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Artykuły w czasopismach na temat „Node selection optimization”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

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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S., J. Patil, Admuthe L.S., and R. Patil M. "CLBNSRM - CONFIDENCE LEVEL BASED UNBLEND NEIGHBOR SELECTION &BLEND NODE REPORT BASED OPTIMIZED ROUTE FORMATION IN MANET." International Journal of Computer Networks & Communications (IJCNC) 12, no. 2 (2020): 109–29. https://doi.org/10.5281/zenodo.3837058.

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A mobile Ad-hoc network (MANET) is an impulsive network that can be recognized with no predetermined infrastructure. To achieve safe path selection cryptographic key exchange was implemented mostly in turn of huge computational cost. Confidence based coordination in MANET focuses on routing challenges created by selfish nodes, as energy utilization & time factor are key issues in this aspect. The present protocol is focused on fuzzy optimization-based node confidence estimation and path selection with minimum energy utilization. The node with maximum confidence value will give high priorit

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Shaheen, Aaina, and Poonam Ghai. "An Energy Efficient Clustering Protocol Using CM-YSGA Optimization Approach in WSN." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 1705–12. http://dx.doi.org/10.22214/ijraset.2022.42635.

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Abstract: While dealing with the wireless sensor networks (WSNs), one of the greatest factors that must be taken into consideration is energy consumption of nodes. One of the most effective common way of preserving energy in sensor nodes is clustering technique in which CH selection is of great importance. In this manuscript, an improved energy efficient clustering protocol is proposed in which chaotic mapping algorithm is clubbed along with the advanced variant of Yellow Saddle Goatfish Algorithm (YSGA). The main objective of the proposed model is to reduce the energy consumption of nodes whi

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Kurnosov, M., and E. Tokmasheva. "Barrier Optimization on Asymmetrical NUMA Subsystems." Herald of the Siberian State University of Telecommunications and Informatics, no. 1 (March 18, 2021): 36–49. http://dx.doi.org/10.55648/1998-6920-2021-15-1-36-49.

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Algorithm MinNumaDist for barrier’s root selection is proposed. A root process allocates memory pages for shared counters and flags from its NUMA node. Total distance is minimized to all NUMA nodes (closeness centrality) by the algorithm. MinNumaDist reduces barrier’s time by 1035% for asymmetrical NUMA subsystems - for different number of processes on NUMA nodes or different number of NUMA nodes used from each socket.

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Ma, Chang Wei. "Coverage Optimization Mechanism Based on Weighted Genetic Algorithm and Constrained Genetic Algorithm." Applied Mechanics and Materials 416-417 (September 2013): 1574–79. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.1574.

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As a basic problem of wireless sensor in network applications, coverage reflects the quality effect of monitoring and tracking of the network. In view of the high density of sensor nodes deployment, this article works on the node set selection problem, puts forward two kinds of coverage optimization mechanisms based on weighted genetic algorithm and constrained genetic algorithm according to the genetic algorithm operation of the fitness function generation, and calculates approximately optimal working nodes required in the sensor network fully covering area. The simulation results show that t

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K B, Manikandan. "SWARM OPTIMIZATION BASED IMPOSTER NODES AND RESOURCE LIMITATION AWARE NODE FAILURE DETECTION." ICTACT Journal on Communication Technology 11, no. 2 (2020): 2163–71. https://doi.org/10.21917/ijct.2020.0319.

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This research work studies about node failures, which can be prevented pretty good by providing the necessary resources rather than by establishing a route path again. This is done by clustering the mobile nodes in accordance with the on node significance level like it is done in the earlier work and the resources among the cluster members are shared with one another to guarantee that sufficient resources are made available. The cluster is established using the Fuzzy K-means clustering technique. The cluster head is accountable for selecting those clusters members, which can share their resour

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Rai, Ashok Kumar, Lalit Kumar Tyagi, Anoop Kumar, Swapnita Srivastava, and Naushen Fatima. "Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 12, no. 1 (2023): e30632. http://dx.doi.org/10.14201/adcaij.30632.

