence of foot complications. One of the technique used at present in the measurement of temperature variations in the plantar surface of the foot using thermogram images. This paper describes a novel system called Thermal Prolfier System which proles the temperature variations in the plantar surface. The Thermal Proler System consists of a device with 23 sensors embedded at strategic locations which senses the temperature values of the plantar surface. It also consists of a mobile application that gets the temperature data from the device, computes the variations in the temperature values and reports abnormalities to the diabetologist. Further, an experimental study is conducted to validate the values recorded by the device. This study includes temperature data of symptomatic and asymptomatic subjects whose values read from the plantar surface using a Thermal Proler device is compared with the temperature data obtained from thermogram images of the same plantar surface captured using FLIR thermal camera at almost the same time. The statistical analysis performed using paired t-test indicate that the difference between the thermal profiler values and the thermogram images are statistically not signficant (p=0.054).
Keywords: Plantar surface; Thermal profiler; Tibial arteries; Angiosomes; Thermogram images.
Cooperative NOMA: device-to-device mode and outage performance analysis
by Thuan Do, Anh-Tu Le, Thi-Anh Hoang
Abstract: In this paper, a new approach as combination of relaying model and device-to-device (D2D) scheme to perform non-orthogonal multiple access (NOMA) in the fifth generation (5G). In such NOMA system, we deploy power domain to transfer multiple users signals over same resource at the same time. As important result, two NOMA users communicate with each other as D2D pair and they exhibit different system performance due to different links and dissimilar allocated power levels. More specifically, expression of a closed-form is presented in term of the outage probability. In numerical result, exactness of the theoretical expressions can be confirmed by exploiting Monte Carlo simulations. Compared to many scenarios in such multiple access technique, the proposed NOMA scheme can offer improved spectral efficiency and user fairness by matching the obtained analytical and simulation results.
Keywords: D2D; non-orthogonal multiple access (NOMA); outage probability.
Radio-Based Vehicle Dynamic Tracking in GNSS Degraded Environments
by Jianqi Liu, Xiuwen Yin, Bi Zeng, Hui Zhang, Wei He
Abstract: The vehicular position information plays an important role in the vehicle communication. In open environments without signal blockage, Global Navigation Satellite System (GNSS) has achieved on-road level accuracy and good reliability, However, the vehicle dynamic tracking is difficult in GNSS degraded environments. Usually, vehicle dynamic tracking consists of three portions: static positioning system, maneuvering model and fusion algorithm. A radio-based positioning system aided by Roadside Units (RSUs) is employed as static positioning system, while the adaptive Kalman filter algorithm is used as fusion algorithm. In this paper, a new maneuvering model is studied. Firstly, the problem of current model is analyzed. Secondly, a current-ellipse maneuvering model is proposed to adapt the strong and weak maneuvering simultaneously. The experiments show that it can improve the tracking accuracy. Finally, a vehicle tracking case is discussed, its results show that root mean square error (RMSE) is smaller than 2 meters, and the positioning accuracy can meet the position-based vehicular communication.
Keywords: Vehicle dynamic tracking;Maneuvering model;RSUs-aided radio-based positioning system;Current-ellipse model.
Application of gravity passive aided strapdown inertial navigation in underwater vehicles
by Qi Wang, Changsong Yang, Shaoen Wu, Yan Wang
Abstract: The area of the ocean accounts for more than 70% of the surface area of our earth, the development and protection of the ocean has become a long-term strategic task of many countries. Underwater vehicle plays an important role in ocean development. Underwater navigation technology is the guarantee to ensure the underwater vehicles complete all tasks. A gravity passive aided strapdown inertial navigation system is proposed in this paper in order to improve the precision of position of autonomous underwater vehicles. Improved unscented Kalman filter is applied in the novel integrated system which is based on gravity gradient characteristics. The main characteristics of strapdown inertial navigation system are presented, gravity-aided navigation system are introduced in this paper, and improved UKF method is applied to the information fusion of integrated navigation system. Simulation experiments were carried out and simulation experiments show that the novel integrated navigation system proposed in the paper can get better performance of position precision comparing to the traditional Kalman filtering methods. The simulation experiment results suggest that the improved UKF method applied in the gravity passive aided navigation system is capable of greatly improving the long-time navigation position precision, attitude precision and velocity precision comparing with the traditional information fusion method.
Keywords: gravity passive aided; strapdown inertial navigation system; gravity gradient; improved unscented Kalman filter.
