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1
Tsvetanov, Filip, and Martin Pandurski. "Efficiency of integration between sensor networks and clouds." International journal of electrical and computer engineering systems 13, no. 6 (2022): 427–33. http://dx.doi.org/10.32985/ijeces.13.6.2.
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Numerous wireless sensor networks (WSN) applications include monitoring and controlling various conditions in the environment, industry, healthcare, medicine, military affairs, agriculture, etc. The life of sensor nodes largely depends on the power supply type, communication ability, energy storage capacity and energy management mechanisms. The collection and transmission of sensor data streams from sensor nodes lead to the depletion of their energy. At the same time, the storage and processing of this data require significant hardware resources. Integration between clouds and sensor networks is an ideal solution to the limited computing power of sensor networks, data storage and processing. One of the main challenges facing systems engineers is to choose the appropriate protocol for integrating sensor data into the cloud structure, taking into account specific system requirements. This paper presents an experimental study on the effectiveness of integration between sensor networks and the cloud, implemented through three protocols HTTP, MQTT and MQTT-SN. A model for studying the integration of sensor network - Cloud with the communication models for integration - request-response and publish- subscribe, implemented with HTTP, MQTT and MQTT-SN. The influence of the number of transmitted data packets from physical sensors to the cloud on the transmitted data delay to the cloud, the CPU and memory load was studied. After evaluating the results of sensor network and cloud integration experiments, the MQTT protocol is the most efficient in terms of data rate and power consumption.
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Bendjima, Mostefa, and Mohammed Feham. "Intelligent Communication in Wireless Sensor Networks." Future Internet 10, no. 9 (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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Zhao, Wei, and Shi Gang. "An Improved MAC Protocol for Wireless Sensor Networks in Medical Application." Applied Mechanics and Materials 236-237 (November 2012): 1020–25. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.1020.
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Wireless Sensor Networks (WSNs) provide a valuable capability to autonomously monitor remote activities. Their limited resources challenge WSN medium access control (MAC) layer designers to adequately support network services while conserving limited battery power. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and self-configuration are primary goals. This paper proposes M-MAC, a medium access control protocol designed for medical wireless sensor networks. M-MAC’s centre management function offers significant energy savings by wiping off contention and keeping nodes sleeping all the time except awaking to send its Data package. All Slave Node(SN) need only communicate with a specific Master Node(MN) in a group and due to close range, routing is unnecessary. The MN acts as scheduler and when receives a Data package from a SN, it will indicate the SN how long it should be asleep and what it should do after awaking. Period is introduced as the time windows and it is divided into Frame Time. Every MN occupies a unique Frame Time and this is decided by its MAC address. Then the Frame Time separates into smaller Slot Time and it is the atomic time span for SN exchanging data with MN. Practice has proved that the M-MAC protocol is effective in our medical application and it can extend the lifetime of SN greatly
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Stojcev, Mile, Ljubisa Golubovic, and Tatjana Nikolic. "Clocks, power and synchronization in duty-cycled wireless sensor nodes." Facta universitatis - series: Electronics and Energetics 24, no. 2 (2011): 183–208. http://dx.doi.org/10.2298/fuee1102183s.
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Recent advances in CMOS VLSI ICs and micro-electromechanical technology have led to development of small, low-cost, and low-power multifunctional sensors. Wireless sensor networks (WSNs) are large-scale networks of such sensors, dedicated to observing and monitoring various aspects of the physical world. Some intrinsic properties of WSNs including limited resource of energy, storage, computation, and bandwidth, make traditional synchronization methods unsuitable for WSNs. Time synchronization as an important issue consists of giving all sensor nodes (SNs) of the WSN a common time scale to operate. The common time scale is usually achieved by periodically synchronizing the clock of each SN to a reference source. In this manner the local time seen by each SN of the network is approximately the same, and time synchronization allows the entire system to cooperate. This paper gives a brief look to the time synchronization problem and the need for synchronization in WSNs. Then it points out that clock systems become a bottle-neck, after that it presents the available current clock technologies, next it examines the influence of these clock technologies, and finally provides guidelines for WSN developers who must choose among the different clock synchronization techniques.
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Kaveri, Kori, and Patil Yogita Dattatraya Prof. "Efficient Routing Technique for Wireless Sensor Networks." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 2399–403. https://doi.org/10.31142/ijtsrd18321.
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A remote sensor arrange has many number of sensors in the parcels which are of various in sizes and they set up in specially appointed or unified association. Each sensor has same measure of detecting capacity which detects all condition parameters like sound, temperature and weight and consolidates or do get together from better places moves to joined data to goal node through group head nodes. A sensor node has essential parts to be specific processor, memory, transmitter, beneficiary, detecting element and authority provide. Besides, a W SN comprises of numerous calculations and conventions and it have the capacity of self sorting out. It is for the most part utilized in military applications, for example, war zone observation, backwoods fire discovery, and modern process checking and agrarian water system administration everywhere human hazard be far above the ground. Kaveri Kori | Prof. Patil Yogita Dattatraya "Efficient Routing Technique for Wireless Sensor Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: https://www.ijtsrd.com/papers/ijtsrd18321.pdf
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Takyu, Osamu, Keiichiro Shirai, Mai Ohta, and Takeo Fujii. "ID Insertion and Data Tracking with Frequency Offset for Physical Wireless Parameter Conversion Sensor Networks." Sensors 19, no. 4 (2019): 767. http://dx.doi.org/10.3390/s19040767.
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As the applications of the internet of things are becoming widely diversified, wireless sensor networks require real-time data reception, accommodation of access from several sensors, and low power consumption. In physical wireless parameter conversion sensor networks (PhyC-SN), all the sensors use frequency shift keying as the modulation scheme and then access the channel to the fusion center, simultaneously. As a result, the fusion center can recognize the statistical tendency of all the sensing results at a time from the frequency spectrum of the received signal. However, the information source, i.e., the sensor, cannot be specified from the received signal because no ID-indicating sensor is inserted to the signal. The data-tracking technique for tracing the time continuity of the sensing results is available for decomposing the sequence of the sensing results per sensor but the error tracking, which is a wrong recognition between the sensing results and the sensor, occurs owing to the similarity of the sensing results. This paper proposes the sensing result separation technique using a fractional carrier frequency offset (CFO) for PhyC-SN. In the proposed scheme, the particular fractional CFO is assigned to each user and it is useful for the ID specifying sensor. The fractional CFO causes inter-carrier interference (ICI). The ICI cancellation of the narrowband wireless communications is proposed. The two types of data-tracking techniques are proposed and are selectively used by the fusion center. Since the proposed data-tracking technique is multi-dimensional, high accuracy of data tracking is achieved even under the similar tendency of the sensing results. Based on computer simulation, we elucidate the advantage of the proposed sensing results separation.
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Shabnam, Kumari, Dalal Sumit, and Rashmi. "A Study on Security in Wireless Sensor Networks." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 477–83. https://doi.org/10.31142/ijtsrd12931.
