Gotowe bibliografie tematyczne / Node selection optimization

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Gotowa bibliografia na temat „Node selection optimization”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Node selection optimization"

Cao, Li, Yinggao Yue, and Yong Zhang. "A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization." Computational Intelligence and Neuroscience 2021 (September 29, 2021): 1–13. http://dx.doi.org/10.1155/2021/9808449.

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In the clustering routing protocol, prolonging the lifetime of the sensor network depends to a large extent on the rationality of the cluster head node selection. The selection of cluster heads for heterogeneous wireless sensor networks (HWSNs) does not consider the remaining energy of the current nodes and the distribution of nodes, which leads to an imbalance of network energy consumption. A strategy for selecting cluster heads of HWSNs based on the improved sparrow search algorithm- (ISSA-) optimized self-organizing maps (SOM) is proposed. In the stage of cluster head selection, the propose

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Mrs. T. Nivetha, Dr. K. Prabhavathy. "Cluster Based Improved Particle Swarm Optimization for Optimum Cluster Head Election for Energy Efficient Routing in Wireless Sensor Networks." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 5223–37. http://dx.doi.org/10.52783/tjjpt.v44.i4.1877.

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The proposed methodology addresses critical challenges in Wireless Sensor Networks (WSN), focusing on optimizing cluster head and forwarding node selection. Leveraging an enhanced Particle Swarm Algorithm (PSO), the approach prioritizes residual energy and spatial balance in node selection. It efficiently assigns cluster head nodes to ordinary nodes and selects forwarding nodes within clusters. The algorithm incorporates proximity principles to ensure balanced positioning of nodes. Through iterative iterations, the method refines node selections, favoring candidates with higher residual energy

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Zhang, Tao. "Collaborative Cognitive Wireless Network Optimization Model and Network Parameter Optimization Algorithm." Journal of Electrical and Computer Engineering 2023 (January 13, 2023): 1–11. http://dx.doi.org/10.1155/2023/3748089.

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In recent years, the combination of cognitive radio and collaborative communication has been widely studied and applied because of its ability to increase user throughput and improve spectrum utilization in a flat-fading wireless channel environment. Such cognitive radio networks that use user collaboration to improve channel capacity and spectrum utilization are called collaborative cognitive radio networks. A Nash equilibrium game-based relay node selection algorithm is investigated, which aims to maximize the utility function of primary and cognitive users. Secondly, a Stackelberg game is i

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Bharti, Rajendra Kumar, V. Bhoopathy, Parul Bhanarkar, et al. "Routing Path Selection and Data Transmission in Industry-Based Mobile Communications Using Optimization Technique." Wireless Communications and Mobile Computing 2022 (July 21, 2022): 1–9. http://dx.doi.org/10.1155/2022/5431413.

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In a mobile network, nodes are share data packets; sometimes, that packets are totally flooding. The packet dropping node does not easily detect for routing time instance. The node trust level is minimum causing the packet loss; it affects the entire network performance, and it reduces throughput and increases communication overhead. Proposed exhaustive routing path allocation (ERP) technique is applied to select the legitimate node for broadcasting the data packets completely. The attacker nodes of that flooding packets are detected by using the legitimate detector which are present in networ

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Wang, Ruisong, Gongliang Liu, Wenjing Kang, Bo Li, Ruofei Ma, and Chunsheng Zhu. "Bayesian Compressive Sensing Based Optimized Node Selection Scheme in Underwater Sensor Networks." Sensors 18, no. 8 (2018): 2568. http://dx.doi.org/10.3390/s18082568.

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Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the information by selecting a subset of the total sensor nodes. The conventional compressed sensing scheme is to select some sensor nodes randomly. The network lifetime and the correlation of sensor nodes are not considered. Therefore, it is significant to adjust the sensor node selection scheme according to these factors for the superior performance. In this p

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Parmanand, Parmanand, Sahdev Sahdev, and Anuradha Dwivedi. "Study the optimization of Dijkstra’s Algorithm." Journal of Ravishankar University (PART-B) 37, no. 2 (2024): 255–67. https://doi.org/10.52228/jrub.2024-37-2-18.

