Journal articles on the topic 'Sensor networks'
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Chan, Tung Jung, Ching Mu Chen, and Tsair Rong Chen. "A Forwarding Station Integrated with Optimal Cluster Number Selection in Wireless Sensor Networks." Applied Mechanics and Materials 201-202 (October 2012): 745–48. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.745.
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In wireless sensor networks, power consumption is the most important issue. That is wireless sensors are normally deployed into unattended places where power of sensors is hard to be charged. Indeed, the network lifetime of wireless sensor networks equipped with city power or deployed into attended place is much longer than those wireless sensors equipped with batteries. In general, wireless sensor nodes are connected together and become a network after deployed into certain places. With the certain range places that wireless senor nodes deployed into, finding the optimal clusters can increase the entire network lifetime. Also, adding the forwarding station extends the network lifetime. Therefore, this paper proposes the integration of both the forwarding station and optimal clusters in ad-hoc wireless sensor networks. Simulation results show that the entire network lifetime proposed is extended in this paper compared to both optimal cluster number selection and normal forwarding station.
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Samara, Ghassan, Mohammad Hassan, and Yahya Zayed. "An Intelligent Vice Cluster Head Election Protocol in WSN." International Journal of Advances in Soft Computing and its Applications 13, no. 3 (November 28, 2021): 202–22. http://dx.doi.org/10.15849/ijasca.211128.14.
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Wireless sensor networks (WSNs) has a practical ability to link a set of sensors to build a wireless network that can be accessed remotely; this technology has become increasingly popular in recent years. Wi-Fi-enabled sensor networks (WSNs) are used to gather information from the environment in which the network operates. Many obstacles prevent wireless sensor networks from being used in a wide range of fields. This includes maintaining network stability and extending network life. In a wireless network, sensors are the most essential component. Sensors are powered by a battery that has a finite amount of power. The battery is prone to power loss, and the sensor is therefore rendered inoperative as a result. In addition, the growing number of sensor nodes off-site affects the network's stability. The transmission and reception of information between the sensors and the base consumes the most energy in the sensor. An Intelligent Vice Cluster Head Selection Protocol is proposed in this study (IVC LEACH). In order to achieve the best performance with the least amount of energy consumption, the proposed hierarchical protocol relies on a fuzzy logic algorithm using four parameters to calculate the value of each node in the network and divides them into three hierarchical levels based on their value. This improves network efficiency and reliability while extending network life by 50 percent more than the original Low Energy Adaptive Clustering Hierarchy protocol. Keywords: Wireless Sensor Networks, Sensors, Communication Protocol, Fuzzy logic, Leach protocol.
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Toliupa, Sergey, Yuriy Kravchenko, and Aleksander Trush. "ORGANIZATION OF IMPLEMENTATION OF UBIQUITOUS SENSOR NETWORKS." Informatics Control Measurement in Economy and Environment Protection 8, no. 1 (February 28, 2018): 36–39. http://dx.doi.org/10.5604/01.3001.0010.8643.
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The article deals with the implementation of one of the most promising technologies of the 21st century – the permeable sensor networks of the USN. The features, architecture, organization and routing algorithms of sensory networks are described. It is determined that further improvement of the work of such networks requires standardization of the development process and implementation process. USN's Vertical Sensor Networks is one of the most promising technologies of the 21st century. Cheap and "smart" sensors, in large quantities combined into a wireless network connected to the public communications network, today provide an unprecedentedly wide range of control and management services for buildings, businesses, cars, and so forth. USN networks, depending on the type of sensors, can be deployed on the ground, in the air, under and over water, in buildings and, finally, on the skin and inside living organisms, including humans. They are also widely used in such important areas as military affairs, crisis and emergency management, and the fight against terrorism.
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Swapna, Bamuli. "Scalable Network Architectures for Distributed Wireless Sensor Networks." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (June 25, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem36083.
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Advances in sensor era and laptop networks have enabled allotted sensor networks (DSNs) to evolve from small clusters of large sensors to big swarms of micro sensors, from constant sensor nodes to mobile nodes, from stressed out communications to wireless communications, from static community topology to dynamically converting topology. To layout those networks, the factors needed to be considered are the coverage place, mobility, power intake, communication Skills and so on. In this study a survey is given regarding the analysis of AC structure and DHC shape, flat tree and DG community, sensor structure layout, ad-hoc sensor networks, sensor packages and also an outline on the patron/server version and cell-Agent primarily based community
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Vino, T., S. S. Sivaraju, R. V. V. Krishna, T. Karthikeyan, Yogesh kumar Sharma, K. G. S. Venkatesan, G. Manikandan, R. Selvameena, and Mebratu Markos. "Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy." International Journal of Photoenergy 2022 (October 11, 2022): 1–8. http://dx.doi.org/10.1155/2022/1164613.
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A wireless touch network is a distributed, self-organizing network of multiple sensors and actuators in combination with multiple sensors and a radio channel. Also, the security area of such a network can be several meters to several meters. The main difference between wireless sensor networks from traditional computer and telephone networks is the lack of a fixed infrastructure owned by a specific operator or provider. Each user terminal in a touch network is capable of acting as a terminal device only. Despite the long history of sensor networks, the concept of building a sensor network is not finally imposed and expressed in some software and hardware (platform) solutions. In this paper, the design and analysis of multicluster model of the sensor nodes in wireless sensor network with the help of solar energy. This proposed model provides the required energy to transmit the information between two end nodes in different cluster. The communication between the end to end clusters was increased based on this design. The implementation of sensory networks at the current stage depends largely on the specific needs of the industrial problem. The architecture, software, and hardware implementation technology is at an intensive development stage, attracting the attention of developers looking for a technological niche of future makers.
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THATIPAMULA RAJU, THATIPAMULA RAJU, and D. DEEPIKA RANI D. DEEPIKA RANI. "Achieving Network Level Privacy in Wireless Sensor Networks." International Journal of Scientific Research 2, no. 8 (June 1, 2012): 183–87. http://dx.doi.org/10.15373/22778179/aug2013/61.
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Hardman, David, Thomas George Thuruthel, Antonia Georgopoulou, Frank Clemens, and Fumiya Iida. "3D Printable Soft Sensory Fiber Networks for Robust and Complex Tactile Sensing." Micromachines 13, no. 9 (September 17, 2022): 1540. http://dx.doi.org/10.3390/mi13091540.
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The human tactile system is composed of multi-functional mechanoreceptors distributed in an optimized manner. Having the ability to design and optimize multi-modal soft sensory systems can further enhance the capabilities of current soft robotic systems. This work presents a complete framework for the fabrication of soft sensory fiber networks for contact localization, using pellet-based 3D printing of piezoresistive elastomers to manufacture flexible sensory networks with precise and repeatable performances. Given a desirable soft sensor property, our methodology can design and fabricate optimized sensor morphologies without human intervention. Extensive simulation and experimental studies are performed on two printed networks, comparing a baseline network to one optimized via an existing information theory based approach. Machine learning is used for contact localization based on the sensor responses. The sensor responses match simulations with tunable performances and good localization accuracy, even in the presence of damage and nonlinear material properties. The potential of the networks to function as capacitive sensors is also demonstrated.