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Wireless Sensor Networks WSNs present myriad application opportunities for several applications such as precision agriculture, environmental and habitat monitoring, traffic control, industrial process monitoring and control, home automation and mission critical surveillance applications such as military surveillance, healthcare elderly, home monitoring applications, disaster relief and management, fire detection applications among others. Since WSNs are used in mission critical tasks, security is an essential requirement. Sensor nodes can easily be compromised by an adversary due to unique constraints inherent in WSNs such as limited sensor node energy, limited computation and communication capabilities and the hostile deployment environments. Shabnam Kumari | Sumit Dalal | Rashmi "A Study on Security in Wireless Sensor Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd12931.pdf
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Solangi, Shauban Ali, Dil Nawaz Hakro, Muhammad Memon, Khalil-ur-Rehman Khoumbati, and Akhtar Hussain Jalbani. "Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks." Mehran University Research Journal of Engineering and Technology 38, no. 4 (2019): 923–34. http://dx.doi.org/10.22581/muet1982.1904.06.
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WSN (Wireless Sensor Network) comprises of small-sized and constraint-capability SN (Sensor Nodes) which record, send and receive data, sensed to a sink. The network lifetime and energy usability are important challenges to be dealt with. During the working of the SN, the maximum amount of energy is consumed than sensing and processing of data. Therefore, an efficient transmission of the data is required so that the energy can be saved. In this paper, a novel routing and scheduling method for WSNs using GA (Genetic Algorithm) is presented, where the sinks employed on four sides of the sensor field. These sinks collect the data from the SNs having the optimal distance towards the respective sink. The proposed scheme finds the optimized path using GA, during transmission of data from SN to the nearest sink. First, we run the GA for determination of routing paths, where a source SN finds the possible number of optimal hops. Second, the hops or intermediate relay SNs are assumed to relay the data towards the sink, efficiently. The performance is experimented and evaluated using MATLAB R2016b. The simulations have carried out through comparing the proposed scheme with TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol). The results of simulation comprise of 10 and 20 number of SNs, discretely. Additionally, the direct distance of each node is calculated and the distance through multiple hops from/to the nearest sink is also evaluated. The achievements of the proposed technique are to save both energy and distance for the sake of network longevity and optimal and precise data delivery by multiple hops.
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Ayala-Ruiz, Daniel, Alejandro Castillo Atoche, Erica Ruiz-Ibarra, Edith Osorio de la Rosa, and Javier Vázquez Castillo. "A Self-Powered PMFC-Based Wireless Sensor Node for Smart City Applications." Wireless Communications and Mobile Computing 2019 (June 3, 2019): 1–10. http://dx.doi.org/10.1155/2019/8986302.
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Long power wide area networks (LPWAN) systems play an important role in monitoring environmental conditions for smart cities applications. With the development of Internet of Things (IoT), wireless sensor networks (WSN), and energy harvesting devices, ultra-low power sensor nodes (SNs) are able to collect and monitor the information for environmental protection, urban planning, and risk prevention. This paper presents a WSN of self-powered IoT SNs energetically autonomous using Plant Microbial Fuel Cells (PMFCs). An energy harvesting device has been adapted with the PMFC to enable a batteryless operation of the SN providing power supply to the sensor network. The low-power communication feature of the SN network is used to monitor the environmental data with a dynamic power management strategy successfully designed for the PMFC-based LoRa sensor node. Environmental data of ozone (O3) and carbon dioxide (CO2) are monitored in real time through a web application providing IoT cloud services with security and privacy protocols.
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Liu, Bin, and Hongbo Zhu. "Energy-Effective Data Gathering for UAV-Aided Wireless Sensor Networks." Sensors 19, no. 11 (2019): 2506. http://dx.doi.org/10.3390/s19112506.
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Unmanned aerial vehicles (UAVs) are capable of serving as a data collector for wireless sensor networks (WSNs). In this paper, we investigate an energy-effective data gathering approach in UAV-aided WSNs, where each sensor node (SN) dynamically chooses the transmission modes, i.e., (1) waiting, (2) conventional sink node transmission, (3) uploading to UAV, to transmit sensory data within a given time. By jointly considering the SN’s transmission policy and UAV trajectory optimization, we aim to minimize the transmission energy consumption of the SNs and ensure all sensory data completed collected within the given time. We take a two-step iterative approach and decouple the SN’s transmission design and UAV trajectory optimization process. First, we design the optimal SNs transmission mode policy with preplanned UAV trajectory. A dynamic programming (DP) algorithm is proposed to obtain the optimal transmission policy. Then, with the fixed transmission policy, we optimize the UAV’s trajectory from the preplanned trace with recursive random search (RRS) algorithm. Numerical results show that the proposed scheme achieves significant energy savings gain over the benchmark schemes.
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Shnain, Ammar H., G. Mohammed, and Yalla Jeevan Nagendra Kumar. "A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics." SHS Web of Conferences 216 (2025): 01044. https://doi.org/10.1051/shsconf/202521601044.
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Using smart data analytics and IoT-driven sensor networks to enhance precision agriculture, the paper provides a whole framework for real-time Crop Monitoring and yield optimization. Using IoT-Driven Sensor Networks (CM-IoT-SN), Crop Monitoring aims to provide farmers practical data for maximizing yields and improving crop condition. Many times, existing precision agricultural technologies suffer from flaws such as poor data granularity, delayed feedback, and the difficulty to provide real-time monitoring across large agricultural fields. These weaknesses lower crop productivity and lead to less than perfect decision-making. To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. Results reveal that this approach not only increases crop productivity however additionally reduces resource waste, therefore providing a sustainable substitute for modern agriculture.
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Zhao, Bingya, and Ya Zhang. "Transmission rate conditions for distributed filtering in sensor networks against eavesdropper." Transactions of the Institute of Measurement and Control 43, no. 12 (2021): 2757–67. http://dx.doi.org/10.1177/01423312211005607.
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This paper studies the distributed secure estimation problem of sensor networks (SNs) in the presence of eavesdroppers. In an SN, sensors communicate with each other through digital communication channels, and the eavesdropper overhears the messages transmitted by the sensors over fading wiretap channels. The increasing transmission rate plays a positive role in the detectability of the network while playing a negative role in the secrecy. Two types of SNs under two cooperative filtering algorithms are considered. For networks with collectively observable nodes and the Kalman filtering algorithm, by studying the topological entropy of sensing measurements, a sufficient condition of distributed detectability and secrecy, under which there exists a code–decode strategy such that the sensors’ estimation errors are bounded while the eavesdropper’s error grows unbounded, is given. For collectively observable SNs under the consensus Kalman filtering algorithm, by studying the topological entropy of the sensors’ covariance matrices, a necessary condition of distributed detectability and secrecy is provided. A simulation example is given to illustrate the results.
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Rababaah, Aaron Rasheed. "Sensor networks simulation framework for target tracking applications: SN-SiFTTA." International Journal of Web Engineering and Technology 16, no. 2 (2021): 113. http://dx.doi.org/10.1504/ijwet.2021.117767.
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Rababaah, Aaron Rasheed. "Sensor networks simulation framework for target tracking applications: SN-SiFTTA." International Journal of Web Engineering and Technology 16, no. 2 (2021): 113. http://dx.doi.org/10.1504/ijwet.2021.10041271.
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Mpitziopoulos, Aristides, Damianos Gavalas, Charalampos Konstantopoulos, and Grammati Pantziou. "CBID: A Scalable Method for Distributed Data Aggregation in WSNs." International Journal of Distributed Sensor Networks 6, no. 1 (2010): 206517. http://dx.doi.org/10.1155/2010/206517.