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This paper presents an optimized approach to the shortest path problem, a fundamental concern in graph theory, by improving node selection and data storage. The traditional Dijkstra's algorithm is enhanced by introducing a novel node selection strategy that prioritizes nodes with the most significant impact on the shortest path, minimizing redundant calculations and accelerating convergence. Additionally, a compact data storage structure is introduced, reducing memory requirements while maintaining accuracy. This optimized approach offers reduced storage needs, enhanced efficiency, and improve

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Kaur, Sandeep, Dr Rajeev Bedi, and Mohit Marwaha. "Optimization of Energy Efficient Advance Leach Protocol." International Journal on Recent and Innovation Trends in Computing and Communication 9, no. 5 (2021): 07–16. http://dx.doi.org/10.17762/ijritcc.v9i5.5472.

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In WSNs, the only source to save life for the node is the battery consumption. During communication with other area nodes or sensing activities consumes a lot of power energy in processing the data and transmitting the collected/selected data to the sink. In wireless sensor networks, energy conservation is directly to the network lifetime and energy plays an important role in the cluster head selection. A new threshold has been formulated for cluster head selection, which is based on remaining energy of the sensor node and the distance from the base station. Proposed approach selects the clust

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Niu, Haixu, Yonghai Li, Shuaixin Hou, et al. "Topology-Aware Anchor Node Selection Optimization for Enhanced DV-Hop Localization in IoT." Future Internet 17, no. 6 (2025): 253. https://doi.org/10.3390/fi17060253.

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Node localization is a critical challenge in Internet of Things (IoT) applications. The DV-Hop algorithm, which relies on hop counts for localization, assumes that network nodes are uniformly distributed. It estimates actual distances between nodes based on the number of hops. However, in practical IoT networks, node distribution is often non-uniform, leading to complex and irregular topologies that significantly reduce the localization accuracy of the original DV-Hop algorithm. To improve localization performance in non-uniform topologies, we propose an enhanced DV-Hop algorithm using Grey Wo

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R., Saraswathi. "Forward Node Selection Using Particle Swarm Optimization (PSO) for Broadcasting in MANET." Journal of Advanced Research in Dynamical and Control Systems 12, no. 1 (2020): 287–94. http://dx.doi.org/10.5373/jardcs/v12i1/20201042.

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Rathore, Rajkumar Singh, Suman Sangwan, Sukriti Mazumdar, et al. "W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks." Sensors 20, no. 5 (2020): 1377. http://dx.doi.org/10.3390/s20051377.

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Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocat

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Rozprawy doktorskie na temat "Node selection optimization"

Baidas, Mohammed Wael. "Node Selection, Synchronization and Power Allocation in Cooperative Wireless Networks." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26527.

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Recently, there has been an increasing demand for reliable, robust and high data rate communication systems that can counteract the limitations imposed by the scarcity of two fundamental resources for communications: bandwidth and power. In turn, cooperative communications has emerged as a new communication paradigm in which network nodes share their antennas and transmission resources for distributed data exchange and processing. Recent studies have shown that cooperative communications can achieve significant performance gains in terms of signal reliability, coverage area, and power savings

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Oz, M. Tufan. "Optimization Of Selection Conditions And Agrobacterium Mediated Transformation Of Chickpea (cicer Arietinum L. Cv. Gokce)." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/3/12605842/index.pdf.

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The objective of this study was to optimize an efficient selection system and Agrobacterium mediated transformation of chickpea (Cicer arietinum L.). Cotyledonary node explants of Turkish chickpea cultivar G&ouml<br>k&ccedil<br>e were used to determine the effects of selective agents, two antibiotics (Kanamycin, Hygromycin) and two herbicides (PPT, Glyphosate) as well as four antibiotics (Augmentin, Carbenicillin, Cefotaxime, Timentin) for eliminating Agrobacterium on multiple shoot and root induction. Selective agents and antibiotics were applied to explants at different concentrations for

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Części książek na temat "Node selection optimization"

Li, Xiaohua(Edward). "Hop Optimization and Relay Node Selection in Multi-hop Wireless Ad-Hoc Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02080-3_17.