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Wireless sensor networks (WSNs) are typically made up of small, low-power sensor nodes (SNs) equipped with capability for wireless communication, processing, and sensing. These nodes collaborate with each other to form a self-organizing network. They can collect data from their surrounding environment, such as temperature, humidity, light intensity, or motion, and transmit it to a central base station (BS) or gateway for additional processing and analysis. LEACH and TSEP are examples of cluster-based protocols developed for WSNs. These protocols require careful design and optimization of CH se

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Shashidhar, P. K., T. C. Thanuja, and Rajashekar Kunabeva. "Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT." Indian Journal Of Science And Technology 17, no. 5 (2024): 436–50. http://dx.doi.org/10.17485/ijst/v17i5.2627.

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Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The

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Hu, Aihua, Zhongliang Deng, Jianke Li, Yao Zhang, Yuhui Gao, and Di Zhao. "Optimization Selection Method of Post-Disaster Wireless Location Detection Equipment Based on Semi-Definite Programming." Electronics 11, no. 14 (2022): 2170. http://dx.doi.org/10.3390/electronics11142170.

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Signal propagation attenuation is greater in the post-disaster collapsed environment than that it is indoor or outdoor. The transmission environment is seriously affected by multi-path and non-line-of-sight transmission. When the signals penetrate the ruins and reach the receiver, their power may become very weak, which greatly affects the success rate of signal acquisition by the receiver. In the post-disaster environment, wireless signal propagation is severely blocked, which leads to serious signal attenuation and non-line-of-sight propagation, and signal acquisition distance and direction

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Venkatasubramanian, S., A. Suhasini, and C. Vennila. "Cluster Head Selection and Optimal Multipath detection using Coral Reef Optimization in MANET Environment." International Journal of Computer Network and Information Security 14, no. 3 (2022): 88–99. http://dx.doi.org/10.5815/ijcnis.2022.03.07.

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Mobile Ad-hoc Network (MANET) data transfer between nodes in a multi-hop way offers a wide variety of applications. The dynamic feature of ad hoc network mobile nodes is primarily influenced by safety issues, which limit data forwarding rate in multipath routing. As a supplementary method to improve safe data delivery in a MANET, this paper propose and analyse the cluster head (CH) selection and optimum multipath scheme. The CHs are chosen based on the possibility values of each node in MANET, which are considered from the residual energy of each node. During the present phase, the total remai

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Yamada, Keigo, Yasuo Sasaki, Takayuki Nagata, Kumi Nakai, Daisuke Tsubakino, and Taku Nonomura. "Efficient Sensor Node Selection for Observability Gramian Optimization." Sensors 23, no. 13 (2023): 5961. http://dx.doi.org/10.3390/s23135961.

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Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-invariant, and discrete-time dynamical system are examined under the assumption of independent and identically distributed measurement noise. This study offers two novel selection algorithms, namely an approximate convex relaxation method with the Newton method and a gradient greedy method, and confirms the performance of the selection methods, including a convex relaxation method with semidefinite programming (SDP) and a pure greedy optimization method proposed in the previous studies. The matrix deter

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Liu, Chao, Qinghua Luo, Xiaozhen Yan, Yang Shao, Kexin Yang, and Chunyu Ju. "A distributed localization method for mobile nodes." IOP Conference Series: Materials Science and Engineering 1207, no. 1 (2021): 012001. http://dx.doi.org/10.1088/1757-899x/1207/1/012001.

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Abstract In Wireless Sensor Networks(WSNs), the location services are the basis of many application scenarios. However, for the range-based localization method, the localization accuracy and the system robustness of the distributed localization system are difficult to guarantee, due to the uncertainty of the distance estimation and position calculation are affected by the node state and communication uncertainty. In this paper, we propose the distributed localization method based on anchor node selection and Particle Filter optimization. In this method, we analyze the uncertainty of error prop

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Vijay Rathod, Et al. "A Network-Centred Optimization Technique for Operative Target Selection." Journal of Electrical Systems 19, no. 2 (2024): 87–96. http://dx.doi.org/10.52783/jes.694.

