Journal articles: 'Controlled sensor networks'

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PICOVICI, D., M. BERGLUND, and J. NELSON. "Voice Controlled Wireless Sensor Networks." Advances in Electrical and Computer Engineering 7, no. 1 (2007): 3–8. http://dx.doi.org/10.4316/aece.2007.01001.

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Botero-Valencia, Juan, Luis Castano-Londono, and David Marquez-Viloria. "Indoor Temperature and Relative Humidity Dataset of Controlled and Uncontrolled Environments." Data 7, no. 6 (June 16, 2022): 81. http://dx.doi.org/10.3390/data7060081.

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The large volume of data generated with the increasing development of Internet of Things applications has encouraged the development of a large number of works related to data management, wireless communication technologies, the deployment of sensor networks with limited resources, and energy consumption. Different types of new or well-known algorithms have been used for the processing and analysis of data acquired through sensor networks, algorithms for compression, filtering, calibration, analysis, or variables being common. In some cases, databases available on the network, public government databases, data generated from sensor networks deployed by the authors themselves, or values generated by simulation are used. In the case that the work approach is more related to the algorithm than to the characteristics of the sensor networks, these data source options may have some limitations such as the availability of databases, the time required for data acquisition, the need for the deployment of a real sensors network, and the reliability or characteristics of acquired data. The dataset in this article contains 4,164,267 values of timestamp, indoor temperature, and relative humidity acquired in the months of October and November 2019, with twelve temperature and humidity sensors Xiaomi Mijia at the laboratory of Control Systems and Robotics, and the De La Salle Museum of Natural Sciences, both of the Instituto Tecnológico Metropolitano, Medellín—Colombia. The devices were calibrated in a Metrology Laboratory accredited by the National Accreditation Body of Colombia (Organismo Nacional de Acreditación de Colombia—ONAC). The dataset is available in Mendeley Data repository.

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Yen, Y. S., S. Hong, R. S. Chang, and H. C. Chao. "Controlled deployments for wireless sensor networks." IET Communications 3, no. 5 (2009): 820. http://dx.doi.org/10.1049/iet-com.2008.0262.

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HUANG, GUANGYAN, XIAOWEI LI, JING HE, and XIN LI. "DATA MINING VIA MINIMAL SPANNING TREE CLUSTERING FOR PROLONGING LIFETIME OF WIRELESS SENSOR NETWORKS." International Journal of Information Technology & Decision Making 06, no. 02 (June 2007): 235–51. http://dx.doi.org/10.1142/s0219622007002538.

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Clustering is applied in wireless sensor networks for increasing energy efficiency. Clustering methods in wireless sensor networks are different from those in traditional data mining systems. This paper proposes a novel clustering algorithm based on Minimal Spanning Tree (MST) and Maximum Energy resource on sensors named MSTME. Also, specified constrains of clustering in wireless sensor networks and several evaluation metrics are given. MSTME performs better than already known clustering methods of Low Energy Adaptive Clustering Hierarchy (LEACH) and Base Station Controlled Dynamic Clustering Protocol (BCDCP) in wireless sensor networks when they are evaluated by these evaluation metrics. Simulation results show MSTME increases energy efficiency and network lifetime compared with LEACH and BCDCP in two-hop and multi-hop networks, respectively.

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Gaura, E. I., R. J. Rider, and N. Steele. "Closed-loop neural network controlled accelerometer." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 214, no. 2 (March 1, 2000): 129–38. http://dx.doi.org/10.1243/0959651001540852.

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The purpose of this paper is to present aspects of an integrated micromachined sensor-neural network transducer development. Micromachined sensors exhibit particular problems such as non-linear characteristics, manufacturing tolerances and the need for complex electronic circuitry. The novel transducer design described here, based on a mathematical model of the micromachined sensor, is aimed at improving in-service performance and facilitating design and manufacture over conventional transducers. The proposed closed-loop transducer structure incorporates two modular artificial neural networks: a compensating neural network, which performs a static mapping, and a feedback neural network, which both linearizes and demodulates the feedback signal. Simulation results to date show an excellent linearity, wide dynamic range and robustness to shocks for the proposed system. The design was approached from a control engineering perspective due to the closed-loop structure of the transducer.

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Nehra, Vibha, and Ajay K. Sharma. "Topology Controlled Energy Proficient Protocol for Wireless Sensor Networks." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 8 (November 27, 2013): 2895–902. http://dx.doi.org/10.24297/ijct.v11i8.3008.

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Random deployment in Wireless sensor networks lead to spatial node redundancy in close knit sensor networks. In this paper, an improved energy proficient PEGASIS based protocol (PEGASIS-TC) has been proposed. PEGASIS-TC exploits this spatial node redundancy by finding optimal subset of nodes that guarantee connectivity and turns off the remaining nodes based on CTR (Critical transmission range) to conserve energy which can be used in later stages to extend the network lifetime. The simulation results obtained show that PEGASIS-TC gives an increase in network lifetime as compared to PEGASIS.

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Wang, Biao, Haobo Zhang, Yunan Zhu, Banggui Cai, and Xiaopeng Guo. "Adaptive Power-Controlled Depth-Based Routing Protocol for Underwater Wireless Sensor Networks." Journal of Marine Science and Engineering 11, no. 8 (August 9, 2023): 1567. http://dx.doi.org/10.3390/jmse11081567.