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Navya, B., and M. Ankitha. "Wireless Sensor Networks." International Journal of Research Publication and Reviews 5, no. 3 (March 9, 2024): 3875–77. http://dx.doi.org/10.55248/gengpi.5.0324.0767.
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Petrivskyi, V. Y., V. L. Shevchenko, O. S. Bychkov, and I. P. Sinitsyn. "Information technology to ensure the survivability of sensor networks." PROBLEMS IN PROGRAMMING, no. 4 (December 2021): 062–69. http://dx.doi.org/10.15407/pp2021.04.062.
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In the modern technological world, sensors and sensor networks are widely used in the all spheres of human activity. One of the key engineering tasks in the design of sensor networks is to ensure the survivability of the network. The article presents algorithms for ensuring the survivability of sensor networks based on a preliminary assessment of this property. Estimation of survivability depends on the network topology. Increasing the survivability of the sensor network is achieved by including additional sensors in the network. An algorithm for finding the position of additional sensors in the stationary sensor network is proposed. Proposed approach takes into account the radius of coverage of the sensors and the need for the intersection of the coverage areas of the sensors to ensure the exchange of information. An iterative algorithm for ensuring the survivability of the network in the presence and consideration of dynamic sensors is presented. The results of computer simulation experiments presented in the paper confirm the effectiveness of the proposed approaches.
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Shukur, Marwan Ihsan. "S-CDCA: a semi-cluster directive-congestion protocol for priority-based data in WSNs." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (July 1, 2021): 438. http://dx.doi.org/10.11591/ijeecs.v23.i1.pp438-444.
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The internet of things (IoT) protocols and regulations are being developed forvarious applications includes: habitat monitoring, machinery control, general health-care, smart-homes and more. A great part of I0T comprised of sensors nodes in connected networks (i.e. sensor networks.). A sensor network is a group of nodes with sensory module and computational elements connected through network interfaces. The most interesting type of sensor networks are wireless sensor networks. The nodes here are connected through wirless interfaces. The shared medium between these nodes, creates different challenges. Congestion in such network is ineavitable. Different models andmethods were proposed to alleviate congestion in wireless sensor networks.This paper presents a semi-cluster directive congestion method that allivatenetwork congestion forpriority-baseddata transmission. The method simprove the network performance by implementing temporary cluster forlow level priority data packets while providing a clear link between highpriority data source node and the network base station. Simulation resultsshow that. The proposed method outperformes ad hocOn-demand distance vector (AODV) reactive procotol approach and priority-based congestion control dynamic clustering (PCCDC) a cluster-based methodin network energy consumption and control packets overhead during network operation.The proposed method also shows comparative improvments in end-to-enddelays versus PCCDC.
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Habibi, Payman, Goran Hassanifard, Abdulbaghi Ghaderzadeh, and Arez Nosratpour. "Offering a Demand-Based Charging Method Using the GBO Algorithm and Fuzzy Logic in the WRSN for Wireless Power Transfer by UAV." Journal of Sensors 2023 (May 2, 2023): 1–19. http://dx.doi.org/10.1155/2023/6326423.
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An extremely high number of geographically dispersed, energy-limited sensor nodes make up wireless sensor networks. One of the critical difficulties with these networks is their network lifetime. Wirelessly charging the sensors continuously is one technique to lengthen the network’s lifespan. In order to compensate for the sensor nodes’ energy through a wireless medium, a mobile charger (MC) is employed in wireless sensor networks (WRSN). Designing a charging scheme that best extends the network’s lifetime in such a situation is difficult. In this paper, a demand-based charging method using unmanned aerial vehicles (UAVs) is provided for wireless rechargeable sensor networks. In this regard, first, sensors are grouped according to their geographic position using the K-means clustering technique. Then, with the aid of a fuzzy logic system, these clusters are ranked in order of priority based on the parameters of the average percentage of battery life left in the sensor nodes’ batteries, the number of sensors, and critical sensors that must be charged, and the distance between each cluster’s center and the MC charging station. It then displays the positions of the UAV to choose the crucial sensor nodes using a routing algorithm based on the shortest and most vital path in each cluster. Notably, the gradient-based optimization (GBO) algorithm has been applied in this work for intracluster routing. A case study for a wireless rechargeable sensor network has been carried out in MATLAB to assess the performance of the suggested design. The outcomes of the simulation show that the suggested technique was successful in extending the network’s lifetime. Based on the simulation results, compared to the genetic algorithm, the proposed algorithm has been able to reduce total energy consumption, total distance during the tour, and total travel delay by 26%, 17.2%, and 25.4%, respectively.
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Bao, Xi Rong, Yue Huang, and Shi Zhang. "A Distributed Motion Algorithm for Mobile Sensor in Hybrid Wireless Sensor Networks." Applied Mechanics and Materials 719-720 (January 2015): 812–17. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.812.
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Constructing a hybrid wireless sensor networks comprising a mix of static sensors and mobile sensors can achieve a balance between improving coverage and reducing the cost of the network. In order to achieve high network coverage, mobile sensor move from a small to a big size of coverage hole in the hybrid wireless sensor networks. Due to the energy of the mobile sensor is limited, how to reduce the moving distance of the mobile sensor and reduce the energy consumption in the process of moving is a very important issue. This paper proposes a distributed minimum cost matching algorithm (DMMA) to redeploy mobile sensor, which can make the level of network coverage to meet the requirement of the environment, while effectively reducing the number of sensors. In our method, static sensors detect coverage hole by Voronoi diagrams, coverage holing sensors and mobile sensors by using DMMA to excellently heal the large coverage holes. Simulation results show that our method can effectively improve the coverage rate of the WSNs, while save the energy of mobile sensors.
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Chen, Tzung-Shi, Jen-Jee Chen, Xiang-You Gao, and Tzung-Cheng Chen. "Mobile Charging Strategy for Wireless Rechargeable Sensor Networks." Sensors 22, no. 1 (January 4, 2022): 359. http://dx.doi.org/10.3390/s22010359.