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The process of accomplishing strategic objectives by concentrating on effects as opposed to attrition-based destruction is known as effects-based operations, or EBO. Finding important nodes in an adversary network is a critical step in the EBO process for a successful implementation. In this paper, propose a network-based method to identify the most influential nodes by combining network centrality and optimization. To determine the node influence, the adversary's network structure is analyzed using degree and between centralities. Given the dynamic nature of the adversary network struct[1]ure

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Wang, Shenglong, Jing Yang, Xiaoyu Ding, and Meng Zhao. "Detecting local communities in complex network via the optimization of interaction relationship between node and community." PeerJ Computer Science 9 (May 15, 2023): e1386. http://dx.doi.org/10.7717/peerj-cs.1386.

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The goal of local community detection algorithms is to explore the optimal community with a reference to a given node. Such algorithms typically include two primary processes: seed selection and community expansion. This study develops and tests a novel local community detection algorithm called OIRLCD that is based on the optimization of interaction relationships between nodes and the community. First, we introduce an improved seed selection method to solve the seed deviation problem. Second, this study uses a series of similarity indices to measure the interaction relationship between nodes

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Du, Yong-wen, Zhang-min Wang, Gang Cai, and Jun-hui Gong. "Load-balanced routing algorithm based on cluster heads optimization for wireless sensor networks." MATEC Web of Conferences 232 (2018): 04050. http://dx.doi.org/10.1051/matecconf/201823204050.

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In order to solve the problem of unbalanced load consumption of nodes for wireless sensor networks (WSNs), this paper proposes a load-balanced routing algorithm based on cluster heads optimization for wireless sensor network. The proposed algorithm first applies first-order wireless transmission model to calculate the optimal number of clusters, then calculate nodes competitiveness rating by fuzzy algorithm considering the residual energy of node and distance from the node to base station, cluster head selection uses unequal clustering algorithm according to the competitiveness of nodes. By no

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Jabeen, Tayyaba, Zain Ali, Wali Ullah Khan, et al. "Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network." Electronics 8, no. 6 (2019): 686. http://dx.doi.org/10.3390/electronics8060686.

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In this paper, we present a joint power allocation and adaptive link selection protocol for an orthogonal frequency division multiplexing (OFDM)-based network consists of one source node i.e., base station (BS), one destination node i.e., (MU) and a buffer aided decode and forward (DF) relay node. Our objective is to maximize the average throughput of the system via power loading over different subcarriers at source and relay nodes. A separate power budget is assumed at each transmitting node to make the system more practical. In order to form our solution more tractable, a decomposition frame

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Wang, Kuiwu, Qin Zhang, Guimei Zheng, and Xiaolong Hu. "Multi-Target Tracking AA Fusion Method for Asynchronous Multi-Sensor Networks." Sensors 23, no. 21 (2023): 8751. http://dx.doi.org/10.3390/s23218751.

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Aiming at the problem of asynchronous multi-target tracking, this paper studies the AA fusion optimization problem of multi-sensor networks. Firstly, each sensor node runs a PHD filter, and the measurement information obtained from different sensor nodes in the fusion interval is flood communicated into composite measurement information. The Gaussian component representing the same target is associated with a subset by distance correlation. Then, the Bayesian Cramér–Rao Lower Bound of the asynchronous multi-target-tracking error, including radar node selection, is derived by combining the comp

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S, Silambarasan, and M. Savitha Devi. "ENHANCED LION SWARM OPTIMIZATION ALGORITHM WITH CENTRALIZED AUTHENTICATION APPROACH FOR SECURED DATA TRANSMISSION OVER WSN." ICTACT Journal on Communication Technology 12, no. 3 (2021): 2471–79. http://dx.doi.org/10.21917/ijct.2021.0365.