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Low energy consumption has always been one of the core issues in the routing design of underwater sensor networks. Due to the high cost and difficulty of deployment and replacement of current underwater nodes, many underwater applications require the routing protocol design to consider the network lifetime extension problem. Based on this, we designed a new routing protocol that takes into account both low energy consumption and balanced energy consumption, and achieves effective extension of the network lifetime, called adaptive power-controlled depth-based routing protocol for underwater wireless sensor networks (APCDBRP). The protocol consists of two phases: (1) the route establishment phase and (2) the data transmission phase. In the route establishment phase, the initial path is established by the sink node broadcasting beacon packets at the maximum transmission power. The receiving nodes update their routing tables based on the beacon information and forward the beacon packets. In the data transmission phase, APCDBRP introduces a novel forwarding factor that considers both energy efficiency and energy balance. It selects the optimal next hop based on high energy efficiency and relatively abundant energy, thus extending the network’s lifetime. Additionally, APCDBRP proposes a new data protection and route reconstruction mechanism to address issues such as network topology changes due to node mobility and data transmission failures. Our simulation is based on AquaSim–Next Generation, which is a specialized tool built on the NS3 platform for researching underwater networks. Simulation results demonstrate that, compared to other typical routing protocols, APCDBRP exhibits superior performance in reducing network energy consumption and extending the network’s lifetime. It also achieves a high packet delivery rate with lower energy consumption.

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Chen, Min, Victor C. M. Leung, and Shiwen Mao. "Directional Controlled Fusion in Wireless Sensor Networks." Mobile Networks and Applications 14, no. 2 (January 19, 2009): 220–29. http://dx.doi.org/10.1007/s11036-008-0133-6.

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Hameed, Bilal Hashim, Anmar Yahya Taher, Raed Khalid Ibrahim, Adnan Hussein Ali, and Yasser Adnan Hussein. "Based on mesh sensor network: design and implementation of security monitoring system with Bluetooth technology." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 3 (June 1, 2022): 1781. http://dx.doi.org/10.11591/ijeecs.v26.i3.pp1781-1790.

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One of the most critical aspects to consider in wireless sensor networks is security, particularly in internet of things (IoT) implementations. Sensor network applications had risen in the past 5 years since these networks have been used in various parts of life (smart residential and commercial buildings, medical, and agriculture). In this study, we provide a novel network of sensors based on the Bluetooth network that may be used to protect commercial buildings. The Bluetooth type HC 06 was chosen since it has a low energy consumption and a communication range of 100 meters. Such security network includes motion sensors and control cameras that are controlled by an Arduino Nano microcontroller. The motion sensor's primary characteristics are solely applicable to humans, and the Arduino Nano is an open-source microcontroller. The key benefit of this research is that it demonstrates how to create a low-cost Bluetooth sensor security network with limited storage space for control movies.

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Madhushri, Priyanka, and Emil Jovanov. "Long-Term Synchronization of Hybrid Sensors Networks." International Journal of Embedded and Real-Time Communication Systems 9, no. 2 (July 2018): 32–46. http://dx.doi.org/10.4018/ijertcs.2018070103.

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This article presents synchronization of a hybrid distributed sensor network with wired and wireless sensors. Authors present an implementation of a sleep monitoring system as a hybrid sensor network that combines wireless inertial sensors controlled by a custom smartphone application as an extension of the polysomnographic (PSG) monitor to improve user's comfort. The authors developed an original method of synchronization of wireless sensor data with the PSG records using an auxiliary audio synchronization signal generated by the smartphone. The timestamps on the smartphone are synchronized with the timestamps from inertial sensors, and time of generated synchronization pulses recorded by the PSG. The individual data streams were synchronized using the Dynamic Time Warping (DTW) mechanism. Authors present the system organization and the results of analysis of the whole night monitoring, including the analysis of channel reliability and clock drift. Clock drift has been reduced from 10-30 seconds to 5.1± 3 milliseconds which is with an improved accuracy as compare to existing methods.

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Qin, Ling, and Bo Lei. "Distributed Multiagent for NAO Robot Joint Position Control Based on Echo State Network." Mathematical Problems in Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/945493.

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Based on echo state networks, the joints position control of NAO robot is studied in this paper. The process to control the robot position can be divided into two phases. The senor parameters are released during the first phase. Depending on the dynamic coupling effect between the angle acceleration of passive joint and the torque of active joint, passive joint can be controlled indirectly to the desired position along the desired trajectory. The ESN control rules during the first phase are described and ESN controller is designed to control the motion of passive joint. The brake is locked during the second phase; then active joint is controlled to the desired position. The experimental control system based on PMAC controller is designed and developed. Finally, the joint position control of the NAO robot is achieved successfully by experiments. Echo state networks utilized incremental updates driven by new sensor readings and massive short memory with history inputs; thus varying communication rates can help imitate human upper limb motion based on wearable sensors to obtain human joint angles.

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Koç, Metin, and Ibrahim Korpeoglu. "Controlled Sink Mobility Algorithms for Wireless Sensor Networks." International Journal of Distributed Sensor Networks 10, no. 4 (January 2014): 167508. http://dx.doi.org/10.1155/2014/167508.