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In a wireless sensor network, the sensing and data transmission for sensors will cause energy depletion, which will lead to the inability to complete the tasks. To solve this problem, wireless rechargeable sensor networks (WRSNs) have been developed to extend the lifetime of the entire network. In WRSNs, a mobile charging robot (MR) is responsible for wireless charging each sensor battery and collecting sensory data from the sensor simultaneously. Thereby, MR needs to traverse along a designed path for all sensors in the WRSNs. In this paper, dual-side charging strategies are proposed for MR traversal planning, which minimize the MR traversal path length, energy consumption, and completion time. Based on MR dual-side charging, neighboring sensors in both sides of a designated path can be wirelessly charged by MR and sensory data sent to MR simultaneously. The constructed path is based on the power diagram according to the remaining power of sensors and distances among sensors in a WRSN. While the power diagram is built, charging strategies with dual-side charging capability are determined accordingly. In addition, a clustering-based approach is proposed to improve minimizing MR moving total distance, saving charging energy and total completion time in a round. Moreover, integrated strategies that apply a clustering-based approach on the dual-side charging strategies are presented in WRSNs. The simulation results show that, no matter with or without clustering, the performances of proposed strategies outperform the baseline strategies in three respects, energy saving, total distance reduced, and completion time reduced for MR in WSRNs.
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Semnani, Samaneh Hosseini, and Otman A. Basir. "Multi-Target Engagement in Complex Mobile Surveillance Sensor Networks." Unmanned Systems 05, no. 01 (January 2017): 31–43. http://dx.doi.org/10.1142/s2301385017500030.
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Efficient use of the network’s resources to collect information about objects (events) in a given volume of interest (VOI) is a key challenge in large-scale sensor networks. Multi-sensor multi-target tracking in surveillance applications is an example where the network’s success in tracking targets, efficiently and effectively, hinges significantly on the network’s ability to allocate the right set of sensors to the right set of targets so as to achieve optimal performance which minimizes the number of uncovered targets. This task can be even more complicated when both the sensors and the targets are mobile. To ensure timely tracking of mobile targets, the surveillance sensor network needs to perform the following tasks in real-time: (i) target-to-sensor allocation; (ii) sensor mobility control and coordination. The computational complexity of these two tasks presents a challenge, particularly in large scale dynamic network applications. This paper proposes a formulation based on the Semi-flocking algorithm and the distributed constraint optimization problem (DCOP). The semi-flocking algorithm performs multi-target motion control and coordination, a DCOP modeling algorithm performs the target engagement task. As will be demonstrated experimentally in the paper, this algorithmic combination provides an effective approach to the multi-sensor/multi-target engagement problem, delivering optimal target coverage as well as maximum sensors utilization.
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Chaczko, Zenon, Christopher Chiu, Shahrzad Aslanzadeh, and Toby Dune. "Sensor-Actor Network Solution for Scalable Ad-hoc Sensor Networks." International Journal of Electronics and Telecommunications 58, no. 1 (March 1, 2012): 55–62. http://dx.doi.org/10.2478/v10177-012-0008-4.
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Sensor-Actor Network Solution for Scalable Ad-hoc Sensor NetworksArchitects of ad-hoc wireless Sensor-Actor Networks (SANETS) face various problems and challenges. The main limitations relate to aspects such as the number of sensor nodes involved, low bandwidth, management of resources and issues related to energy management. In order for these networks to be functionally proficient, the underlying software system must be able to effectively handle unreliable and dynamic distributed communication, power constraints of wireless devices, failure of hardware devices in hostile environments and the remote allocation of distributed processing tasks throughout the wireless network. The solution must be solved in a highly scalable manner. This paper provides the requirements analysis and presents the design of a software system middleware that provides a scalable solution for ad-hoc sensor network infrastructure made of both stationary and mobile sensors and actuators.
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Ye, Chunxuan, Zinan Lin, Alpaslan Demir, and Yan Li. "Performance Analysis of Different Types of Sensor Networks for Cognitive Radios." Journal of Electrical and Computer Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/632762.
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We consider the problem of using multiple sensors to detect whether a certain spectrum is occupied or not. Each sensor sends its spectrum sensing result to a data fusion center, which combines all the results for an overall decision. With the existence of wireless fading on the channels from sensors to data fusion center, we examine three different mechanisms on the transmissions from sensors to data fusion center: (1) direct transmissions; (2) transmissions with the assistance of relays and (3) transmissions with the assistance of an intermediate fusion helper which fuses the sensing results from the sensors and sends the fused result to the data fusion center. For each mechanism, we analyze the correct probability of the overall decision made by the data fusion center. Our evaluation establishes that a sensor network with an intermediate fusion helper performs almost as good as a sensor network with relays, but providing energy and spectral advantages. Both networks significantly outperform the sensor network without relay or intermediate fusion helper. Such analysis facilitates the design of sensor networks. Furthermore, we generalize this evaluation to sensor networks with an arbitrary number of sensors and to sensor networks applying various information combining rules. Our simulations validate the analytical results.
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Ma, Rui, Yan Cheng Liu, and Chuan Wang. "A Novel Algorithm to Improve Network Lifetime of Wireless Sensor Networks." Applied Mechanics and Materials 433-435 (October 2013): 599–602. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.599.
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One approach to extend the network lifetime is to divide the deployed sensors into disjoint subsets of sensors, or sensor covers, such that each sensor cover can cover all targets and work by turns. The more sensor covers can be found, the longer sensor network lifetime can be prolonged.This study propose a novel hybrid genetic algorithm (NHGA) comprising both basic generic operations with a fitness-improving local-search strategy to divide all wireless sensor nodes into a maximum number of disjoint set covers (DSCs). The simulation results show that NHGA outperforms the existing methods by generating more disjoint set covers and prolongs network lifetime.
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Khaytbaev, A. E., and A. M. Eshmuradov. "APPLICATIONS OF NEURAL NETWORK TECHNOLOGIES IN WIRELESS SENSOR NETWORKS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 195 (September 2020): 46–51. http://dx.doi.org/10.14489/vkit.2020.09.pp.046-051.
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The purpose of the article is to study the possibilities of improving the efficiency of the sensory network management technique, using the neural network method. The presented model of the wireless sensor network takes into account the charging of the environment. The article also tests the hypothesis of the possibility of organizing distributed computing in wireless sensor networks. To achieve this goal, a number of tasks are allocated: review and analysis of existing methods for managing BSS nodes; definition of simulation model components and their properties of neural networks and their features; testing the results of using the developed method. The article explores the major historical insights of the application of the neural network technologies in wireless sensor networks in the following practical fields: engineering, farming, utility communication networks, manufacturing, emergency notification services, oil and gas wells, forest fires prevention equipment systems, etc. The relevant applications for the continuous monitoring of security and safety measures are critically analyzed in the context of the relevancy of specific decisions to be implemented within the system architecture. The study is focused on the modernization of methods of control and management for the wireless sensor networks considering the environmental factors to be allocated using senor systems for data maintenance, including the information on temperature, humidity, motion, radiation, etc. The article contains the relevant and adequate comparative analysis of the updated versions of node control protocols, the components of the simulation model, and the control method based on neural networks to be identified and tested within the practical organizational settings.