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Mobile Agent (MA) technology has been recently proposed in Wireless Sensors Networks (WSNs) literature to answer the scalability problem of client/server model in data fusion applications. Herein we present CBID, a novel algorithm that calculates near-optimal routes for MAs that incrementally fuse the data as they visit the Sensor Nodes (SNs) while also enabling fast updates on the designed itineraries upon changes of network topology. CBID dispatches in parallel a number of MAs that sequentially visit sensor nodes arranged in tree structures and upon visiting an SN with two or more child SNs, the MAs (master MAs) clone of themselves with each clone (slave MA) visiting a tree branch. When all slave MAs return to that SN, they deliver their collected data to the master MA and are then disposed of. This results in a significant reduction of the overall energy expenditure and response time. Simulation results prove the high effectiveness of CBID in data fusion tasks compared to other alternative algorithms.
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Ali, Syed Asif, Mubashar Sarfraz, Sajjad A. Ghauri, et al. "A Weighted Cluster Head Selection Algorithm for Energy Efficient Wireless Sensor Networks." Journal of Sensors 2022 (May 6, 2022): 1–13. http://dx.doi.org/10.1155/2022/3055178.
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The wireless sensor network’s (WSNs) lifetime is mainly dependent on the RE of the sensor nodes (SeN). In recent years, energy minimization in a WSN has been a prominent research topic, and numerous solutions have been proposed. This research focuses on the energy minimization of the SeNs where firstly, K-medoid clustering algorithm is applied to create clusters. Second, a weighted cluster head selection technique is used to choose a cluster head (CH) by integrating three independent weights associated with an SeN: energy, distance from the centroid, and distance from the sink node (SN). According to the energy level and distance from the SN and cluster’s centre, each node is assigned a constant weight. The simulation results are compared to existing methodologies, and the results show that the suggested network’s lifetime enhances.
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Ito, Toshi, Masafumi Oda, Osamu Takyu, Mai Ohta, Takeo Fujii, and Koichi Adachi. "Three Level Recognition Based on the Average of the Phase Differences in Physical Wireless Parameter Conversion Sensor Networks and Its Effect to Localization with RSSI." Sensors 23, no. 6 (2023): 3308. http://dx.doi.org/10.3390/s23063308.
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In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access by sensors and waiting time to avoid packet collisions; this increases the aggregation time. The physical wireless parameter conversion sensor network (PhyC-SN) method, which transmits sensor information corresponding to the carrier wave frequency, facilitates the bulk collection of sensor information, thereby reducing the communication time and achieving a high aggregation success rate. However, when more than one sensor transmits the same frequency simultaneously, the estimation accuracy of the number of accessed sensors deteriorates significantly because of multipath fading. Thus, this study focuses on the phase fluctuation of the received signal caused by the frequency offset inherent to the sensor terminals. Consequently, a new feature for detecting collisions is proposed, which is a case in which two or more sensors transmit simultaneously. Furthermore, a method to identify the existence of 0, 1, 2, or more sensors is established. In addition, we demonstrate the effectiveness of PhyC-SNs in estimating the location of radio transmission sources by utilizing three patterns of 0, 1, and 2 or more transmitting sensors.
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N. Keerthikaa. "A Comprehensive Study on Energy-Efficient and Secure Communication Strategies in WSN." Journal of Information Systems Engineering and Management 10, no. 48s (2025): 1084–96. https://doi.org/10.52783/jisem.v10i48s.9729.
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Wireless Sensor Networks (WSNs) are group of sensor nodes (SN) distributed in space and linked through wireless communication. WSN include the processors, battery modules and wireless communication devices. SN gathers and transmits the environmental information to BS for efficient processing. WSN includes low-power and low-cost devices for administration because of critical roles of energy as well as security. SN is dependent on batteries that experienced the energy loss with minimum network lifetime. Consequently, energy efficient data broadcast is performed in WSN through optimization methods. Dissimilar researchers performed their research on energy efficient and secured information broadcast by optimization and cryptographic methods in WSN. However, energy consumption was not minimized and data confidentiality rate was not enhanced by existing techniques. The main aim of research work is to reduce energy utilization and increase the network security using cryptographic and optimization techniques.
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Tuyishimire, Emmanuel, Antoine Bagula, and Adiel Ismail. "Clustered Data Muling in the Internet of Things in Motion." Sensors 19, no. 3 (2019): 484. http://dx.doi.org/10.3390/s19030484.
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This paper considers a case where an Unmanned Aerial Vehicle (UAV) is used to monitor an area of interest. The UAV is assisted by a Sensor Network (SN), which is deployed in the area such as a smart city or smart village. The area being monitored has a reasonable size and hence may contain many sensors for efficient and accurate data collection. In this case, it would be expensive for one UAV to visit all the sensors; hence the need to partition the ground network into an optimum number of clusters with the objective of having the UAV visit only cluster heads (fewer sensors). In such a setting, the sensor readings (sensor data) would be sent to cluster heads where they are collected by the UAV upon its arrival. This paper proposes a clustering scheme that optimizes not only the sensor network energy usage, but also the energy used by the UAV to cover the area of interest. The computation of the number of optimal clusters in a dense and uniformly-distributed sensor network is proposed to complement the k-means clustering algorithm when used as a network engineering technique in hybrid UAV/terrestrial networks. Furthermore, for general networks, an efficient clustering model that caters for both orphan nodes and multi-layer optimization is proposed and analyzed through simulations using the city of Cape Town in South Africa as a smart city hybrid network engineering use-case.
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Ren, Qian, and Guangshun Yao. "An Energy-Efficient Cluster Head Selection Scheme for Energy-Harvesting Wireless Sensor Networks." Sensors 20, no. 1 (2019): 187. http://dx.doi.org/10.3390/s20010187.
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Concerning the large amount of energy consumption during the cluster head selection stage and the unequal harvested energy among nodes in energy-harvesting wireless sensor networks (EH-WSNs), an energy- efficient cluster head selection scheme called EECHS is proposed in this paper. The scheme divides all nodes from one cluster into three types: cluster head (CH), cluster member (CM), and scheduling node (SN). The SN is designed to monitor and store real-time information about the residual energy of all nodes, including CMs and the CH, in the same cluster. In the CH selection stage, the SN specifies a corresponding CM as the new CH according to the monitored results, thereby reducing the energy consumption caused by CH selection. In this way, the task of CH selection is migrated from CHs to SNs and, thus, the CHs can preserve more energy for data forwarding. Moreover, the EECHS adjusts the transmission radius of some nodes dynamically to prevent these nodes from discarding the harvested energy if their batteries are fully charged. A series of experiments were conducted to verify the effectiveness of the proposed EECHS, and the results demonstrate that EECHS can provide an efficient CH selection scheme for EH-WSNs and is able to use the harvested energy more efficiently than corresponding competitors.
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Brini, Oussama, Dominic Deslandes, and Frederic Nabki. "A System-Level Methodology for the Design of Reliable Low-Power Wireless Sensor Networks." Sensors 19, no. 8 (2019): 1800. http://dx.doi.org/10.3390/s19081800.