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Hunkeler, Urs, Clemens Lombriser, Hong Linh Truong, and Beat Weiss. "A case for centrally controlled wireless sensor networks." Computer Networks 57, no. 6 (April 2013): 1425–42. http://dx.doi.org/10.1016/j.comnet.2012.12.019.

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CHAKRABORTY, RUDRASIS, CHIN-TENG LIN, and NIKHIL R. PAL. "SENSOR (GROUP FEATURE) SELECTION WITH CONTROLLED REDUNDANCY IN A CONNECTIONIST FRAMEWORK." International Journal of Neural Systems 24, no. 06 (July 31, 2014): 1450021. http://dx.doi.org/10.1142/s012906571450021x.

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For many applications, to reduce the processing time and the cost of decision making, we need to reduce the number of sensors, where each sensor produces a set of features. This sensor selection problem is a generalized feature selection problem. Here, we first present a sensor (group-feature) selection scheme based on Multi-Layered Perceptron Networks. This scheme sometimes selects redundant groups of features. So, we propose a selection scheme which can control the level of redundancy between the selected groups. The idea is general and can be used with any learning scheme. We have demonstrated the effectiveness of our scheme on several data sets. In this context, we define different measures of sensor dependency (dependency between groups of features). We have also presented an alternative learning scheme which is more effective than our old scheme. The proposed scheme is also adapted to radial basis function (RBS) network. The advantages of our scheme are threefold. It looks at all the groups together and hence can exploit nonlinear interaction between groups, if any. Our scheme can simultaneously select useful groups as well as learn the underlying system. The level of redundancy among groups can also be controlled.

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Ransom, Elliot, Xiyuan Chen, and Fu-Kuo Chang. "Design of a Robust Tool for Deploying Large-Area Stretchable Sensor Networks from Microscale to Macroscale." Sensors 22, no. 13 (June 27, 2022): 4856. http://dx.doi.org/10.3390/s22134856.

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An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the surface of large structures at macroscale to create “smart” structures with embedded distributed sensor networks. Integrating a large network of distributed sensors with structures has been a major challenge in the design of so-called smart structures or devices for cyber-physical applications where a large amount of usage data from structures or devices can be generated for artificial intelligence applications. Indeed, many “island-and-serpentine”-type distributed sensor networks, while promising, remain difficult to deploy. This study aims to enable such networks to be deployed in a safe, automated, and efficient way. To this end, a scissor-hinge controlled system was proposed as the basis for a deployment mechanism for such stretchable sensor networks (SSNs). A model based on a kinematic scissor-hinge mechanism was developed to simulate and design the proposed system to automatically stretch a micro-scaled square network with uniformly distributed sensor nodes. A prototype of an automatic scissor-hinge stretchable tool was constructed during the study with an array of four scissor-hinge mechanisms, each belt-driven by a single stepper motor. Two micro-fabricated SSNs from a 100 mm wafer were fabricated at the Stanford Nanofabrication Facility for this deployment study. The networks were designed to be able to cover an area 100 times their manufacturing size (from a 100 mm diameter wafer to a 1 m2 active area) once stretched. It was demonstrated that the proposed deployment tool could place sensor nodes in prescribed locations efficiently within a drastically shorter time than in current labor-intensive manual deployment methods.

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Liu, Guiyun, Yonggui Liu, Jing Yao, Hongbin Chen, and Dong Tang. "Repeated Game for Distributed Estimation in Autonomous Clustered Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/806456.

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A commonly encountered problem in wireless sensor networks (WSNs) applications is to reconstruct the state of nature, that is, distributed estimation of a parameter of interest through WSNs’ observations. However, the distributed estimation in autonomous clustered WSNs faces a vital problem of sensors’ selfishness. Each sensor autonomously decides whether or not to transmit its observations to the fusion center (FC) and not be controlled by the fusion center (FC) any more. Thus, to encourage cooperation within selfish sensors, infinitely and finitely repeated games are firstly modeled to depict sensors’ behaviors. Then, the existences of Nash equilibriums for infinitely and finitely repeated games are discussed. Finally, simulation results show that the proposed Nash equilibrium strategies are effective.

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Quwaider, Muhannad, and Subir Biswas. "Physical Context Detection using Wearable Wireless Sensor Networks." Journal of Communications Software and Systems 4, no. 3 (September 22, 2008): 191. http://dx.doi.org/10.24138/jcomss.v4i3.219.

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This paper presents the architecture of a wearable sensor network and a Hidden Markov Model (HMM) processingframework for stochastic identification of body postures andphysical contexts. The key idea is to collect multi-modal sensor data from strategically placed wireless sensors over a human subject’s body segments, and to process that using HMM in order to identify the subject’s instantaneous physical context. The key contribution of the proposed multi-modal approach is a significant extension of traditional uni-modal accelerometry in which only the individual body segment movements, without their relative proximities and orientation modalities, is used for physical context identification. Through real-life experiments with body mounted sensors it is demonstrated that while the unimodal accelerometry can be used for differentiating activityintensive postures such as walking and running, they are not effective for identification and differentiation between lowactivity postures such as sitting, standing, lying down, etc. In the proposed system, three sensor modalities namely acceleration, relative proximity and orientation are used for context identification through Hidden Markov Model (HMM) based stochastic processing. Controlled experiments using human subjects are carried out for evaluating the accuracy of the HMMidentified postures compared to a naïve threshold based mechanism over different human subjects.