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Khaytbaev, A. E., and A. M. Eshmuradov. "APPLICATIONS OF NEURAL NETWORK TECHNOLOGIES IN WIRELESS SENSOR NETWORKS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 195 (September 2020): 46–51. http://dx.doi.org/10.14489/vkit.2020.09.pp.046-051.
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The purpose of the article is to study the possibilities of improving the efficiency of the sensory network management technique, using the neural network method. The presented model of the wireless sensor network takes into account the charging of the environment. The article also tests the hypothesis of the possibility of organizing distributed computing in wireless sensor networks. To achieve this goal, a number of tasks are allocated: review and analysis of existing methods for managing BSS nodes; definition of simulation model components and their properties of neural networks and their features; testing the results of using the developed method. The article explores the major historical insights of the application of the neural network technologies in wireless sensor networks in the following practical fields: engineering, farming, utility communication networks, manufacturing, emergency notification services, oil and gas wells, forest fires prevention equipment systems, etc. The relevant applications for the continuous monitoring of security and safety measures are critically analyzed in the context of the relevancy of specific decisions to be implemented within the system architecture. The study is focused on the modernization of methods of control and management for the wireless sensor networks considering the environmental factors to be allocated using senor systems for data maintenance, including the information on temperature, humidity, motion, radiation, etc. The article contains the relevant and adequate comparative analysis of the updated versions of node control protocols, the components of the simulation model, and the control method based on neural networks to be identified and tested within the practical organizational settings.
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Wayzani, Sarah, and Chérif Diallo. "SPEEDA: A Secure Protocol and Energy Efficient for Data Aggregation in Wireless Sensor Networks." International Journal of Engineering & Technology 7, no. 4.20 (November 28, 2018): 598. http://dx.doi.org/10.14419/ijet.v7i4.20.27422.
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Wireless Sensor Networks (WSN) consists of a set of small and resources-constrained devices. They have received much attention over the last few years for the study and development of a plethora of potential applications. However, the common denominator of all applications of these sensor networks is the vulnerability of micro-sensors because of their limited material resources the most constraining of which is energy. In fact, wireless sensors are limited in terms of calculation, storage, battery, etc. Therefore, every possible solution that aims to conserve these resources is extensively sought. Thus, a great deal of researches has been conducted leading to an effective technique answering the established problem. This solution concerns the aggregation of data which is one of the techniques that is actually considered as an essential paradigm for sensor networks since it tends to save computation and communication resources. Data aggregation allows in-network processing which leads to lesser packet transmissions and reduces redundancy, and therefore, helps in increasing network’s overall lifetime. However, sensor networks are usually deployed in unattended and hostile environments.Thus, the designer should not only consider the limited resources of the sensor nodes but also the security threats that can occur in an easily accessible network to the attacker. In this paper, we will give an overview study of the existing data aggregation solutions in wireless sensor networks then, we will propose a new efficient and secure approach to aggregation which can be evaluated with specific criteria.
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Dadhirao, Chandrika, and Ravi Sankar Sangam. "Attenuate the Network Lifetime in Wireless Sensor Networks." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 12 (December 31, 2022): 59–64. http://dx.doi.org/10.17762/ijritcc.v10i12.5886.
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Wireless Sensor Networks are one of the well-established and as well as im- proving areas, which have a prominent role in many existing technologies. The day-to-day advancement in this field made a direction for growing low-power, low-cost, along with multi functioning of the sensors. This collective formation of the system with motes or sensors is Wireless Sensor Network (WSN). WSNs follow the principle of ”EAAs” stands for Everyone, Anywhere, Anytime. The nodes in the network have certain limitations in terms of memory, power, etc. Clustering the nodes in the network is an efficient and most preferable technique to address the problem of better performance of the wireless sensor networks. In this work, we provide a re-modified approach for cluster head selection for the transmission of data between nodes, cluster heads, and mote with a low packet loss ratio. The Statistical results of the two existing approaches and the pro- posed approach are compared for 100 iterations and shown in results. The time complexity of the proposed approach is also calculated.
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Basaligheh, Parvaneh. "Optimal Coverage in Wireless Sensor Network using Augmented Nature-Inspired Algorithm." International Journal on Future Revolution in Computer Science & Communication Engineering 8, no. 2 (June 30, 2022): 71–78. http://dx.doi.org/10.17762/ijfrcsce.v8i2.2082.
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One of the difficult problems that must be carefully considered before any network configuration is getting the best possible network coverage. The amount of redundant information that is sensed is decreased due to optimal network coverage, which also reduces the restricted energy consumption of battery-powered sensors. WSN sensors can sense, receive, and send data concurrently. Along with the energy limitation, accurate sensors and non-redundant data are a crucial challenge for WSNs. To maximize the ideal coverage and reduce the waste of the constrained sensor battery lifespan, all these actions must be accomplished. Augmented Nature-inspired algorithm is showing promise as a solution to the crucial problems in “Wireless Sensor Networks” (WSNs), particularly those related to the reduced sensor lifetime. For “Wireless Sensor Networks” (WSNs) to provide the best coverage, we focus on algorithms that are inspired by Augmented Nature in this research. In wireless sensor networks, the cluster head is chosen using the Diversity-Driven Multi-Parent Evolutionary Algorithm. For Data encryption Improved Identity Based Encryption (IIBE) is used. For centralized optimization and reducing coverage gaps in WSNs Time variant Particle Swarm Optimization (PSO) is used. The suggested model's metrics are examined and compared to various traditional algorithms. This model solves the reduced sensor lifetime and redundant information in Wireless Sensor Networks (WSNs) as well as will give real and effective optimum coverage to the Wireless Sensor Networks (WSNs).
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Jurenoks, Aleksejs, and Leonids Novickis. "Wireless sensor networks lifetime assessment model development." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (June 16, 2015): 121. http://dx.doi.org/10.17770/etr2015vol3.508.
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<p class="R-AbstractKeywords"><span lang="EN-US">In the recent years low power computing systems have gained popularity. Networks, which use low power computer systems and transmitted data by using wireless connection are called wireless sensor networks, which main task is to get the information from sensors and transmission network. Nowadays, the most topical researches pertaining to wireless sensor networks are grounded on the new optimization of structure of network transmission protocol, the routing optimization in transmission network, optimization of network structure, as a result of which the life circle of wireless network sensors is possible to increase. In the present article the methodology for determining the life circle of network is discussed. The approaches in detection of life circle pertaining to the important network nodes are described.</span></p>
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Aloimonos, Yiannis. "Sensory grammars for sensor networks." Journal of Ambient Intelligence and Smart Environments 1, no. 1 (2009): 15–21. http://dx.doi.org/10.3233/ais-2009-0002.