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Securing data accuracy in WSNs (Wireless Sensor Networks) is a major problem. Aggregation techniques for improving accuracy in data processing have been gaining attention of scholars, recently. Existing security systems using singular paths for transmission of data have delays in transmissions while being open to intrusions. Moreover, increased computational overheads and processing time increases the delay of data transmission in the given networks. To overcome these issues, this work proposes ELSOA-CA (Enhanced Lion Swarm Optimization Algorithm and Centralized Authentication) method. This me

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Chung, Vincent, Hamzarul Alif Hamzah, Norah Tuah, Kit Guan Lim, Min Keng Tan, and Kenneth Tze Kin Teo. "CLUSTER HEAD SELECTION OPTIMIZATION IN WIRELESS SENSOR NETWORK VIA GENETIC-BASED EVOLUTIONARY ALGORITHM." ICTACT Journal on Communication Technology 11, no. 4 (2020): 2301–9. https://doi.org/10.21917/ijct.2020.0340.

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Wireless sensor network (WSN) is an embedded system comprises of spatially distributed sensor nodes where an energy-efficient mechanism is needed to prolong the network lifetime. Existing approaches for this optimization problem have several drawbacks, including non-adaptive network configuration that may cause premature death of sensor nodes. Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. Therefore, the per

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Yang, Cheng, Fei Zheng, Yujie Zou, et al. "MSGL+: Fast and Reliable Model Selection-Inspired Graph Metric Learning." Electronics 13, no. 1 (2023): 44. http://dx.doi.org/10.3390/electronics13010044.

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The problem of learning graph-based data structures from data has attracted considerable attention in the past decade. Different types of data can be used to infer the graph structure, such as graphical Lasso, which is learned from multiple graph signals or graph metric learning based on node features. However, most existing methods that use node features to learn the graph face difficulties when the label signals of the data are incomplete. In particular, the pair-wise distance metric learning problem becomes intractable as the dimensionality of the node features increases. To address this ch

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Nalinipriya, G., M. Geetha, D. Sudha, and T. Daniya. "Fuzzy Neighbors and Deep Learning-Assisted Spark Model for Imbalanced Classification of Big Data." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 31, no. 01 (2023): 141–62. http://dx.doi.org/10.1142/s0218488523500095.

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Big data is important in knowledge manipulation, assessment, and prediction. However, extracting and analyzing knowledge through big database are complex because of imbalance data distribution that leads to wrong decisions and biased classification outputs. Hence, an effective and optimal big data classification approach is designed using the proposed Bird Swarm Deer Hunting Optimization-Deep Belief Network (BSDHO-based DBN) algorithm based on spark architecture that follows the master and slave nodes. The proposed BSDHO is obtained by combining Deer Hunting Optimization algorithm and Bird Swa

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Cui, Huanqing, Yongquan Liang, Chuanai Zhou, and Ning Cao. "Localization of Large-Scale Wireless Sensor Networks Using Niching Particle Swarm Optimization and Reliable Anchor Selection." Wireless Communications and Mobile Computing 2018 (December 2, 2018): 1–18. http://dx.doi.org/10.1155/2018/2473875.

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Due to uneven deployment of anchor nodes in large-scale wireless sensor networks, localization performance is seriously affected by two problems. The first is that some unknown nodes lack enough noncollinear neighbouring anchors to localize themselves accurately. The second is that some unknown nodes have many neighbouring anchors to bring great computing burden during localization. This paper proposes a localization algorithm which combined niching particle swarm optimization and reliable reference node selection in order to solve these problems. For the first problem, the proposed algorithm

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Singh, Ravinder, and Rajdavinder Singh Boparai. "Dynamic Clustering and Cluster Head Selection for Energy Optimization under Wireless Sensor Network." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 1 (2018): 84. http://dx.doi.org/10.23956/ijarcsse.v8i1.529.