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Ananth, S., A. M. Kalpana, and R. Vijayarajeswari. "A dynamic technique to enhance quality of service in software-defined network-based wireless sensor network (DTEQT) using machine learning." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 01 (July 4, 2019): 1941020. http://dx.doi.org/10.1142/s0219691319410200.

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Wireless Sensor Network (WSN) is the interconnection between things or objects embedded with hardware and software. In WSN, small end devices (like sensors) and high end devices (like servers) are connected to the Internet. For WSN enabled in Software-Defined Network (SDN), the routers are controlled using a controller server node. It is a dynamic network due to the presence of mobile nodes and energy constrained nodes. The routing is the process of detecting route from source to target. In dynamic networks like WSN, routing is a challengeable task. This paper is to provide a routing solution for backboneless SDN-enabled WSN. The proposed work enhances routing Quality of Service (QoS) in WSN. The paths are dynamically reallocated to reduce the packet loss.

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Abu Taleb, Anas, Qasem Abu Al-Haija, and Ammar Odeh. "Efficient Mobile Sink Routing in Wireless Sensor Networks Using Bipartite Graphs." Future Internet 15, no. 5 (May 14, 2023): 182. http://dx.doi.org/10.3390/fi15050182.

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Wireless sensor networks (W.S.N.s) are a critical research area with numerous practical applications. W.S.N.s are utilized in real-life scenarios, including environmental monitoring, healthcare, industrial automation, smart homes, and agriculture. As W.S.N.s advance and become more sophisticated, they offer limitless opportunities for innovative solutions in various fields. However, due to their unattended nature, it is essential to develop strategies to improve their performance without draining the battery power of the sensor nodes, which is their most valuable resource. This paper proposes a novel sink mobility model based on constructing a bipartite graph from a deployed wireless sensor network. The proposed model uses bipartite graph properties to derive a controlled mobility model for the mobile sink. As a result, stationary nodes will be visited and planned to reduce routing overhead and enhance the network’s performance. Using the bipartite graph’s properties, the mobile sink node can visit stationary sensor nodes in an optimal way to collect data and transmit it to the base station. We evaluated the proposed approach through simulations using the NS-2 simulator to investigate the performance of wireless sensor networks when adopting this mobility model. Our results show that using the proposed approach can significantly enhance the performance of wireless sensor networks while conserving the energy of the sensor nodes.

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Pongsakornsathien, Nichakorn, Yixiang Lim, Alessandro Gardi, Samuel Hilton, Lars Planke, Roberto Sabatini, Trevor Kistan, and Neta Ezer. "Sensor Networks for Aerospace Human-Machine Systems." Sensors 19, no. 16 (August 8, 2019): 3465. http://dx.doi.org/10.3390/s19163465.

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Intelligent automation and trusted autonomy are being introduced in aerospace cyber-physical systems to support diverse tasks including data processing, decision-making, information sharing and mission execution. Due to the increasing level of integration/collaboration between humans and automation in these tasks, the operational performance of closed-loop human-machine systems can be enhanced when the machine monitors the operator’s cognitive states and adapts to them in order to maximise the effectiveness of the Human-Machine Interfaces and Interactions (HMI2). Technological developments have led to neurophysiological observations becoming a reliable methodology to evaluate the human operator’s states using a variety of wearable and remote sensors. The adoption of sensor networks can be seen as an evolution of this approach, as there are notable advantages if these sensors collect and exchange data in real-time, while their operation is controlled remotely and synchronised. This paper discusses recent advances in sensor networks for aerospace cyber-physical systems, focusing on Cognitive HMI2 (CHMI2) implementations. The key neurophysiological measurements used in this context and their relationship with the operator’s cognitive states are discussed. Suitable data analysis techniques based on machine learning and statistical inference are also presented, as these techniques allow processing both neurophysiological and operational data to obtain accurate cognitive state estimations. Lastly, to support the development of sensor networks for CHMI2 applications, the paper addresses the performance characterisation of various state-of-the-art sensors and the propagation of measurement uncertainties through a machine learning-based inference engine. Results show that a proper sensor selection and integration can support the implementation of effective human-machine systems for various challenging aerospace applications, including Air Traffic Management (ATM), commercial airliner Single-Pilot Operations (SIPO), one-to-many Unmanned Aircraft Systems (UAS), and space operations management.

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Rhman, Zain-Aldeen, Ramzy Ali, and Basil Jasim. "Wirelessly Controlled Irrigation System." Iraqi Journal for Electrical and Electronic Engineering 10, no. 2 (December 1, 2014): 89–99. http://dx.doi.org/10.37917/ijeee.10.2.4.

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In the city of Basrah, there is an urgent need to use the water for irrigation process more efficiently for many reasons: one of them, the high temperature in long summer season and the other is the lack of sources fresh water sources. In this work, a smart irrigation system based wireless sensor networks (WSNs) is implemented. This system consists of the main unit that represented by an Arduino Uno board which include an ATmega328 microcontroller, different sensors as moisture sensors, temperature sensors, humidity sensors, XBee modules and solenoid valve. Zigbee technology is used in this project for implementing wireless technology. This system has two modes one manual mode, the other is a smart mode. The set points must be changed manually according to the specified season to satisfy the given conditions for the property irrigation, and the smart operation of the system will be according to these set points.