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Singh, Mitali, and Viktor K. Prasanna. "A HIERARCHICAL MODEL FOR DISTRIBUTED COLLABORATIVE COMPUTATION IN WIRELESS SENSOR NETWORKS." International Journal of Foundations of Computer Science 15, no. 03 (June 2004): 485–506. http://dx.doi.org/10.1142/s012905410400256x.
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In-network collaborative computation is essential for implementation of a large number of sensor applications. We approach the problem of computation in sensor networks from a parallel and distributed system's perspective. We define COSMOS, the Cluster-based, heterOgeneouSMOdel for Sensor networks. The model abstracts the key features of the class of cluster-based sensor applications. It assumes a hierarchical network architecture comprising of a large number of low cost sensors with limited computation capability, and fewer number of powerful clusterheads, uniformly distributed in a two dimensional terrain. The sensors are organized into single hop clusters, each managed by a distinct clusterhead. The clusterheads are organized in a mesh-like topology. All sensors in a cluster are time synchronized, whereas the clusterheads communicate asynchronously. The sensors are assumed to have multiple power states and a wakeup mechanism to facilitate power management. To illustrate algorithm design using our model, we discuss implementation of algorithms for sorting and summing in sensor networks.
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Ross-Pinnock, David, Glen Mullineux, and Patrick S. Keogh. "Temperature Sensor Position Planning." Journal of Integrated Design and Process Science 24, no. 3-4 (April 11, 2022): 65–94. http://dx.doi.org/10.3233/jid-210025.
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One of the challenges in large volume metrology is that it is often difficult or impossible to control the ambient conditions in which the object is to be measured. Dimensional measurement results vary with those conditions and it becomes necessary to apply some form of compensation. Thermal compensation of dimensional measurement is primarily reliant on the ability to properly measure temperature across the volume, which can differ by several degrees, but conventionally a uniform scaling has been applied. This paper focuses upon temperature sensor network planning improvement to facilitate thermal compensation. Beyond assembly environments, data from sensor networks are increasingly used to make decisions, but appropriate design and testing of such networks can be limited. As the demand for production digital twins increase, appropriate methods to quantify and optimise uncertainty to improve confidence will be invaluable. A virtual test bed has been created for the design, test, and optimisation of temperature sensor networks supported by physical simulation. Sensor networks have been used to take virtual measurements from a known temperature distribution and used to reconstruct the temperature distribution. Random search optimisation on a subset of the sensor network was carried out to determine some initial rules for sensor network design. The positioning of the sensors within the measurement volume and the method of reconstructing the temperature field was found to be more important than the capability of the individual sensors. Two means of interpolating the ambient field have been investigated: polynomial fitting and kriging. Temperature sensor networks appeared more sensitive to changes at the spatial boundary and these positions seem to be most critical for accurate reconstruction. In the case of the barrel section assembly it was found that asymmetric sensor heights produced better results, for example. A polynomial interpolation model using a 16-sensor network with 0.1 °C (confidence interval, k = 2) uncertainty sensors could produce a consistent temperature reconstruction error of ~0.04 °C RMS, corresponding to a thermal expansion error of ~1.5 μm in aluminium over a 1.6 m-tall structure.
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Bouakkaz, Fatima, Wided Ali, and Makhlouf Derdour. "Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression." Instrumentation Mesure Métrologie 20, no. 1 (February 28, 2021): 57–63. http://dx.doi.org/10.18280/i2m.200108.
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Recently, the issue of multimedia sensors received considerable critical attention, that led to the apparition of Wireless Multimedia Sensor Networks (WMSNs) WMSN that different from wireless sensor networks (WSN) by using multimedia sensors that can process video, audio, image data besides scalar data and send it to station base (SB). Multimedia data have a big volume bigger than scalar data and need more resources and consumed more energy. The ideal solution to solve the problems of WMSN (big volume, energy consumption) is data compression. Forest plays a critical role in our daily life we can summarize the importance of forests in human life. Among the most dangerous events the forest fires that happen because of natural or Man-made. Many methods used to detect forest fires the newest are: wireless multimedia sensor networks. Our system of detecting forest fire has been developed using a wireless multimedia senor network with two types of sensors (scalar, images). In the first phase when the scalar sensors detected a high temperature its announced alarm to activate the image sensors. In the second phase for detecting fire the image sensors, we used image processing tools. When the zone of fire in the image captured was detected the phase of compression started using the down sampling method. the final phase is transmission data to the station base using the grid chain transmission protocol technique, which allows a critical optimization of energy consumption. So, maximizing network life. The competence of the proposed system is achieved by minimizing size of image transmitted with grid chain routing protocol.
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Hung, Li-Ling. "Charging Protocol for Partially Rechargeable Mobile Sensor Networks." Sensors 23, no. 7 (March 24, 2023): 3438. http://dx.doi.org/10.3390/s23073438.
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Wireless sensor networks (WSNs) have wide applicability in services used in daily life. However, for such networks, limited energy is a critical issue. The efficiency of a deployed sensor network may be subject to energy supply. Wireless rechargeable sensor networks have recently been proposed and discussed. Most related studies have involved applying static rechargeable sensors to an entire rechargeable environment or having mobile chargers patrol the environment to charge sensors within it. For partially rechargeable environments, improving the recharge efficiency and extending the lifetime of WSNs are considerable challenges. Scientists have devoted attention to energy transmission technologies and mobile sensor network (MSN) applications. In this paper, we propose a flexible charging protocol in which energy can be transmitted from certain energy supply regions to other regions in an MSN. Mobile rechargeable sensors are deployed to monitor the environment. To share energy in a certain region, the sensors move to replenish their energy and transmit energy to sensors outside the energy supply region. The efficiency of the proposed protocol is also discussed in the context of various situations. The evaluation results suggest that the flexible protocol is more efficient than other charging protocols in several situations.
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Luo, Xu, and Jun Yang. "A Survey on Pollution Monitoring Using Sensor Networks in Environment Protection." Journal of Sensors 2019 (January 14, 2019): 1–11. http://dx.doi.org/10.1155/2019/6271206.
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Detecting pollution timely and locating the pollution source is of great importance in environmental protection. Considering advantages of the sensor network technology, sensor networks have been adopted in pollution monitoring works. In this paper, a survey on researches of pollution monitoring using sensor networks in environment protection is given. Firstly, sensors and pollution monitoring network systems are studied. Secondly, different pollution detection methods are analyzed and compared. Thirdly, an overview of state-of-art technologies on pollution source localization is given. Finally, challenges on pollution monitoring using sensor networks are presented.
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Kohli, Sheena. "Sensor Hop-based Energy Efficient Networking Approach for Routing in Underwater Acoustic Communication." Journal of Telecommunications and Information Technology, no. 1 (March 30, 2017): 44–49. http://dx.doi.org/10.26636/jtit.2017.1.649.