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Innovative Internet of Things (IoT) applications with strict performance and energy consumption requirements and where the agile collection of data is paramount are arising. Wireless sensor networks (WSNs) represent a promising solution as they can be easily deployed to sense, process, and forward data. The large number of Sensor Nodes (SNs) composing a WSN are expected to be autonomous, with a node’s lifetime dictated by the battery’s size. As the form factor of the SN is critical in various use cases, minimizing energy consumption while ensuring availability becomes a priority. Moreover, energy harvesting techniques are increasingly considered as a viable solution for building an entirely green SN and prolonging its lifetime. In the process of building a SN and in the absence of a clear and well-rounded methodology, the designer can easily make unfounded and suboptimal decisions about the right hardware components, their configuration, and reliable data communication techniques, such as automatic repeat request (ARQ) and forward error correction (FEC). In this paper, a methodology to design, configure, and deploy a reliable ultra-low power WSNs is proposed. A comprehensive energy model and a realistic path-loss (PL) model of the sensor node are also established. Through estimations and field measurements it is proven that, following the proposed methodology, the designer can thoroughly explore the design space and the make most favorable decisions when choosing commercial off-the-shelf (COTS) components, configuring the node, and deploying a reliable and energy-efficient WSN.
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Guo, Zhihui, Hongbin Chen, and Shichao Li. "Deep Reinforcement Learning-Based UAV Path Planning for Energy-Efficient Multitier Cooperative Computing in Wireless Sensor Networks." Journal of Sensors 2023 (April 5, 2023): 1–13. http://dx.doi.org/10.1155/2023/2804943.
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Benefiting from the progress of microelectromechanical system (MEMS) technology, wireless sensor networks (WSNs) can run a large number of complex applications. One of the most critical challenges for complex WSN applications is the huge computing demands and limited battery energy without any replenishment. The recent development of UAV-assisted cooperative computing technology provides a promising solution to overcome these shortcomings. This paper addresses a three-tier WSN model for UAV-assisted cooperative computing, which includes several sensor nodes, a moving UAV equipped with computing resources, and a sink node (SN). Computation tasks arrive randomly at each sensor node, and the UAV moves around above the sensor nodes and provides computing services. The sensor nodes can process the computation tasks locally or cooperate with the UAV or SN for computing. In a life cycle of the UAV, we aim to maximize the energy efficiency of cooperative computing by optimizing the UAV path planning on the constraints of node energy consumption and task deadline. To adapt to the time-varying indeterminate environment, a deep Q network- (DQN-) based path planning algorithm is proposed. Simulation studies show that the performance of the proposed algorithm is better than the competitive algorithms, significantly improves the energy efficiency of cooperative computing, and achieves energy consumption balance.
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Tsvetanov, Filip Atanasov, and Martin Pandurski. "Selection of Protocols for Integration of Sensory Data Networks in Cloud Structures." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 09 (2022): 29–40. http://dx.doi.org/10.3991/ijoe.v18i09.31321.
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The striving to obtain more detailed information about the environment and control various processes leads to an increase in the number of connected sensor devices in various industrial areas. The collected large amount of data can be analysed in real-time. The sensors that build up the WSN have limited hardware resources and cannot process large amounts of data. The integration between WSN and cloud structures is an excellent method for storing, processing, accessing data via the Internet and solves the issue of the limited capacity of WSN. The big challenge to designing the WSN - cloud systems is establishing a communication channel (through different protocols) between devices in the network and cloud platforms. This project executes/perform a real experiment on the XBee sensor network and the ThingSpeak cloud, and the data transmission between them is forwarded using different protocols (HTTP, HTTPS, MQTT and MQTT-SN). The influence of the parameters of the transmitted packet on the delay, the CPU, RAM load has been studied. The results give some advantages of MQTT over other protocols in terms of data rate, CPU and RAM load when working with XBee sensor modules and integration between WSN and cloud structures.
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Pala, Zeydin. "The effects of LT-SN on energy dissipation and lifetime in wireless sensor networks." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 7, no. 1 (2016): 50–58. http://dx.doi.org/10.11121/ijocta.01.2017.00408.
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Wireless sensor networks (WSNs) still attract the attention of researchers, users and the private sector despite their low power and low range tendency for malfunction. This attraction towards WSNs results from their low cost structure and the solutions they offer for many prevalent problems. Many conditions, which remain unforeseen or unexpected during the design of the system, may arise after the initialization of the system. Similarly, many situations where security vulnerabilities take place may emerge in time in WSNs operating normally. In this study, we called nodes which enter sleeping mode without any further waking up and causing a sparser number of nodes in the network without any function in data transmission as Long-Term Sleep Nodes (LT-SN); and considered energy spaces caused by such nodes as a problem; and established two Linear Programming (LP) models based on the efficiency of the present nodes. We offered two different models which present the effect of sensor nodes, which were initially operating in wireless sensor network environment and did not wake up following sleep mode, on network lifetime. The results of the present study report that as the number of LT-SN increases, the lifetime of the network decreases.
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Jain, Khushboo, Anoop Kumar, and Vaibhav Vyas. "A Resilient Steady Clustering Technique for Sensor Networks." International Journal of Applied Evolutionary Computation 11, no. 4 (2020): 1–12. http://dx.doi.org/10.4018/ijaec.2020100101.
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In wireless sensor networks (WSNs), each sensor node is proficient to transmit data packets dynamically deprived of any constraint of fixed infrastructure. Sensor nodes (SNs) intermittently travels within the network from one cluster to another, which makes the network topology unsteady, uncertain, and unreliable. Consequently, it turns to be an immense challenge to sustain network stability and durability. In this work, the authors have presented a resilient steady clustering technique (RSCT) that will maintain durability and steadiness to the sensor network by reducing the unnecessary and avoidable cluster head (CH) changes and minimizing clustering and networking overheads. In the presented technique, they have introduced a new SN that acts as a standby node (SBN) in the cluster. This SBN performs the tasks of CH whenever the actual CH moves from the cluster. Later the CH re-elect the new SBN. This process keeps the network available and serviceable without any interruption. The decision for selecting the CH and SBN depends on the optimal CH threshold function and an energy threshold function.
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Sinyavskiy, Ivan, Igor Sorokin, and Andrei Sukhov. "Prototype wireless network for internet of things based on DECT standard." Telfor Journal 14, no. 1 (2022): 8–11. http://dx.doi.org/10.5937/telfor2201008s.
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This paper presents a software prototype of a wireless network for the Internet of Things (IoT) based on the DECT (Digital Enhanced Cordless Telecommunication) standard. It proposes an architecture for encapsulating commands from the most common IoT protocol, MQTT (Message Queuing Telemetry Transport), into SIP (Session Initiation Protocol) packets. A module is created to embed MQTT-SN (MQTT for Sensor Networks) packets into SIP packets. The module is developed in Go language using the built-in "net" library. Delivery of MQTT-SN packets to IoT devices is carried out using the SIP protocol. Source codes and instructions for installing the gateway can be found at https://github.com/iSinyavsky/mqtt-sn-sip-gateway.
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Just, Gilson E., Marcelo E. Pellenz, Luiz A. de Paula Lima, Bruno S. Chang, Richard Demo Souza, and Samuel Montejo-Sánchez. "UAV Path Optimization for Precision Agriculture Wireless Sensor Networks." Sensors 20, no. 21 (2020): 6098. http://dx.doi.org/10.3390/s20216098.