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Wireless sensor network is a field of networking that has been used for sensing information from environment. In WSN the sensor nodes are attached to a battery for sensing information. Each node utilizes three types of energy during its lifetime over the network. These energies are sensing energy, transmission or receiving energy and idle energy. During the sensing information the nodes consumes energy and transmission energy is used to transmit a data over a distance. Idle energy is that when node is not working but remains in on state. Due to deployment of WSN in unreachable area energy is m

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Xiang Xu, Xiang Xu, 李儀 Xiang Xu, and Yi-Fan Wang Yi Li. "Particle Swarm Optimization with Long and Short Term Memory in Feature Selection." 電腦學刊 33, no. 5 (2022): 121–33. http://dx.doi.org/10.53106/199115992022103305011.

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<p>Taking each iteration of Particle swarm optimization (PSO) algorithm as a time node, the change of population in PSO algorithm can be regarded as a time series model. Particle population learns and evolves in multiple time nodes, which can be regarded as a dependent behavior on leader particles. In the traditional particle swarm optimization algorithm, this dependence behavior is independent of time, and its consideration standard is only the fitness value of particles. We deeply study the leadership mechanism of PSO algorithm in order to find a more robust leadership mechanism and im

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Maina Mwangi, Peter, John Gichuki Ndia, and Geoffrey Muchiri Muketha. "AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CONSUMPTION IN WIRELESS SENSOR NETWORKS." International Journal of Network Security & Its Applications 15, no. 03 (2023): 65–83. http://dx.doi.org/10.5121/ijnsa.2023.15305.

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Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm selection opt

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Peter, Maina Mwangi, Gichuki Ndia John, and Muchiri Muketha Geoffrey. "AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CONSUMPTION IN WIRELESS SENSOR NETWORKS." International Journal of Network Security & Its Applications (IJNSA) 15, no. 3 (2023): 65–83. https://doi.org/10.5281/zenodo.8072861.

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Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm s

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Yu, Guoqing, Hongtao Ma, and Deden Witarsyah. "Optimal path selection algorithm for mobile beacons in sensor network under non-dense distribution." Open Physics 16, no. 1 (2018): 1066–75. http://dx.doi.org/10.1515/phys-2018-0127.

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Abstract When the traditional anchor aided location algorithm is used to select the mobile beacon path in the sensor network, there is no analysis of the energy imbalance of nodes in non-dense conditions, the optimal network node cannot be selected, and the selection error of the optimal path of the beacon is larger. A path selection algorithm for mobile beacons in a sensor network under non-dense distribution is proposed. Using the mobile beacon based wireless sensor network location algorithm, the weighted centroid algorithm and the extended Kalman filter (EKF) are used to obtain the accurat

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Balaram, Allam, Rajendiran Babu, Miroslav Mahdal, et al. "Enhanced Dual-Selection Krill Herd Strategy for Optimizing Network Lifetime and Stability in Wireless Sensor Networks." Sensors 23, no. 17 (2023): 7485. http://dx.doi.org/10.3390/s23177485.

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Wireless sensor networks (WSNs) enable communication among sensor nodes and require efficient energy management for optimal operation under various conditions. Key challenges include maximizing network lifetime, coverage area, and effective data aggregation and planning. A longer network lifetime contributes to improved data transfer durability, sensor conservation, and scalability. In this paper, an enhanced dual-selection krill herd (KH) optimization clustering scheme for resource-efficient WSNs with minimal overhead is introduced. The proposed approach increases overall energy utilization a

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Rani, Anju, and Amit Kumar Bindal. "Optimization of Energy Conservation in Wireless Sensor Networks." Journal of Computational and Theoretical Nanoscience 17, no. 6 (2020): 2658–63. http://dx.doi.org/10.1166/jctn.2020.8962.