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Underwater Wireless Sensor Networks are deployed to explore the world under the water, measure different parameters and communicate the data to the surface, in the widespread applications. The main operating technology of these networks is the acoustic communication. The communication among the sensors and finally to the surface station requires a routing protocol. The sensors being battery limited and unfeasible to be replaced under the water requires an energy efficient routing protocol. Clustering imparted in routing is an energy saving technique in sensor networks. The routing may involve single or multi hop communication in the sensor networks. The paper gives a comparative study of the benchmark protocol multi-hop LEACH with the proposed Sensor Hop-based Energy Efficient Networking Approach (SHEENA) for the shallow as well as deep water in three dimensional Underwater Wireless Sensor Networks. The network energy model for the Underwater Wireless Sensor Networks is based among the different acoustic channel characteristics. The proposed approach is found to give better response.
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Lee, Chao Yang, Fu Tian Lin, and Chu Sing Yang. "Mobile Sensor Navigation in Wireless Hybrid Sensor Networks." Advanced Materials Research 694-697 (May 2013): 1013–16. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1013.
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With recent advances in mobile platforms, hybrid sensor networks are becoming very popular technology. Mobile sensors can dynamically move to monitor uncovered areas and thus improve the coverage quality. Due to the obstacles may exist in the monitor fields, mobile sensors need to find an obstacle-free moving path for mobile sensor movement. However, in practical, sensors are difficult to obtain the geographic information of obstacles. Additionally, sensors have resource constraints. Hence, this work proposed an obstacle-free and geographic-free dispatch scheme (OGDS) for mobile sensor navigation with low computational complexity. The moving path for mobile sensor dispatch has obtained by using the Dynamic Source Routing protocol (DSR) protocol. Experimental results reveal that the proposed scheme can be efficiently executed.
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Paliwal, Rakesh, and Irfan Khan. "Design and Analysis of Soft Computing Based Improved Routing Protocol in WSN for Energy Efficiency and Lifetime Enhancement." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 3 (April 13, 2022): 12–24. http://dx.doi.org/10.17762/ijritcc.v10i3.5521.
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Mobile wireless sensor networks have been developed as a result of recent advancements in wireless technologies. Sensors in the network are low-cost and have a short battery life, in addition to their mobility. They are more applicable in terms of the essential properties of these networks. These networks have a variety of uses, including search and rescue operations, health and environmental monitoring, and intelligent traffic management systems, among others. According to the application requirements, mobile wireless sensor nodes are energy limited equipment, so energy conservation is one of the most significant considerations in the design of these networks. Aside from the issues posed by sensor node mobility, we should also consider routing and dynamic clustering. According to studies, cluster models with configurable parameters have a substantial impact on reducing energy usage and extending the network's lifetime. As a result, the primary goal of this study is to describe and select a smart method for clustering in mobile wireless sensor networks utilizing evolutionary algorithms in order to extend the network's lifetime and ensure packet delivery accuracy. For grouping sensor nodes in this work, the Genetic Algorithm is applied initially, followed by Bacterial Conjugation. The simulation's results show a significant increase in clustering speed acceleration. The speed of the nodes is taken into account in the suggested approach for calibrating mobile wireless sensor nodes.
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Pethe, Rahul, and Aachal Pethe. "Analysis of Life Time Improvement Energy Efficient Risk-Free Protocol (ERP) for Data Transmission in Wireless Sensor Networks." Journal of Power Electronics and Devices 9, no. 1 (February 23, 2023): 6–11. http://dx.doi.org/10.46610/joped.2023.v09i01.001.
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Recently, wireless sensor networks (WSNs) have come to be seen as the fundamental architecture that paved the way for the development of the Internet of Things (IoT). However, a challenging problem develops when WSNs are connected to the IoT because of their nodes' high energy consumption and low network lifetime. As a result, the core concepts of WSNs include energy limits in sensor nodes, sensor data exchange, and routing protocols. The enhanced smart-energy-efficient routing protocol (ESEERP) presented in this study addresses the aforementioned shortcomings by extending the network's lifespan and enhancing connectivity. Since the Internet of Things (IoT) demands a significant amount of energy for sensing, processing, and data transport, the IoT application in wireless sensor networks (WSNs) poses substantial issues in maintaining network durability. As a result, multiple traditional algorithms incorporate different optimization techniques to improve the performance of WSN networks. We utilize IPv4 in wireless sensor networks to transmit data (packets), however, this strategy prevents users from accessing big amounts of data over long distances since it may need a lot of power to transmit large amounts of data using IPv4. The Internet of Things (IoT) can be used to solve this problem because it connects small battery-operated devices like sensors as well as consumer electronics and home appliances. One of the most often utilised wireless methods for sensor network connectivity is the IEEE 802.11 standard.
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Khalid, Muhammad, Zahid Ullah, Naveed Ahmad, Muhammad Arshad, Bilal Jan, Yue Cao, and Awais Adnan. "A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks." Journal of Sensors 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/7539751.
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Underwater wireless sensor networks are a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in the area of underwater wireless sensor networks have also been discussed.
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Kaur, Simerpreet, Md Ataullah, and Monika Garg. "Security from Denial of Sleep Attack in Wireless Sensor Network." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (August 30, 2005): 419–25. http://dx.doi.org/10.24297/ijct.v4i2b1.3230.
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With the advancement in Wireless Sensor Network (WSN) sensors are gaining importance in the physical world. Besides the low power of sensor nodes used, sensors are widely used in detecting temperature, pollution, pressure and other various applications. Energy-constrained sensor networks periodically place nodes to sleep in order to extend the network Lifetime. Denial of sleep attacks are a great threat to lifetime of sensor networks as it prevents the nodes from going into sleep mode. In this paper we are describing prevention against Denials of sleep attack. We have analyzed each of proposed solutions, identify their strengths and limitations.
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Ahmed, Mohammed M. "SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network." Indian Journal of Data Communication and Networking 1, no. 2 (April 10, 2021): 16–20. http://dx.doi.org/10.35940/ijdcn.b5006.041221.
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In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node location we create transmission paths between the sink node and rest of nodes using Prim's minimum spanning tree to choose shortest paths. Accordingly, for fitness function that used to decrease energy consumption for a network. Simulation results clarify that our proposed algorithm that solves localization of sink node presents the best results for prolonging the network's lifetime compared to Cat Swarm Optimization algorithm (CSA) and Particle Swarm Optimization (PSO).
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Ahmed, Mohammed M. "SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network." Indian Journal of Data Communication and Networking 1, no. 2 (April 10, 2021): 16–20. http://dx.doi.org/10.54105/ijdcn.b5006.041221.
Full textAbstract:
In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node location we create transmission paths between the sink node and rest of nodes using Prim’s minimum spanning tree to choose shortest paths. Accordingly, for fitness function that used to decrease energy consumption for a network. Simulation results clarify that our proposed algorithm that solves localization of sink node presents the best results for prolonging the network’s lifetime compared to Cat Swarm Optimization algorithm (CSA) and Particle Swarm Optimization (PSO).