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The use of monitoring sensors is increasingly present in the context of precision agriculture. Usually, these sensor nodes (SNs) alternate their states between periods of activation and hibernation to reduce battery usage. When employing unmanned aerial vehicles (UAVs) to collect data from SNs distributed over a large agricultural area, we must synchronize the UAV route with the activation period of each SN. In this article, we address the problem of optimizing the UAV path through all the SNs to reduce its flight time, while also maximizing the SNs’ lifetime. Using the concept of timeslots for time base management combined with the idea of flight prohibition list, we propose an efficient algorithm for discovering and reconfiguring the activation time of the SNs. Experimental results were obtained through the development of our own simulator—UAV Simulator. These results demonstrate a considerable reduction in the distance traveled by the UAV and also in its flight time. In addition, the model provides a reduction in transmission time by SNs after reconfiguration, thus ensuring a longer lifetime for the SNs in the monitoring environment, as well as improving the freshness and continuity of the gathered data, which support the decision-making process.
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Shiltagh, Nadia A., Mahmood Z. Abdullah, and Ahmed R. Zarzoor. "Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2880. http://dx.doi.org/10.11591/ijece.v9i4.pp2880-2892.
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An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols in two phases: The first phase is used to evaluate the route quality and networks’ energy consumption on small WSN with one mobile Sink Node (SN) and GMSs. The second phase, is used to evaluate the route quality and networks’ energy consumption on large network (four WSNs) with GMSs. The two phases are implementated by creating five sceneries via using NS2.3 simulator software. The implementation results of the proposed performance evaluation technique have demonstrated that SMSNDRP gives better networks’ energy consumption on small single network in comparison with KM-DGP. Also, it gives high quality route in large network that used four mobile SN, in contrast to KM-DGP that used sixteen mobile SNs. While in large network, it found that KM-DGP with sixteen mobile SNs gives better networks’ energy consumption in comparison with SMSNDRP with four mobile SNs.
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Nadia, A. Shiltagh, Z. Abdullah Mahmood, and R. Zarzoor Ahmed. "Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2880–92. https://doi.org/10.11591/ijece.v9i4.pp2880-2892.
Full textAbstract:
An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols in two phases: The first phase is used to evaluate the route quality and networks’ energy consumption on small WSN with one mobile Sink Node (SN) and GMSs. The second phase, is used to evaluate the route quality and networks’ energy consumption on large network (four WSNs) with GMSs. The two phases are implementated by creating five sceneries via using NS2.3 simulator software. The implementation results of the proposed performance evaluation technique have demonstrated that SMSNDRP gives better networks’ energy consumption on small single network in comparison with KM-DGP. Also, it gives high quality route in large network that used four mobile SN, in contrast to KM-DGP that used sixteen mobile SNs. While in large network, it found that KM-DGP with sixteen mobile SNs gives better networks’ energy consumption in comparison with SMSNDRP with four mobile SNs.
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Sana, Muhammad Shahzaib, Muhammad Yousaf Ali Khan, Nasir Saleem, Imran Ullah Khan, and Arbab Waheed Ahmed. "Improved Cooperation in Underwater Wireless Sensor Networks." Mehran University Research Journal of Engineering and Technology 38, no. 4 (2019): 1009–20. http://dx.doi.org/10.22581/muet1982.1904.13.
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The WSNs (Wireless Sensor Networks) lead to great opportunities to explore it scientifically. In this network different numbers of SN (Sensor Nodes) are deployed in a specific area to gather information. The UWSNs (Underwater Wireless Sensor Networks) is a highly distributed network of sensor nodes deployed underwater to gather environmental information. Hence, acquirement of real-time data at enhanced data rate and to reduce power consumption is a key concern while designing routing protocol for UWSNs. In this paper, a cooperation based solution is suggested. The solution proposed here uses the DF (Decode and Forward) strategy for relying the information from the source to the destination using a relay node. The signals coming towards the destination are weighted and combined on the basis of their SNRC (Signal to Noise Ratio Combing). The simulation results verify enhancement in different factors, required for evaluation of a UWSN. After implementation of the proposed solution the stability of the network is increased which maximize the PDR (Packet Delivery Ratio). In our proposed solution the transmission is based on channel estimation, an estimate is made for higher reliable channel, which reduces retransmission of packets. Hence, sink receive the packets with lesser delay and as a result E2E (End-to-End) delay is decreased. Data is forwarded using data forwarding by neighbor nodes. It improves average energy consumption of the system. Hence the overall performance and lifetime of a UWSN is increased.
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Gali, Sowmya, Madhusudhana Reddy Y., Alekya Himabindu B., et al. "Capacity trust assessment for multi-hop routing in wireless sensor networks." E3S Web of Conferences 391 (2023): 01181. http://dx.doi.org/10.1051/e3sconf/202339101181.
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This paper proposed a newIntrusion Detection mechanism based on Multiple Trust Attributes in Wireless Sensor Networks (WSNs). Mainly this work concentrated to assess the trust in ems of capacities of the sensor nodes. The capacity of a node is formulated based on two trusts namely Fault Tolerance Trust and Stability Trust. Every SN checks the trustworthiness of its neighbour SNs based on the Capacity Trust and confirms their trustworthiness. If any node is discovered as malicious, such type of node is called as intrusion or outlier and isolated from network.Extensive Simulations are conducted over the proposed intrusion detection mechanism and the performance is evaluated through Malicious Detection Rate, and False Positive Rate.
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Remlein, Piotr, and Urszula Stachowiak. "Security Verification in the Context of 5G Sensor Networks." Journal of Telecommunications and Information Technology 2 (March 30, 2021): 107–19. http://dx.doi.org/10.26636/jtit.2021.153221.
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In order to develop reliable safety standards for 5G sensor networks (SN) and the Internet of Things, appropriate verification tools are needed, including those offering the ability to perform automated symbolic analysis process. The Tamarin prover is one of such software-based solutions. It allows to formally prove security protocols. This paper shows the modus operandi of the tool in question. Its application has been illustrated using an example of an exchange of messages between two agents, with asynchronous encryption. The scheme may be implemented, for instance, in the TLS/DTLS protocol to create a secure cryptographic key exchange mechanism. The aim of the publication is to demonstrate that automated symbolic analysis may be relied upon to model 5G sensor networks security protocols. Also, a use case in which the process of modeling the DTLS 1.2 handshake protocol enriched with the TCP SYN Cookies mechanism, used to preventing DoS attacks, is presented
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Johnson, Lini, S. Uma, and M. Mathan Kumar. "CDAMA: CONCEALED DATA AGGREGATION SCHEME FOR MULTIPLE APPLICATIONS IN WIRELESS SENSOR NETWORKS." COMPUSOFT: An International Journal of Advanced Computer Technology 03, no. 03 (2014): 629–32. https://doi.org/10.5281/zenodo.14715441.
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Generally, Data Mining is the process of analysing data from different perspectives and summarizing the information. Wireless sensor networks (WSNs) consist of thousands of sensor nodes (SN) that gather data from deployed environments. Efficient data aggregation scheme with security is needed to provide security in the wireless sensor networks as they may suffer unauthorized aggregation attacks. In previous homomorphic encryptions have been applied to conceal communication during aggregation such that enciphered data can be aggregated algebraically without decryption. It reduces a large amount of transmission and it is the most practical technique. Although data aggregation could significantly reduce transmission, it is vulnerable to some attacks. The objective of the proposed system is to design a scheme to detect these attacks or mitigate their impact. It can change the path in the intermediate level. So this will not get any aggregation problem and packet delivery issue.