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Seo, Jun-Bae, and Hu Jin. "Optimally Controlled Pure ALOHA Systems for Wireless Sensor Networks." IEEE Communications Letters 21, no. 11 (November 2017): 2460–63. http://dx.doi.org/10.1109/lcomm.2017.2731314.

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Zhitong Huang, Yuefeng Ji, Yueming Lu, and Daxiong Xu. "Sensor-based performance monitoring mechanism in GMPLS-controlled networks." IEEE Communications Letters 12, no. 4 (April 2008): 325–27. http://dx.doi.org/10.1109/lcomm.2008.071279.

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Misra, Sudip, and Ankur Jain. "Policy controlled self-configuration in unattended wireless sensor networks." Journal of Network and Computer Applications 34, no. 5 (September 2011): 1530–44. http://dx.doi.org/10.1016/j.jnca.2010.07.002.

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Basagni, Stefano, Alessio Carosi, Emanuel Melachrinoudis, Chiara Petrioli, and Z. Maria Wang. "Controlled sink mobility for prolonging wireless sensor networks lifetime." Wireless Networks 14, no. 6 (February 7, 2007): 831–58. http://dx.doi.org/10.1007/s11276-007-0017-x.

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Han, Duo, Keyou You, Lihua Xie, Junfeng Wu, and Ling Shi. "Optimal Parameter Estimation Under Controlled Communication Over Sensor Networks." IEEE Transactions on Signal Processing 63, no. 24 (December 2015): 6473–85. http://dx.doi.org/10.1109/tsp.2015.2469639.

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Prabhu. M, Mr Dinesh, and Dr Dinesh Senduraja. "MAC chastised Dynamism Efficient in Wireless Device Lattice Spending Mistralapproach." International Journal of Engineering and Computer Science 10, no. 12 (December 15, 2021): 25453–58. http://dx.doi.org/10.18535/ijecs/v10i12.4641.

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In Wireless sensor Network, several researchers have provided different routing protocol for sensor networks, particularly routing protocols depending on clusters protocols. Reliability of nodes is necessary parameter in effective sensor networks. We use MAC protocol for controlling the network packets. This is because the usage of cluster based routing has several merits like minimized control messages, re-usability of bandwidth and enhanced power control. Different cluster based routing protocol is proposed by many researchers for the purpose of reducing the consumption energy in wireless sensor networks. Those techniques reduces the energy consumption but with several disadvantages like lack of QoS, inefficient transmission, etc., To overcome those problems, modified QoS enhanced base station controlled in Mistrial Approach (flooding Technique) for wireless sensor networks is proposed in this work. Here we reduce the number of retransmission and detect the overlay packets in networks using proposed approach. Simulation results show the better energy consumption, Maximum Life time & Efficient Bandwidth is achieved by flooding management when compared to the conventional techniques

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Selvakennedy, S., and S. Sinnappan. "An Adaptive Data Dissemination Strategy for Wireless Sensor Networks." International Journal of Distributed Sensor Networks 3, no. 1 (February 1, 2007): 23–40. http://dx.doi.org/10.1080/15501320601067725.

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Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena in real time. However, the nodes are typically highly resource-constrained. Since the communication task is a significant power consumer, various attempts have been made to introduce energy-awareness at different levels within the communication stack. Clustering is one such attempt to control energy dissipation for sensor data dissemination in a multihop fashion. The Time-Controlled Clustering Algorithm (TCCA) is proposed to realize a network-wide energy reduction. A realistic energy dissipation model is derived probabilistically to quantify the sensor network's energy consumption using the proposed clustering algorithm. A discrete-event simulator is developed to verify the mathematical model and to further investigate TCCA in other scenarios. The simulator is also extended to include the rest of the communication stack to allow a comprehensive evaluation of the proposed algorithm.

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Akkaya, Kemal, Fatih Senel, Aravind Thimmapuram, and Suleyman Uludag. "Distributed Recovery from Network Partitioning in Movable Sensor/Actor Networks via Controlled Mobility." IEEE Transactions on Computers 59, no. 2 (February 2010): 258–71. http://dx.doi.org/10.1109/tc.2009.120.

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Faizullin, Marsel, Anastasiia Kornilova, Azat Akhmetyanov, and Gonzalo Ferrer. "Twist-n-Sync: Software Clock Synchronization with Microseconds Accuracy Using MEMS-Gyroscopes." Sensors 21, no. 1 (December 24, 2020): 68. http://dx.doi.org/10.3390/s21010068.

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Sensor networks require a high degree of synchronization in order to produce a stream of data useful for further purposes. Examples of time misalignment manifest as undesired artifacts when doing multi-camera bundle-adjustment or global positioning system (GPS) geo-localization for mapping. Network Time Protocol (NTP) variants of clock synchronization can provide accurate results, though present high variance conditioned by the environment and the channel load. We propose a new precise technique for software clock synchronization over a network of rigidly attached devices using gyroscope data. Gyroscope sensors, or IMU, provide a high-rate measurements that can be processed efficiently. We use optimization tools over the correlation signal of IMU data from a network of gyroscope sensors. Our method provides stable microseconds accuracy, regardless of the number of sensors and the conditions of the network. In this paper, we show the performance of the gyroscope software synchronization in a controlled environment, and we evaluate the performance in a sensor network of smartphones by our open-source Android App, Twist-n-Sync, that is publicly available.