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Xu, Benlian, and Zhiquan Wang. "Bearings-Only Target Tracking Using Node Selection Based on an Accelerated Ant Colony Optimization." In Computational Intelligence and Security. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_129.

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Gao, Yuan, Hong Ao, Weigui Zhou, et al. "A Novel AI Based Optimization of Node Selection and Information Fusion in Cooperative Wireless Networks." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29513-4_2.

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Nithya, K. Jane, and K. Shyamala. "Mean Donkey and Smuggler Optimization (MDSO) Based Cluster Head Selection and Recurrent Neural Network Clone Node Detection (RNNCND) for Wireless Sensor Network (WSN)." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-66410-6_12.

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Acevedo, Javier, Saturnino Maldonado, Sergio Lafuente, Hilario Gomez, and Pedro Gil. "Model Selection for Support Vector Machines Using Ant Colony Optimization in an Electronic Nose Application." In Ant Colony Optimization and Swarm Intelligence. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11839088_47.

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Saha, P., S. Ghorai, B. Tudu, R. Bandyopadhyay, and N. Bhattacharyya. "Optimization of Sensor Array in Electronic Nose by Combinational Feature Selection Method." In Sensing Technology: Current Status and Future Trends II. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02315-1_9.

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Khaddour, Lina A., and Siegfried K. Yeboah. "Multiple-Criteria Optimization of Residential Buildings Envelope Toward nZEBs: Simplified Approach for Damascus Post-war." In Springer Proceedings in Energy. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30960-1_21.

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AbstractSyria faces significant challenges in optimizing residential building energy consumption to subsequently reduce CO2 emissions due to its conventional construction methods and systems, exacerbated by the recent conflict. Post-war re-construction provides new opportunities for improvement in building standards through the 2009 BIC insulation code towards nearly Zero Energy Buildings (nZEBs). However, the decline in economy growth poses significant challenges. In this study, we formulate a simplified building envelope selection approach using multi-criterion optimization methodology based

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Lai Feng-Gang, Li Yu-Tai, and Shang Zhi-Jie. "Quantum Inspired Bee Colony Optimization Based Multiple Relay Selection Scheme." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-722-1-312.

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Multiple relay selection schemes for cooperative relaying considering maximizing the end-to-end signal to noise ratio (SNR) and power efficiency are researched in this paper. In cooperative multiple relay networks, the relay nodes which is selected are very important to the system performance. How to choose the best cooperative relay node number and which relay nodes are selected are an optimization problems. The exhaustive search scheme can solve the relay selection problem but the complexity will increase exponentially with the size of network, that is, the number of relays in the network. T

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Chawra, Vrajesh Kumar, and Govind P. Gupta. "Salp." In Advances in Computer and Electrical Engineering. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1626-3.ch003.

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The formation of the unequal clusters of the sensor nodes is a burning research issue in wireless sensor networks (WSN). Energy-hole and non-uniform load assignment are two major issues in most of the existing node clustering schemes. This affects the network lifetime of WSN. Salp optimization-based algorithm is used to solve these problems. The proposed algorithm is used for cluster head selection. The performance of the proposed scheme is compared with the two-node clustering scheme in the term of residual energy, energy consumption, and network lifetime. The results show the proposed scheme

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Parwekar, Pritee, and Sireesha Rodda. "Optimization of Clustering in Wireless Sensor Networks Using Genetic Algorithm." In Sensor Technology. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2454-1.ch039.

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The energy of a sensor node is a major factor for life of a network in wireless sensor network. The depletion of the sensor energy is dependent on the communication range from the sink. Clustering is mainly used to prolong the life of a network with energy consumption. This paper proposes optimization of clustering using genetic algorithm which will help to minimize the communication distance. The cluster overhead and the active and sleep mode of a sensor is also considered while calculating the fitness function to form the cluster. This approach helps to prolong the network life of sensor net

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Streszczenia konferencji na temat "Node selection optimization"

Wang, Xuan, Ruizhe Yang, Enchang Sun, Yihong Liu, Meng Li, and Tonghui Zhao. "Joint Optimization of Node Selection and Resource Allocation for Sharded Blockchain." In 2024 10th International Conference on Computer and Communications (ICCC). IEEE, 2024. https://doi.org/10.1109/iccc62609.2024.10942082.