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Zakariyya, Aliyu, Umar Iliyasu, and Bashir Ahmad Jamilu. "Optimal selection of cluster head in wireless sensor networks using particle swarm optimization (PSO)." Dutse Journal of Pure and Applied Sciences 9, no. 3a (2023): 226–36. http://dx.doi.org/10.4314/dujopas.v9i3a.23.
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In a wide range of applications, such as the military, healthcare, and environmental monitoring, wireless sensor networks (WSNs) have emerged as a key player. Cluster-based WSNs are a viable method for enhancing the life of the sensor network. Choosing the proper cluster head for wireless sensor networks (WSNs) is a key undertaking that affects the network's performance. Current approaches for selecting the cluster head have a number of drawbacks, such as nodes dying too quickly, uneven energy utilization, and shorter network lifespan. Additionally, conventional techniques like fixed Cluster Head and randomized Clustering are ineffective at extending the network lifetime. In the proposed method, Particle swarm optimization was used to create an optimal cluster head selection that addresses the problem of intra-cluster communication and lowers SN energy consumption. The simulation result shows that the performance improvement of the developed algorithm PSO in terms of network lifetime is 10% against Improved Cuckoo Search Algorithm (ICSA) and 25% against Hybrid Crow Search Algorithm (HCSA), energy consumption is 15% against ICSA and 20% against HCSA, and number of alive node is 4% against ICSA and 6% against HCSA respectively. Therefore, our developed algorithm PSO outperforms ICSA and HCSA in terms of the aforementioned parameters.
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Sambu Anitha, Et al. "Energy Aware Clustering System for Wireless Sensor Networks utilizing Rider Sunflower Optimization Approach." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 1498–505. http://dx.doi.org/10.17762/ijritcc.v11i9.9131.
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Wireless Sensor Networks (WSN) are spatially disseminated sensors that are utilized for monitoring physical or environmental factors, like sound, temperature, pressure, and so on, to collectively drive their information from the networking to the base station. The WSN is composed of hundreds or thousands, where all the nodes are interconnected with other Sensor Node (SN). Clustering is the most popular topology management technique in WSN, grouping nodes to manage them or execute different tasks in a distributed manner, like resource management. It includes grouping sensors and selecting Cluster Heads (CHs) for every cluster. Therefore, this study presents a new Rider Sunflower Optimizing Model-Based Energy Aware Clustering Approach (RSFOA-EACA) for WSNs. The prime goal of the RSFOA-EACA technique is in the optimum selection of CH for data transmission in the WSN. With Rider Optimization Algorithm (ROA) and Sunflower Optimization (SFO) incorporation, the RSFOA-EACA technique mainly depends upon the RSFOA. Furthermore, the RSFOA-EACA algorithm derives a Fitness Function (FF) by the computation of distance, Residual Energy (RE), Node Degree (ND), and network coverage. The CH selecting enables proper inter-cluster transmission in the network. The experimental analysis of the RSFOA-EACA method is investigated by implementing a sequence of simulations. The simulation values emphasized the promising energy efficiency outcomes of the RSFOA-EACA approach.
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Tong, Jin, and Jian Sun. "Data Acquisition Method of Sensor News Based on Collaborative Filtering Algorithm." Wireless Communications and Mobile Computing 2022 (February 12, 2022): 1–9. http://dx.doi.org/10.1155/2022/1504454.
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With the vigorous development of new media technologies such as Internet of Things, big data, and cloud computing, data-based sensor news (SN) will become the trend of news reporting in the future and the new normal of news production. Under this background, this paper further analyzes the relationship between SN production mode and traditional news production, including the inheritance of traditional news production value concept, as well as the breakthrough and change in form, media, and effect. In this paper, collaborative filtering (CF) algorithm is improved to solve the problems of data sparseness, user interest migration, and scalability in CF technology. In the calculation of news content similar degree (SD), the influence of part of speech and position of feature words in news is also considered, and the time window is used to establish a model that adapts to the change of user interest with time. In this method, the contribution degree of different attributes to distinguishing users is considered, and the attribute SD between users is accurately calculated, which effectively improves the accuracy of SN data acquisition results.
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Xiao, Xingxing, and Haining Huang. "A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks." Algorithms 13, no. 10 (2020): 250. http://dx.doi.org/10.3390/a13100250.
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Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selection based on the residual energy of nodes and the distance factor. The selected CHN gathers data sent by the CMNs and transmits them to the sink node by multiple hops. Optimal multi-hop paths from the CHNs to the SN are found by an improved ACO algorithm. This paper presents the ACO algorithm through the improvement of the heuristic information, the evaporation parameter for the pheromone update mechanism, and the ant searching scope. Simulation results indicate the high effectiveness and efficiency of the proposed algorithm in reducing the energy consumption, prolonging the network lifetime, and decreasing the packet loss ratio.
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Amodu, Oluwatosin Ahmed, Rosdiadee Nordin, Chedia Jarray, Umar Ali Bukar, Raja Azlina Raja Mahmood, and Mohamed Othman. "A Survey on the Design Aspects and Opportunities in Age-Aware UAV-Aided Data Collection for Sensor Networks and Internet of Things Applications." Drones 7, no. 4 (2023): 260. http://dx.doi.org/10.3390/drones7040260.
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Due to the limitations of sensor devices, including short transmission distance and constrained energy, unmanned aerial vehicles (UAVs) have been recently deployed to assist these nodes in transmitting their data. The sensor nodes (SNs) in wireless sensor networks (WSNs) or Internet of Things (IoT) networks periodically transmit their sensed data to UAVs to be relayed to the base station (BS). UAVs have been widely deployed in time-sensitive or real-time applications, such as in disaster areas, due to their ability to transmit data to the destination within a very short time. However, timely delivery of information by UAVs in WSN/IoT networks can be very complex due to various technical challenges, such as flight and trajectory control, as well as considerations of the scheduling of UAVs and SNs. Recently, the Age of Information (AoI), a metric used to measure the degree of freshness of information collected in data-gathering applications, has gained much attention. Numerous studies have proposed solutions to overcome the above-mentioned challenges, including adopting several optimization and machine learning (ML) algorithms for diverse architectural setups to minimize the AoI. In this paper, we conduct a systematic literature review (SLR) to study past literature on age minimization in UAV-assisted data-gathering architecture to determine the most important design components. Three crucial design aspects in AoI minimization were discovered from analyzing the 26 selected articles, which focused on energy management, flight trajectory, and UAV/SN scheduling. We also investigate important issues related to these identified design aspects, for example, factors influencing energy management, including the number of visited sensors, energy levels, UAV cooperation, flight time, velocity control, and charging optimization. Issues related to flight trajectory and sensor node scheduling are also discussed. In addition, future considerations on problems such as traffic prioritization, packet delivery errors, system optimization, UAV-to-sensor node association, and physical impairments are also identified.
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Faheem, Yasir, and Saadi Boudjit. "Duty-cycle SN-multi-point relay algorithm for mobile sink wireless sensor networks." IET Wireless Sensor Systems 5, no. 5 (2015): 219–27. http://dx.doi.org/10.1049/iet-wss.2013.0141.