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Natalizio, Enrico, and Valeria Loscrí. "Controlled mobility in mobile sensor networks: advantages, issues and challenges." Telecommunication Systems 52, no. 4 (August 19, 2011): 2411–18. http://dx.doi.org/10.1007/s11235-011-9561-x.

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Ghica, O., G. Trajcevski, P. Scheuermann, N. Valtchanov, and Z. Bischof. "Controlled Multi-Path Routing in Sensor Networks Using Bezier Curves." Computer Journal 54, no. 2 (April 9, 2010): 230–54. http://dx.doi.org/10.1093/comjnl/bxq034.

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Khan, Atta ur Rehman, Sajjad A. Madani, Khizar Hayat, and Samee Ullah Khan. "Clustering-based power-controlled routing for mobile wireless sensor networks." International Journal of Communication Systems 25, no. 4 (May 2, 2011): 529–42. http://dx.doi.org/10.1002/dac.1280.

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Cheng, Yusi, Chen Fang, Jingfeng Yuan, and Lei Zhu. "Design and Application of a Smart Lighting System Based on Distributed Wireless Sensor Networks." Applied Sciences 10, no. 23 (November 29, 2020): 8545. http://dx.doi.org/10.3390/app10238545.

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Buildings have been an important energy consuming sector, and inefficient controlling of lights can result in wastage of energy in buildings. The aim of the study is to reduce energy consumption by implementing a smart lighting system that integrates sensor technologies, a distributed wireless sensor network (WSN) using ZigBee protocol, and illumination control rules. A sensing module consists of occupancy sensors, including passive infrared (PIR) sensors and microwave Doppler sensors, an ambient light sensor, and lighting control rules. The dimming level of each luminaire is controlled by rules taking into consideration occupancy and daylight harvesting. The performance of the proposed system is evaluated in two scenarios, a metro station and an office room, and the average energy savings are about 45% and 36%, respectively. The effects of different factors on energy savings are analyzed, including people flow density, weather, desired illuminance, and the number of people in a room. Experimental results demonstrate the robustness of the proposed system and its ability to save energy consumption. The study can benefit the development of intelligent and sustainable buildings.

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Ju, Zhiyang, Hui Zhang, Ying Tan, and Xiang Chen. "Coverage control of mobile sensor networks with directional sensing." Mathematical Biosciences and Engineering 19, no. 3 (2022): 2913–34. http://dx.doi.org/10.3934/mbe.2022134.

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<abstract>Control design of mobile sensors for coverage problem is addressed in this paper. The mobile sensors have non-linear dynamics and directional sensing properties which mean the sensing performance is also affected by the pointing directions of the sensors. Different from the standard optimal coverage problem where sensors are assumed to be omni-directional ones, orientation angles of the directional sensors should also be controlled, other than the position control, to achieve the coverage purpose. Considering also the non-linear dynamics of the mobile sensors, new control methodology is necessarily developed for the coverage problem with directional sensors. In the approach proposed, an innovative gradient based non-smooth motion controller is designed for the mobile sensors with unicycle dynamics. With the proposed controllers, the states of sensors will always stay in an positive invariant set where the gradient of the performance valuation function is well-defined if they are initialized within this set. Moreover, the sensors' states are proved to converge to some critical point where the gradient is zero. Simulation results are provided to illustrate the performance of the proposed coverage control strategy.</abstract>

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Qiu, Zhiyu, Lihong Wu, and Peixin Zhang. "An Efficient Localization Method for Mobile Nodes in Wireless Sensor Networks." International Journal of Online Engineering (iJOE) 13, no. 03 (March 28, 2017): 160. http://dx.doi.org/10.3991/ijoe.v13i03.6868.

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With the development of electronic technology and communication protocols, wireless sensor network technology is developing rapidly. In a sense, the traditional static wireless sensor network has been unable to meet the needs of new applications. However, the introduction of mobile nodes extends the application of wireless sensor networks, despite the technical challenges. Because of its flexibility, the mobile wireless sensor network has attracted great attention, and even small, self-controlled mobile sensor devices have appeared. At present, mobile node localization has become one of the hotspots in wireless sensor networks. As the storage energy of wireless sensor network nodes is limited, and the communication radius is small, many scientists have focused their research direction on the location algorithm of mobile nodes. According to the continuity principle of mobile node movement, in this paper we propose an improved mobile node localization algorithm based on the Monte Carlo Location (MCL) algorithm, and the method can reduce the sampling interval effectively. First of all, this paper introduces the structure and classification of wireless sensor localization technology. Secondly, the principle of the Monte Carlo Location algorithm is described in detail. Thirdly, we propose an efficient method for mobile node localization based on the MCL algorithm. Finally, the effectiveness and accuracy of the new algorithm are verified by comparative analysis.