A High Precision Recognition Method for Abnormal Data in An Optical Network based on Data Mining
by Jinkun Sun
Abstract: In order to overcome the problem that abnormal data in optical networks affect the quality of data transmission and result in the loss of data information. In this paper, a new high-precision method for abnormal data recognition in an optical network based on data mining is proposed. The acquisition system is used to collect data in the optical network, and photoelectric conversion is carried out. The collected data are filtered and processed by a filter. A segmentation method is used to extract the sequence features of the data. A distance method is used to complete feature matching to realize the recognition of abnormal data in the optical network. The experimental results show that, compared with the three traditional methods for abnormal data recognition in optical networks, the proposed method has higher recognition accuracy and speed, which can detect abnormal data in optical networks quickly and accurately, and ensure the quality of data transmission.
Keywords: Data mining; Optical network; Abnormal data; High precision; Recognition method.
Wireless Energy Harvesting for Nakagami fading channels
by Nadhir Ben Halima, Hatem Boujemaa
Abstract: This paper deals with wireless energy harvesting using Radio Frequency (RF) signals for Nakagami channels. We derive the Packet Error Probability (PEP) of different Relay Selection (RS) techniques where all nodes harvest energy from RF signal received from node H. Node H can be a base station. We choose the harvesting duration to maximize the throughput. Our analysis is valid for Nakagami fading channels with arbitrary fading figure of different links.
Keywords: Radio Frequency (RF) Energy harvesting; cooperative communications; optimal harvesting duration; throughput analysis.
Multiobjective Optimization Model and Algorithm for Data Center Scheduling in Elastic Optical Networks
by Xia Li, Zhanqi Xu, Yuping Wang, Chunxia Ji
Abstract: How to properly assign data centers in EONs is a particularly important issue, which determines not only the quality of service (QoS), but also the cost of data centers and their operational expenditures. In this paper, we first propose a multiobjective optimization model for data center scheduling (DDEA/RSS) on EONs and design an evolutionary algorithm using the framework of NSGA-II to solve the model when the total number of data centers deployed in EONs and the call request blocking probability are considered. Then, we design three heuristic routing algorithms to construct routes between a pair of nodes based on deployment of data centers. The experimental results on both small-scale and large-scale network topologies indicate that DDEA/RSS produces the lower call request blocking probability under the same number of data centers in EONs and the smaller number of data centers under the same call request blocking probability.
Keywords: Elastic Optical Network; Multiobjective Evolutionary Technique; DatarnCenter Placement; Data Center Assignment.
Real-time detection of burst faults of key nodes in optical transmission networks based on a firework algorithm
by Peng Wang, Ningchao Zhang
Abstract: In order to overcome the problems of poor real-time performance and low fitting degree of real-time detection methods for burst faults of key nodes in existing optical transmission networks, a new real-time detection method for burst faults of key nodes in optical transmission networks based on fireworks algorithm is proposed. Firstly, this method builds a real-time detection framework for burst faults of key nodes in optical transmission network. Based on this framework, fireworks algorithm is used to identify key nodes in optical transmission network. The recognition results are used as the basis of information of key nodes in optical transmission network. Based on similarity analysis, the trust degree of key nodes is evaluated, and the decision function of burst faults is set up. According to the trust value, the decision function of burst faults is set to determine whether the key nodes have burst faults, and the real-time detection of burst faults of the key nodes is completed. The experimental results show that, compared with the traditional methods, the proposed real-time detection method for burst faults of key nodes in optical transmission network based on fireworks algorithm greatly improves the real-time performance and fitness, fully demonstrating that the proposed real-time detection method for burst faults of key nodes in optical transmission network based on fireworks algorithm has better detection effect.
Keywords: Fireworks algorithm; Optical transmission; Key nodes; Burst faults; Detection;.
Optimization of delay tolerance in wireless sensor networks based on unscented Kalman filter estimation
by Zhongli Shen, Guozhu Yao, Qiyue Xie, Fei Jiang
Abstract: Delay tolerance in wireless sensor network can be applied to complex and harsh communication environment. In order to improve the communication performance of delay tolerance in wireless sensor network, the optimization of delay tolerance in wireless sensor network based on Unscented Kalman filter estimation is studied. Firstly, the model of delay tolerance in wireless sensor network is established according to the theory of dynamics and position constraints, and then an unscented Kalman filter estimation algorithm is used. Through analyzing the basic state and measurement equation of delay tolerance in wireless sensor network model, the measurement equation of round-trip delay model is obtained. The pre handover time estimated by unscented Kalman filter is set, to effectively reduce the pre handover time and energy consumption, and optimize the delay wireless sensor network. The experimental results show that the delay tolerance of wireless sensor network optimized by the proposed method is within 30ms under different observation noises, and the packet loss rate and energy consumption are low.