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Fu, Hao, Yinghong Liu, Zhe Dong, and Yuanming Wu. "A Data Clustering Algorithm for Detecting Selective Forwarding Attack in Cluster-Based Wireless Sensor Networks." Sensors 20, no. 1 (2019): 23. http://dx.doi.org/10.3390/s20010023.
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In cluster-based wireless sensor networks, cluster heads (CHs) gather and fuse data packets from sensor nodes; then, they forward fused packets to the sink node (SN). This helps wireless sensor networks balance energy effectively and efficiently to prolong their lifetime. However, cluster-based WSNs are vulnerable to selective forwarding attacks. Compromised CHs would become malicious and launch selective forwarding attacks in which they drop part of or all the packets from other nodes. In this paper, a data clustering algorithm (DCA) for detecting a selective forwarding attack (DCA-SF) is proposed. It can capture and isolate malicious CHs that have launched selective forwarding attacks by clustering their cumulative forwarding rates (CFRs). The DCA-SF algorithm has been strengthened by changing the DCA parameters (Eps, Minpts) adaptively. The simulation results show that the DCA-SF has a low missed detection rate of 1.04% and a false detection rate of 0.42% respectively with low energy consumption.
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Aalsalem, Mohammed Y. "An effective hotspot mitigation system for Wireless Sensor Networks using hybridized prairie dog with Genetic Algorithm." PLOS ONE 19, no. 4 (2024): e0298756. http://dx.doi.org/10.1371/journal.pone.0298756.
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Wireless Sensor Networks (WSNs) consist of small, multifunctional nodes distributed across various locations to monitor and record parameters. These nodes store data and transmit signals for further processing, forming a crucial topic of study. Monitoring the network’s status in WSN applications using clustering systems is essential. Collaboration among sensors from various domains enhances the precision of localised information reporting. However, nodes closer to the data sink consume more energy, leading to hotspot challenges. To address these challenges, this research employs clustering and optimised routing techniques. The aggregation of information involves creating clusters, further divided into sub-clusters. Each cluster includes a Cluster Head (CH) or Sensor Nodes (SN) without a CH. Clustering inherently optimises CHs’ capabilities, enhances network activity, and establishes a systematic network topology. This model accommodates both multi-hop and single-hop systems. This research focuses on selecting CHs using a Genetic Algorithm (GA), considering various factors. While GA possesses strong exploration capabilities, it requires effective management. This research uses Prairie Dog Optimization (PDO) to overcome this challenge. The proposed Hotspot Mitigated Prairie with Genetic Algorithm (HM-PGA) significantly improves WSN performance, particularly in hotspot avoidance. With HM-PGA, it achieves a network lifetime of 20913 milliseconds and 310 joules of remaining energy. Comparative analysis with existing techniques demonstrates the superiority of the proposed approach.
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Ghosh, Ramkrishna. "A novel Sugeno type 2 Fuzzy system for finding error positions applying localization in wireless sensor network." International Journal Artificial Intelligent and Informatics 2, no. 1 (2022): 53–66. http://dx.doi.org/10.33292/ijarlit.v2i1.34.
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In various usages where Wireless Sensor Networks (WSNs) have been utilized, this is vital to identify wherefrom Sensor nodes (SNs) or which position valuable details is attained. The Global Positioning System (GPS) is traditionally utilized to find out position. Nevertheless, GPS schemes are not perfect for various usages because of their extreme power utilization and high charge. As a substitute to GPS, distance and position may be approximated during the practice of more than three SNs with identified positions. Received Signal Strength Indication (RSSI) is the easiest and largely economical method applied to decide distance and position, and is a criterion aspect on each sensor. Howbeit, RSSI might be influenced through sound and ecological difficulties. Due to this, this is not easy to place up a statistical model for RSSI. The range free technique has various approaches to evaluate the location of SNs in a particular area. In our research work, Centroid localization is employed for development and investigation. RSSI is attained by evaluating the distance between every anchor node (AN) and the SN. Evaluating the position of every SN would be carried out with the help of centroid technique. However, the weights remain the chief metrics in the centroid connection; those are the output of the Sugeno Type 2 fuzzy scheme. Actually, the sugeno type 2 fuzzy technique is obtained RSSIs being inputs to depict the outputs; those are weights of every AN to the SN.
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Nwankwo, Emmanuel, Michael David, and Elizabeth Nonye Onwuka. "Integration of MQTT-SN and CoAP protocol for enhanced data communications and resource management in WSNs." Bulletin of Electrical Engineering and Informatics 13, no. 3 (2024): 1613–20. http://dx.doi.org/10.11591/eei.v13i3.5158.
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Lightweight communication protocols for wireless sensor networks (WSNs) are unfolding for machine to machine (M2M) communications and thus there is always going to be a possible conflict of interest on which protocol is best suited for any particular application. The two protocols of interest in this study are the message queue telemetry transport protocol for sensor network (MQTT-SN), a variant of message queue telemetry transport (MQTT) protocol and the constrained application protocol (CoAP). There have been studies that reveal that these protocols perform differently based on the underlying network conditions. CoAP experience lower delays than MQTT for higher packet loss and higher delays for lower packet loss. MQTT default communication via a broker is easier to scale compared to CoAP direct request-response paradigm. Although this is a huge advantage over CoAP, it presents the single point-of-failure problem. In this paper we propose an integration of MQTT-CoAP protocol using an abstraction layer that enables both MQTT-SN and CoAP protocol to be used in the same sensor node. Resources are managed by directly modifying sensor node configuration using CoAP protocol. Performance evaluation of these protocols under the integrated scenario shows acceptable levels of latency and energy consumption for internet of thing (IoT) operations.
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Lin, Chi-Yi, Kai-Hung Liao, and Chia-Hsuan Chang. "An Experimental System for MQTT/CoAP-based IoT Applications in IPv6 over Bluetooth Low Energy." JUCS - Journal of Universal Computer Science 24, no. (9) (2018): 1170–91. https://doi.org/10.3217/jucs-024-09-1170.
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With the rapid development of Internet of Things (IoT), it is an inevitable trend that all things will get connected to the Internet to form various intelligent services such as Industry 4.0, smart home, smart medical care, etc. To make such intelligent IoT services practicable, it is vital to have a low-power link-layer technology that can accommodate a diversity of upper-layer networking protocols. Currently, there are many popular low-power wireless networking technologies for IoT such as ZigBee and Bluetooth Low Energy (BLE). Because of the ubiquity of BLE-enabled smartphones nowadays, BLE has gained much attention in the IoT industry recently. In this research, we aim at implementing an IPv6 over BLE experimental system using Raspberry Pi 3 and nRF51-DK development boards, and then run the Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) protocol and the Constrained Application Protocol (CoAP) over the protocol stack of IPv6/BLE. Specifically, in our experimental system every BLE node is IPv6-addressable and accessible through the MQTT/CoAP protocols from anywhere over the Internet. Moreover, to ease user accesses from ordinary web browsers, we build two gateways as the web servers for end users, which receive real-time sensor data via CoAP or MQTT-SN protocols and then push the data to end users' browsers. The gateways are also designed to routinely request sensor data and then forward the data to cloud database platforms, which serve as the data sources for historical sensor data. Preliminary results showed that our system is capable of achieving the designed goals and is user-friendly. Compared with the non-IP based BLE sensor networks, our implementation can be integrated into a variety of existing and widely used IP-based applications easily.