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Shahriar, S., I. Rahaman, A. Bin Karim, M. M. Hasan, F. Chowdhury, and M. Sarker. "Bridging Internet of Things and Wireless Sensor Networks: Applications and Challenges." Indonesian Journal of Computing, Engineering and Design (IJoCED) 2, no. 1 (April 3, 2020): 13. http://dx.doi.org/10.35806/ijoced.v2i1.99.

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With the increasing demand of Wireless Sensor Networks (WSNs) innovations, it cuts numerous zones mobile communication, cloud computing and embedded system in modern living. Inter-net of Things (IoT) is widely used in environmental condition monitoring, logistic support and interfacing sensors and actuators wirelessly, which can be controlled from very long distance. This offers the capacity to control the world from a corner of a room. Wherein sensors and actuators operate reliably with the help of IoT. Wireless data transmission that uses Radio Frequency (RF) has major technical burdens and security vulnerability. The IoT replaced RF as it provides secure transmission capabilities. In this paper, we exhibit a technical overview of WSNs and IoT especially their drawbacks and challenges. Additionally, this paper discusses the progress of the WSNs and IoT innovation.

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Nehra, Vibha, Raju Pal, and Ajay K. Sharma. "Fuzzy-based Leader Selection for Topology Controlled PEGASIS Protocol for Lifetime Enhancement in Wireless Sensor Network." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 3 (April 30, 2013): 755–64. http://dx.doi.org/10.24297/ijct.v4i3.4198.

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Wireless sensor Networks present a new generation of real time embedded systems with limited computation, energy and memory resources that are being used in wide variety of applications where traditional networking infrastructure is practically infeasible. Legitimate leader selection can drastically improve the lifetime of the sensor network. This paper proposes fuzzy logic methodology for leader election in PEGASIS based protocol PEGASIS-TC [1] based on two descriptors- residual energy of node and its proximity to Base Station. Simulation results show that depending on network configuration, a substantial increase in stability of network lifetime can be accomplished as compared to PEGASIS-TC.

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Cuevas-Martinez, Juan-Carlos, Antonio-Jesus Yuste-Delgado, Antonio-Jose Leon-Sanchez, Antonio-Jose Saez-Castillo, and Alicia Triviño-Cabrera. "A New Centralized Clustering Algorithm for Wireless Sensor Networks." Sensors 19, no. 20 (October 11, 2019): 4391. http://dx.doi.org/10.3390/s19204391.

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Clustering is presently one of the main routing techniques employed in randomly deployed wireless sensor networks. This paper describes a novel centralized unequal clustering method for wireless sensor networks. The goals of the algorithm are to prolong the network lifetime and increase the reliability of the network while not compromising the data transmission. In the proposed method, the Base Station decides on the cluster heads according to the best scores obtained from a Type-2 Fuzzy system. The input parameters of the fuzzy system are estimated by the base station or gathered from the network with a careful design that reduces the control message exchange. The whole network is controlled by the base station in a rounds-based schedule that alternates rounds when the base station elects cluster heads, with other rounds in which the cluster heads previously elected, gather data from their contributing nodes and forward them to the base station. The setting of the number of rounds in which the Base Station keeps the same set of cluster heads is another contribution of the present paper. The results show significant improvements achieved by the proposal when compared to other current clustering methods.

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Pachlor, Rohit, and Deepti Shrimankar. "VCH-ECCR: A Centralized Routing Protocol for Wireless Sensor Networks." Journal of Sensors 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8946576.

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A wireless sensor network (WSN) is a collection of hundreds to thousands of compact, battery-operated sensors. It is deployed to accumulate useful information from the nearby environment. Depending upon the type of application, the sensors have to work for months to years with a finite energy source. In some extreme environments, the replacement of energy source is challenging and sometimes not feasible. Therefore, it is vital for sensors to perform their duties in an energy efficient way to improve the longevity of the network. This paper proposes an energy-efficient centralized cluster-based routing protocol called Vice-Cluster-Head-Enabled Centralized Cluster-based Routing protocol (VCH-ECCR). The VCH-ECCR uses a two-level hierarchy of vice cluster heads to use the energy of sensors efficiently and to cut back the frequency of the clustering. The performance of VCH-ECCR is compared with low-energy adaptive clustering hierarchy (LEACH), LEACH-Centralized (LEACH-C), and base station controlled dynamic clustering protocol (BCDCP). The experimental results show that the VCH-ECCR outperforms over its comparative in terms of network lifetime, overall energy consumption, and throughput.

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Delussu, Federico, Faisal Imran, Christian Mattia, and Rosa Meo. "Fuel Prediction and Reduction in Public Transportation by Sensor Monitoring and Bayesian Networks." Sensors 21, no. 14 (July 11, 2021): 4733. http://dx.doi.org/10.3390/s21144733.

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We exploit the use of a controller area network (CAN-bus) to monitor sensors on the buses of local public transportation in a big European city. The aim is to advise fleet managers and policymakers on how to reduce fuel consumption so that air pollution is controlled and public services are improved. We deploy heuristic algorithms and exhaustive ones to generate Bayesian networks among the monitored variables. The aim is to describe the relevant relationships between the variables, to discover and confirm the possible cause–effect relationships, to predict the fuel consumption dependent on the contextual conditions of traffic, and to enable an intervention analysis to be conducted on the variables so that our goals are achieved. We propose a validation technique using Bayesian networks based on Granger causality: it relies upon observations of the time series formed by successive values of the variables in time. We use the same method based on Granger causality to rank the Bayesian networks obtained as well. A comparison of the Bayesian networks discovered against the ground truth is proposed in a synthetic data set, specifically generated for this study: the results confirm the validity of the Bayesian networks that agree on most of the existing relationships.