Keywords: Unscented Kalman filter; Estimation; Wireless sensor; Network; Delay tolerance; Optimization research.
Energy-Efficient Routing under Delay Constraint in Duty-Cycle Wireless Sensor Networks
by Mengmeng Xu, Hai Zhu, Hengzhou Xu, Xiaofei Yang
Abstract: The duty-cycle scheme, in which a sensor node could switch between active and dormant states, is widely used in wireless sensor networks (WSNs) to reduce energy consumption and to improve network lifetime. In this paper, we investigate the problem of energy-efficient routing design from a sensor node to a sink node under a given delay constraint. The network topologies in duty-cycle WSNs are changed from one time-slot to another due to each sensor node's active/dormant schedule. A series of network topologies over a period of time are modeled as a virtual time-expanded graph. The time-expanded graph is constituted of the spatial links in each time-slot and the temporal links from one time-slot to another. Then, the problem of routing design on the time-expanded graph is defined, whose aim is to find a space-time path from a sensor node to the sink node with the minimum energy consumption under a delay constraint. Next, an Energy-efficient Routing algorithm in Time-expanded Graph (ERTG) is proposed to find the optimal space-time path. Simulation results validate the effectiveness of the proposed algorithm in energy savings.
Keywords: Routing; Energy-Efficiency; Delay Constraint; Wireless Sensor Network; Duty-Cycle; Time-Expanded Graph.
Cloud Service Security Evaluation of Smart Grid Using Deep Belief Network
by Liping Chen
Abstract: Cloud service can be widely used in the smart grid which implements reliable, efficient and cost-effective power management. Cloud service security will face significant challenges due to malicious attacks. Therefore cloud service security evaluation is crucial to ensuring the smart grid work effectively and reliably. In this paper, we analyze key security problems in the scalable platform architecture of cloud service of smart grid. We also establish evaluating process according to the lack of evaluation mechanism. It presents evaluating index system of cloud security of smart grid which has seventy-four indicators in the third-level. They evaluate security risks in 5 respects which are policy and organizational risks, general technical risks, SaaS risks, PaaS risks and IaaS risks.rnThe evaluation model based on DBN is proposed which is composed of multiple RBMs and a BP neural network. The RBMs are trained by greedy training algorithm, and then BP algorithm is used to fine-tuning. After case verification, it is found that the various errors (including MAE, MRE, MSE, Maximum error and Minimum error) of DBN model are the smallest compared BP and AE model. It avoids the problem that multilayer neural network is trapped in the local optimum. rn
Keywords: Smart grid;Cloud service security;Scalable platform architecture;Evaluating process;Evaluating index system;Evaluation model;Deep Belief Network (DBN); Restricted Boltzmann Machines (RBM);BP neural network;Fine tuning.
Optimum Data Collection and Fusion Schemes in WBSN
by Mohammad Mehrani
Abstract: in this paper first we define our strategies aiming at minimizing number of communicated data while keeping data integrity in Wireless Body Sensor Networks (WBSNs). In this way, we introduce modified Fisher test, develop Spline interpolation as the behavior function and define controlling parameters. To achieve at significant results we propose three efficient algorithms to perform adaptive sampling over WBSN. Furthermore, at the second step, we represent our method to calculate the priority of vital sign data packets to transmit emergency packets in terms of their priorities. For this purpose we employ Spline interpolation function and define six new controlling parameters for it. At the third step, for correct inference of patients situations and calculating accurate results for monitored patient we introduce our method which develops Adaptive Neuro Fuzzy Inference System (ANFIS) with rncross-validation. This intelligent combination allows the system to track the status of monitored patients, correctly. To evaluate the performance of the proposed approaches we run a number of simulations in MATLAB R2018b. Simulation results demonstrate the optimum performance of our schemes for number of communicated data, network lifetime, priority based data communication and also correct inference of patients situations.
Keywords: WBSN; Data Collection; Data Fusion; Energy Optimality; Sampling Rate; Packet Priority; ANFIS; Spline;.