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Luo, Xin-long, Wei Li, and Jia-ru Lin. "Geometric Location Based on TDOA for Wireless Sensor Networks." ISRN Applied Mathematics 2012 (January 11, 2012): 1–10. http://dx.doi.org/10.5402/2012/710979.
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Wireless sensor networks (WSNs) consist of a large number of low-cost miniature sensors, which can be applied to battlefield surveillance, environmental monitoring, target tracking, and other applications related to the positions of sensors. The location information of sensors is of great importance for wireless sensor networks. In this paper, we propose a new localization algorithm for the wireless sensor network based on time difference of arrival (TDOA), which is a typical algorithm in the wireless localization field. In order to improve the localization accuracy of a sensor, a new strategy is proposed for a localized sensor being upgraded to an anchor node, which is used to localize the position of the next sensor. Performance analysis and simulation results show that the revised TODA localization algorithm has the higher localization accuracy when compared with the original TDOA location method.
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Mi, Zhenqiang, Rong-Shue Hsiao, Zenggang Xiong, and Yang Yang. "Graph-Theoretic Based Connectivity Restoration Algorithms for Mobile Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/404651.
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In mobile sensor networks (MSN), actuated sensors collaborate with each other in some predefined missions. The collaboration requires application-level coordination based on a strongly connected underlying network, which is often in an infrastructure-free ad hoc manner. The particular network topology provides flexibility as well as vulnerability to the potential applications of MSN; for example, the connectivity can be easily jeopardized if the network is partitioned into disjoint segments from the failure of some critical sensors. In this paper, a critical sensor determination and substitution (CSDS) strategy is proposed to address the important problem of network partitions in mobile sensor networks (MSN) due to the failure of particular sensors. CSDS utilizes a graph-theoretic method to locally identify critical sensors with 2-hop neighboring information. Then, an efficient backup sensor selection algorithm is proposed to monitor the critical sensors and, if necessary, substitute it in order to eliminate the partitions in MSN. The main contribution of our proposed work is that CSDS requires the relocation of only one sensor in each partition elimination process, so that the impacts on the primary missions of the MSN are minimized. Experimental simulations are conducted to evaluate the correctness and effectiveness of CSDS.
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Mishra, Saurabh, Prof Rakesh Ranjan, Dr Sonika Singh, and Dr Gagan Singh. "Performance Analysis of MIMO Heterogeneous Wireless Sensor Networks." International Journal of Innovative Technology and Exploring Engineering 12, no. 12 (November 30, 2023): 25–31. http://dx.doi.org/10.35940/ijitee.l9742.11121223.
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Wireless Sensor Networks (WSN) are widely used in remote applications related to defence and healthcare. A network with nodes having different capabilities like sensing, various computational capabilities, power-efficient communication, and a varied sensing range is called a heterogeneous wireless sensor network. Heterogeneous wireless sensor networks using MIMO wireless channels are more useful for energy-efficient multi-channel communication. MIMO applications in wireless sensor networks have the potential to enhance throughput, reduce End-to-End Delay, improve packet delivery ratios, and conserve energy in wireless sensor networks. Its implementation needs to be carefully considered in light of the specific deployment conditions and resource constraints of the network, considering proper antenna design, synchronisation mechanisms, and energy-efficient algorithms. This paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO for various Quality of Service parameters like Packet Delivery Ratio, End to End Delay, Throughput and Residual energy. The research work shows that the application of MIMO in Wireless Sensor Networks enables sensor nodes to collaborate effectively, leading to improved reliability and coverage, and also increases the network's lifetime by conserving energy in resource-constrained sensor nodes through the preservation of Residual Energy.
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Qu, Ming Zhe. "Research on the Applications and Characteristics of the Wireless Sensor Network." Applied Mechanics and Materials 538 (April 2014): 498–501. http://dx.doi.org/10.4028/www.scientific.net/amm.538.498.
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A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The more modern networks are bi-directional, also enabling control of sensor activity. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on. The WSN is built of "nodes" – from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting.
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Bendjima, Mostefa, and Mohammed Feham. "Intelligent Communication in Wireless Sensor Networks." Future Internet 10, no. 9 (September 15, 2018): 91. http://dx.doi.org/10.3390/fi10090091.
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Wireless sensor networks (WSN) are designed to collect information by means of a large number of energy-limited battery sensor nodes. Therefore, it is important to minimize the energy consumed by each sensor, in order to extend the network life. The goal of this work is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent is sent to each sensor in order to process the information and to cooperate with neighboring sensors while mobile agents (MA) can be used to reduce information shared between source nodes (SN) and send them to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the multi-agent system (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the sensors of the network have been grouped into sectors. For each MA, we have established an optimal itinerary, consuming a minimum amount of energy with data aggregation efficiency in a minimum time. Successive simulations in large-scale wireless sensor networks through the SINALGO (published under a BSD license) simulator show the performance of the proposed method, in terms of energy consumption and package delivery rate.
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Ramezani, Tayebeh, and Tahereh Ramezani. "A Distributed Method to Reconstruct Connection in Wireless Sensor Networks by Using Genetic Algorithm." Modern Applied Science 10, no. 6 (April 10, 2016): 50. http://dx.doi.org/10.5539/mas.v10n6p50.
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In recent years most of the research in the field of sensor networks is allocated to the wireless sensor and actor networks due to their complicacy and vastness of research area. This type of network is a group of sensors and actors wirelessly linked to each other. Sensors gather information of physical world while actors take appropriate decisions on the basis of gathered information and then perform proper actions upon the environment. In wireless sensor and actor networks, it is very important to maintain the connection between actors. Failure of one or more actors can break up the network into separated parts and this failure acts as a barrier to the network to perform its duties. The purpose of the present paper was to provide a genetic algorithm in wireless sensor and actor networks, to improve evaluation and to maintain the connection between actors’ networks. In order to evaluate strong points and weaknesses of the recommended approach, the OMNet++ simulation was used and the outcomes of the simulation were indicative of the recommended approach’s validity.
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Majid, Amir. "Lifetime Extension of Three-Dimensional Wireless Sensor Networks, Based on Gaussian Coverage Probability." Journal Européen des Systèmes Automatisés 54, no. 4 (August 31, 2021): 569–74. http://dx.doi.org/10.18280/jesa.540406.