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Ma, Sixing, Meng Li, Ruizhe Yang, Yang Sun, and Zhuwei Wang. "Intelligent Node Selection for Ad Hoc Networks-Assisted CBTC Systems Based on Proximal Policy Optimization." In 2024 10th International Conference on Computer and Communications (ICCC). IEEE, 2024. https://doi.org/10.1109/iccc62609.2024.10941915.

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Efendi, Yahya, Arinto Yudi Ponco Wardoyo, and Agus Naba. "Optimization of E-Nose Technology Using Learning Methods based on Feature Selection Algorithm." In 2024 IEEE International Conference on Smart Mechatronics (ICSMech). IEEE, 2024. https://doi.org/10.1109/icsmech62936.2024.10812332.

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Duewall, Clinton M., and Mahmoud M. El-Halwagi. "Constraint Formulations for Bayesian Optimization of Process Simulations: General Approach and Application to Post-Combustion Carbon Capture." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.170471.

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Some of the most highly trusted and ubiquitous process simulators have solution methods that are incompatible with algorithms designed for equation-oriented optimization. The natively unconstrained Efficient Global Optimization (EGO) algorithm approximates a black-box simulation with kriging surrogate models to convert the simulation results into a reduced-order model more suitable for optimization. This work evaluates several established constraint-handling approaches for EGO to compare their accuracy, computational efficiency, and reliability using an example simulation of an amine post-comb

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Sun, Liqun, Yan Cheng, Shibo Wang, Shumin Sun, Xiaoqi Zhang, and Yunhai Lv. "Based on the Bi-level Optimization Framework for Site Selection and Capacity Determination of Renewable Energy Distribution Network Nodes." In 2025 8th International Conference on Energy, Electrical and Power Engineering (CEEPE). IEEE, 2025. https://doi.org/10.1109/ceepe64987.2025.11034061.

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Meng, Xiance, and Mangui Liang. "Node Selection-Based Anonymous Network Performance Optimization Method." In 2024 9th International Conference on Computer and Communication Systems (ICCCS). IEEE, 2024. http://dx.doi.org/10.1109/icccs61882.2024.10602902.

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Liu, Hongyu, Haoyang Liu, Yufei Kuang, Jie Wang, and Bin Li. "Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics." In GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion. ACM, 2024. http://dx.doi.org/10.1145/3638530.3664128.

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Wang Jia-ren, Dong En-qing, Qiao Fu-long, and Zou Zong-jun. "Wireless sensor networks node localization via Leader Intelligent Selection optimization algorithm." In 2013 19th Asia-Pacific Conference on Communications (APCC). IEEE, 2013. http://dx.doi.org/10.1109/apcc.2013.6766033.

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Dongare, Mahendra, Satish Jondhale, and Balasaheb Agarkar. "Energy-Efficient Approach for Node Selection in Routing Protocols of Wireless Sensor Networks." In 2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT). IEEE, 2024. http://dx.doi.org/10.1109/icdcot61034.2024.10515331.

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Wang, Yu, Wenbin Zhou, and Fanfan Zhou. "Volunteer Sensor Networks Node Availability Prediction via Stronger Intelligent Selection Optimization Algorithm." In 2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA). IEEE, 2014. http://dx.doi.org/10.1109/bwcca.2014.47.

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Raporty organizacyjne na temat "Node selection optimization"

Weller, Joel I., Ignacy Misztal, and Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, 2015. http://dx.doi.org/10.32747/2015.7594404.bard.

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The main objectives of this research was to detect the specific polymorphisms responsible for observed quantitative trait loci and develop optimal strategies for genomic evaluations and selection for moderate (Israel) and large (US) dairy cattle populations. A joint evaluation using all phenotypic, pedigree, and genomic data is the optimal strategy. The specific objectives were: 1) to apply strategies for determination of the causative polymorphisms based on the “a posteriori granddaughter design” (APGD), 2) to develop methods to derive unbiased estimates of gene effects derived from SNP chips

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