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Rahiminasab, Atefeh, Peyman Tirandazi, M. J. Ebadi, Ali Ahmadian, and Mehdi Salimi. "An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks." Applied Sciences 10, no. 21 (November 6, 2020): 7886. http://dx.doi.org/10.3390/app10217886.

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Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

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Kotukh, Y. V., V. O. Lyubchak, and O. P. Strakh. "One approach to the design of individual mathematical models of security in wireless sensor networks." Radiotekhnika, no. 207 (December 24, 2021): 78–82. http://dx.doi.org/10.30837/rt.2021.4.207.08.

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The current level of development of engineering and technology is characterized by a constant expansion of the variety and complexity of mechanical and controlled objects, the operation of which occurs in a continuous-discrete time mode. One of these objects is the process of spreading malicious software in wireless sensor networks, the constant growth of trends towards which is due to their use as a single type of self-organized data transmission network with the least labor intensity and low cost. The concept of building sensor networks has not been formed at all. Therefore, the study of certain properties of such networks is very important for both domestic and world science. Moreover, for the strategically important sectors of the country, in particular defense, the protection of wireless sensor networks is a very important component. A new model of malware distribution is proposed, which is described by some boundary value problem for an impulsive dynamical system on a time scale.

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Lilhore, Umesh Kumar, Osamah Ibrahim Khalaf, Sarita Simaiya, Carlos Andrés Tavera Romero, Ghaida Muttashar Abdulsahib, Poongodi M, and Dinesh Kumar. "A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks." International Journal of Distributed Sensor Networks 18, no. 9 (September 2022): 155013292211171. http://dx.doi.org/10.1177/15501329221117118.

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Underwater wireless sensor network attracted massive attention from researchers. In underwater wireless sensor network, many sensor nodes are distributed at different depths in the sea. Due to its complex nature, updating their location or adding new devices is pretty challenging. Due to the constraints on energy storage of underwater wireless sensor network end devices and the complexity of repairing or recharging the device underwater, this is highly significant to strengthen the energy performance of underwater wireless sensor network. An imbalance in power consumption can cause poor performance and a limited network lifetime. To overcome these issues, we propose a depth controlled with energy-balanced routing protocol, which will be able to adjust the depth of lower energy nodes and be able to swap the lower energy nodes with higher energy nodes to ensure consistent energy utilization. The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. The proposed model also utilized an enhanced back propagation neural network for data fusion operation, which is based on multi-hop system and also operates a highly optimized momentum technique, which helps to choose only optimum energy nodes and avoid duplicate selections that help to improve the overall energy and further reduce the quantity of data transmission. In the proposed energy-efficient routing protocol, an enhanced cluster head node is used to select a strategy that can analyze the remaining energy and directions of each participating node. In the simulation, the proposed model achieves 86.7% packet delivery ratio, 12.6% energy consumption, and 10.5% packet drop ratio over existing depth-based routing and energy-efficient depth-based routing methods for underwater wireless sensor network.

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Nithya, V., B. Ramachandran, and G. Vaishanavi Devi. "Energy Efficient Tree Routing Protocol for Topology Controlled Wireless Sensor Networks." International Journal on Communications Antenna and Propagation (IRECAP) 5, no. 1 (February 28, 2015): 1. http://dx.doi.org/10.15866/irecap.v5i1.4805.

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de Silva, V., and R. Ghrist. "Coordinate-free Coverage in Sensor Networks with Controlled Boundaries via Homology." International Journal of Robotics Research 25, no. 12 (December 2006): 1205–22. http://dx.doi.org/10.1177/0278364906072252.

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Kominami, Daichi, Masashi Sugano, Masayuki Murata, and Takaaki Hatauchi. "Controlled and self-organized routing for large-scale wireless sensor networks." ACM Transactions on Sensor Networks 10, no. 1 (November 2013): 1–27. http://dx.doi.org/10.1145/2529920.

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Raval, Gaurang, Madhuri Bhavsar, and Nitin Patel. "Enhancing data delivery with density controlled clustering in wireless sensor networks." Microsystem Technologies 23, no. 3 (May 30, 2016): 613–31. http://dx.doi.org/10.1007/s00542-016-2990-4.

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Mourad, Farah, Hicham Chehade, Hichem Snoussi, Farouk Yalaoui, Lionel Amodeo, and Cedric Richard. "Controlled Mobility Sensor Networks for Target Tracking Using Ant Colony Optimization." IEEE Transactions on Mobile Computing 11, no. 8 (August 2012): 1261–73. http://dx.doi.org/10.1109/tmc.2011.154.

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Kim, Jaesub, and Kyu Ho Park. "An energy-efficient, transport-controlled MAC protocol for wireless sensor networks." Computer Networks 53, no. 11 (July 2009): 1879–902. http://dx.doi.org/10.1016/j.comnet.2009.03.002.

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Journal articles on the topic 'Controlled sensor networks'

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