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The aim of this work is to evaluate the nth joined probability of three-dimensional wireless sensor networks, and to extend the lifetime of these networks. A Gaussian probability distribution function is assumed for the power coverage probability for each sensor in the 3-dimensional cartesian and spherical coordinates. The overall joint probability is evaluated from each sensor to a target in the network, and then the network lifetime of sensors power sensing a number of targets, is extended based on removing redundancies of powering all sensors at the same time. Proportional to the evaluated probabilities, sensors are energized during slots of periodic time. The formulated probabilities are assumed to be uncorrelated among each sensor to any target zone. A case study is introduced to demonstrate extending the lifetime of a network comprising 7 sensors targeting two uncorrelated zones, in which 8 different cases of subsets are formed, when a minimum threshold of overall power coverage probability of 35% is assumed. Network lifetime is extended more than 70%, with some sensors reaching more than 90% power saving. This work can be extended to deal with other types of probabilities, as well as with cases of correlated sensor-target coverages.
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S, Sweta, and Balajee Maram. "Underwater Wireless Sensor Networks." JOIV : International Journal on Informatics Visualization 2, no. 1 (January 5, 2018): 10. http://dx.doi.org/10.30630/joiv.2.1.99.
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There are a plenty of unexploited resources that lies underwater that covers almost 75% of the earth.In order to utilise them,the field of underwater wireless sensor networks (UWSN) is attracting the researchers to extend their thoughts in this field. The wireless sensor networks are heavy networks that consist of small low cost sensors that have a large amount of solving ability and energy resources which can be applicable in any type of irregular environments irrespective of changing conditions. Keeping in view of the real-time remote data transferring requirements, underwater acoustic sensor networks (UASN) has been recognised as a preferred network because it satisfies all aspects of data transfer. In UASN, the required availability and recycling of energy resources along with specified utilisation of data with the help of utilized sensor nodes for energy requirements that are necessary are done for the development of further theories in these contexts. Due to these causes, the maximum underwater resources utilisation techniques mainly depends on UAN (Underwater Acoustic Networks).Underwater wireless sensor networks (UWSNs) suitable for applications on submarine detection and monitoring,where nodes collect data with a mobile autonomous underwater vehicle (AUV) via optical communications, and applied accordingly to deal with further approaches. They provide continuous monitoring for various applications like ocean sampling network, pollution monitoring, submarine detection, disaster prevention etc.This paper particularly deals with a brief collection of the UWSN applications and some of the algorithms for the path finding in order to pass maximum valued information(VOI) among the different nodes.
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Kaur, Rashmeet, Amit Gupta, and Rakesh Goyal. "Analysis of Coverage Hole Problem for Detection and Restoration in Wireless Sensor Networks." Advanced Science, Engineering and Medicine 12, no. 3 (March 1, 2020): 403–8. http://dx.doi.org/10.1166/asem.2020.2537.
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Wireless Sensor Network is an evolving technology which has gained massive attention in the past few years. Researchers are focusing on designing the wireless sensors more and more intelligent and efficient to make our life extremely comfortable and luxurious. Wireless Sensor Networks are used in bridge monitoring, smart agriculture, health care monitoring, landslide detection, biodiversity mapping, etc. Coverage holes are one of the key problems which occur in the Wireless Sensor Network accidentally and they cannot be neglected. The coverage holes appear in the sensing field due to poor instalment, node failure, battery depletion, etc. In this paper, detection and restoration method based on Hybrid Wireless Sensor Networks and Static Wireless Sensor Networks are discussed. Further, we have analysed the performances of these networks using Unequal Clustering and Connected Graphand Novel Energy Efficient Clustering Protocol techniques. The simulation results revealed that for Hybrid Wireless Sensor Networks, Unequal Clustering and Connected Graph protocol is best suitable and for Static Wireless Sensor Networks, Novel Energy Efficient Clustering Protocoltechnique will be preferred.
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Kusuma, S. M., K. N. Veena, B. P. Vijaya Kumar, and B. V. Varun. "Performance Modeling of Energy Efficiency for Sensors Deployment in Embedded Wireless Sensor Networks." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4515–24. http://dx.doi.org/10.1166/jctn.2020.9107.
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Present trend of Internet of Things (IoT) and sensors deployment increased in every sectors enormously from last one decade. But the deployment challenges of sensors and their networks with respect to their contextual dynamics and system performance is not much investigated. Hence there is a need to investigate the deployment challenges of sensors supporting the computing system that exactly imitates the phenomenon by understanding the context and other influencing parameters, i.e., to sense the environmental parameter values accurately and precisely from the respective embedded sensor system. In this paper, a methodology is proposed to analyze the performance of embedded Wireless Sensor Networks (eWSNs) with respect to energy efficiency based on sensors deployment. The method involves in clustering the sensor nodes based on distance from the phenomenon and its physical location. Sensors and sensor network lifetime energy consumption for data acquisition is analyzed using Markovian model. Simulation platform for random deployment of sensor nodes along with Self Organizing map neural network for clustering with various cases of sensors deployment, network dynamics and environment are studied to understand the performance of the embedded WSN system for energy efficiency.
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Kaur, Amneet, and Harpreet Kaur. "A REVIEW ON A HYBRID APPROACH USING MOBILE SINK AND FUZZY LOGIC FOR REGION BASED CLUSTERING IN WSN." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 16, no. 2 (March 22, 2017): 7586–90. http://dx.doi.org/10.24297/ijct.v16i2.5999.
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A Wireless Sensor Network or WSN is supposed to be made up of a large number of sensors and at least one base station. The sensors are autonomous small devices with several constraints like the battery power, computation capacity, communication range and memory. They also are supplied with transceivers to gather information from its environment and pass it on up to a certain base station, where the measured parameters can be stored and available for the end user. In most cases, the sensors forming these networks are deployed randomly and left unattended to and are expected to perform their mission properly and efficiently. As a result of this random deployment, the WSN has usually varying degrees of node density along its area. Sensor networks are also energy constrained since the individual sensors, which the network is formed with, are extremely energy-constrained as well. Wireless sensor networks have become increasingly popular due to their wide range of application. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. Minimizing the energy consumption of a wireless sensor network application is crucial for effective realization of the intended application in terms of cost, lifetime, and functionality. However, the minimizing task is hardly possible as no overall energy cost function is available for optimization.
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Vervečka, Martynas. "SENSOR NETWORK DATA FUSION METHODS." Mokslas - Lietuvos ateitis 2, no. 1 (February 28, 2010): 50–53. http://dx.doi.org/10.3846/mla.2010.011.
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Sensor network data fusion is widely used in warfare, in areas such as automatic target recognition, battlefield surveillance, automatic vehicle control, multiple target surveillance, etc. Non-military use example are: medical equipment status monitoring, intelligent home. The paper describes sensor networks topologies, sensor network advantages against the isolated sensors, most common network topologies, their advantages and disadvantages.
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Ashokkumar, Jobanputra Paresh, and Prof Arun Jhapate. "A Review of Sensor Node in Wireless Sensor Networks." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (June 30, 2019): 124–27. http://dx.doi.org/10.31142/ijtsrd23620.
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