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Kumar Dwivedi, Anshu, Awadhesh Kumar Sharma, and Pawan Singh Mehra. "Energy Efficient Sensor Node Deployment Scheme for Two Stage Routing Protocol of Wireless Sensor Networks assisted IoT." ECTI Transactions on Electrical Engineering, Electronics, and Communications 18, no. 2 (2020): 158–69. http://dx.doi.org/10.37936/ecti-eec.2020182.240541.
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Now a day wireless sensor networks (WSNs) is an essential unit of the internet of things (IoT). IoT theater a vital role in real-time applications which is more useful in real life. Due to its small price and potential use, WSNs have shown importance in different applications over the past year. Health concerns, environmental observation, human protection, military operations, surveillance systems, etc. WSNs have a small device called a sensor node (SN) that has a limited battery. IoT based WSNs consume more energy in sensor node communication. Therefore a Novel energy-efficient sensor node deployment scheme for two-stage routing protocol (EE- DSTRP) has been proposed to reduce the energy consumption of sensor nodes and extend the lifetime of the network. Sensor node deployment is a novel approach based on the golden ratio. All traditional protocols divide network zones for communication. No existing protocols tell about the sensor node deployment ratio in each zone. The deployment method is an important factor in reducing the energy usage of a network. To validate its efficiency, in this article, simulation results prove that the proposed IoT based EE-DSTRP protocol is superior to other existing protocols.
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Bashir, Humera, Zohaib Zahid, Agha Kashif, Sohail Zafar, and Jia-Bao Liu. "On 2-metric resolvability in rotationally-symmetric graphs." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11887–95. http://dx.doi.org/10.3233/jifs-210040.
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The 2-metric resolvability is an extension of metric resolvability in graphs having several applications in intelligent systems for example network optimization, robot navigation and sensor networking. Rotationally symmetric graphs are important in intelligent networks due to uniform rate of data transformation to all nodes. In this article, 2-metric dimension of rotationally symmetric plane graphs Rn, Sn and Tn is computed and found to be independent of the number of vertices.
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Natesan, Sathish Kumar, and Raja Kumar Krishnan. "Fuzzy Logic Depth Based Energy Aware Routing Protocol for Underwater Acoustic Sensor Network: FLDEAR." Journal of Information & Knowledge Management 20, Supp01 (2021): 2140002. http://dx.doi.org/10.1142/s0219649221400025.
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The Underwater Acoustic Sensor Network (UASN) plays a dynamic role in various application extents like surveillance, military, terrestrial networks and industrial application. In UASN, each Underwater Sensor Node (USN) is deployed in many places. The multiple paths are always used for transmitting data from USN to the Sink Node (SN). Each sensor constitutes a set of small devices and a small battery. If data is received from multiple nodes at the same time then, there is a chance for a collision and also it will bring down network lifetime. In recent years, only a few research works are done in fuzzy based routing in UASN. For increasing the network’s lifetime, there is always a need for an optimum routing path in UASN with improved parameters related to propagation delay, energy and throughput. The present paper proposes the Fuzzy Logic Depth based Energy-Aware Routing (FLDEAR) path in UASN. A static USN was utilized in the proposed system. Each USN is assigned a Priority Number (PN) by the SN. The PN is used for avoiding collision in the proposed model. The simulation is conducted employing Aqua-Sim (AS) which is based on Network Simulator-2(NS2). The simulation results illustrate that this system outperforms the existing routing protocol such as protocols of Energy Efficient Cooperative Opportunistic Routing (EECOR), Fuzzy Depth Based Routing (FDBR) and Depth Based Routing (DBR) in terms of improved parameters related to energy, propagation delay and throughput. Finally, the lifetime of UASN is improved by 70–80% by the implementation of the proposed FLDEAR protocol.
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Sadik Croock, Muayad, and Sahar Salman Mahmood. "Management System of Smart Electric Vehicles Using Software Engineering Model." International journal of electrical and computer engineering systems 13, no. 5 (2022): 369–77. http://dx.doi.org/10.32985/ijeces.13.5.5.
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In this paper, a management system for smart electric vehicle is introduced using software engineering models and installed Sensor Network (SN). Two software engineering models are proposed to construct information exchange and available resource management algorithms, in which the required performance of vehicles is obtained. The resource management algorithm adopts the LeNet-5 deep-learning model in choosing the best driving mode. The datset is achieved from the simulated sensor Network (SN). The results show the satisfied performance of the electric cars in terms of information exchange and resource management. The MQTT broker server is employed for monitoring the information exchange algorithm, where the delay time is less than 1 sec for transmitting 1000 message. The proposed system saves power by 1-8 Kwh and a storage capacity by 9-95 MB for driving 100Km.
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Ntankouo Njila, Roger Cesarié, Mir Abolfazl Mostafavi, and Jean Brodeur. "A Decentralized Fuzzy Rule-Based Approach for Computing Topological Relations between Spatial Dynamic Continuous Phenomena with Vague Boundaries Using Sensor Data." Sensors 21, no. 20 (2021): 6840. http://dx.doi.org/10.3390/s21206840.
Full textAbstract:
Sensor networks (SN) are increasingly used for the observation and monitoring of spatiotemporal phenomena and their dynamics such as pollution, noise and forest fires. In multisensory systems, a sensor node may be equipped with different sensing units to observe and detect several spatiotemporal phenomena at the same time. Simultaneous detection of different phenomena can be used to infer their spatial interactions over space and time. For this purpose, decentralized spatial computing approaches have shown their potential for effective reasoning on spatial phenomena within a sensor network. However, in most cases, spatial extents of continuous dynamic phenomena are uncertain, and their relations and interactions cannot be inferred by the existing approaches at the sensor node level. To address this limitation, in this paper, we propose and develop a decentralized fuzzy rule-based spatial reasoning approach to depict the spatial relations that hold between two evolving spatial phenomena with fuzzy boundaries. The proposed method benefits from a more adapted fuzzy-crisp representation of dynamic phenomena observed by SN where each vague phenomenon is composed of five distinguished zones including the kernel, conjecture and exterior zone and their boundaries. For each detected phenomenon, a sensor node will report one of these zones based on its location. Aggregation of the information reported from the sensor nodes allows reasoning on spatial relations between the observed phenomena and their evolution. Such spatial information provides users with more valuable near real-time information on the state of different phenomena that can be used for informed decision-making.
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Pise, Anil Audumbar, Byungun Yoon, Saurabh Singh, and Jude Imuede. "Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks." Journal of High-Frequency Communication Technologies 2, no. 03 (2024): 186–200. http://dx.doi.org/10.58399/nvdh415.
Full textAbstract:
Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization (PELO) based Cluster head selection (CHs) meant for considering Congestion, Node Degree, Node Density, Network area, Network Coverage, Number of clusters, Number of nodes, Communication cost, Distance, Residual Energy, Distance to neighbor, Node Centrality. Moreover, the Sooty Tern Optimization (STO) model are utilized for the determination of the best routing path for the cluster heads. Taking into account node degree, residual energy, and distance, the STO maximizes network performance. The suggested approach has undergone thorough testing for ensuring network durability and energy efficiency. The proposed model achieved a maximum 97% Packet Delivery Ratio (PDR) with 900 nodes in comparison with 91%, 89%, 83%, and 82% for CRPSH, HQCA, EACRLEACH, and BWO-IACO algorithms respectively.