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Presently, Wireless Sensor Networks (WSNs) is quickest developing technology which broadly embracing for different application services including; climate observing, traffic expectation, reconnaissance, research and scholastic fields and so on. As the sensor nodes are haphazardly conveyed in remote condition, security measurements turns out to be most encouraging test where correspondence wirelesses systems confronting today. The Stable Election Protocol (SEP) is an enhanced algorithm of Adaptive Clustering Hierarchy (LEACH) with low energy in heterogeneous Wireless Sensor Network (WSN) for im

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Zheng, Xiandong, Wenlong Feng, Mengxing Huang, and Siling Feng. "Optimization of PBFT Algorithm Based on Improved C4.5." Mathematical Problems in Engineering 2021 (March 3, 2021): 1–7. http://dx.doi.org/10.1155/2021/5542078.

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Aiming at the problems of PBFT algorithm of consortium blockchain, such as high communication overhead, low consensus efficiency, and random selection of leader nodes, an optimized algorithm of PBFT is proposed. Firstly, the algorithm improves C4.5 and introduces weighted average information gain to overcome the mutual influence between conditional attributes and improve the classification accuracy. Then classify the nodes with improved C4.5, and select the ones with a high trust level to form the main consensus group. Finally, the integral voting mechanism is introduced to determine the leade

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Jiang, Dexia, and Leilei Li. "Node Selection Algorithm for Network Coding in the Mobile Wireless Network." Symmetry 13, no. 5 (2021): 842. http://dx.doi.org/10.3390/sym13050842.

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In the multicast network, network coding has proven to be an effective technique to approach maximum flow capacity. Although network coding has the advantage of improving performance, encoding nodes increases the cost and delay in wireless networks. Therefore, minimizing encoding nodes is of great significance to improve the actual network’s performance under a maximum multicast flow. This paper seeks to achieve partial improvements in the existing selection algorithm of encoding nodes in wireless networks. Firstly, the article gives the condition for an intermediate node to be an encoding nod

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Gao, He, Jun Li, Fu Qiang Zhou, Rong Zou, and Yi Cui. "Outage Probability Analysis and Adaptive Power Allocation for ISDF MIMO Cooperation Systems." Applied Mechanics and Materials 58-60 (June 2011): 2296–302. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2296.

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The outage probability performance is analyzed for the optimization of incremental selection decode-amplify-forward (ISDF) multi-node MIMO cooperative communication systems. Firstly, the system model for the proposed multi-node MIMO cooperative protocol. Then, the incremental selection decode-amplify-forward and optimal relay selection strategy (routing) based on the opportunistic relaying scheme is proposed. The mutual information and outage probability between source and destination nodes for the proposed scheme are formulated with the relays have the capability of maximum ratio combining (M

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Saadi, Amnah A., and Osama A. Awad. "LIFETIME MAXIMIZATION OF A MOBILE WSN USING ZRP-FUZZY CLUSTERING PROTOCOL BASED ON ANT-LION OPTIMIZER." Iraqi Journal of Information and Communications Technology 1, no. 1 (2021): 70–82. http://dx.doi.org/10.31987/ijict.1.1.171.

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Wireless Sensor Networks require energy-efficient protocols for communication and data fusion to integrate data and extend the lifetime of the network. An efficient clustering algorithm for sensor nodes will optimize the energy efficiency of WSNs. However, the clustering process requires additional overhead, such as selection of cluster head, cluster creation, and deployment. This paper prepared a modified ZRP for mobile WSN clustering scheme and optimization using ant-lion optimization algorithm and so far named as mobility cluster head fuzzy logic based on the zone routing protocol (ZRP-FMC-

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Jabbar, Sohail, Rabia Iram, Muhammad Imran, et al. "Energy Aware Simple Ant Routing Algorithm for Wireless Sensor Networks." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/194532.

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Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases

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Xing, Xiaoyou, Zhiwen Zhong, Xueting Li, and Yiyang Yue. "Node Selection and Path Optimization for Passive Target Localization via UAVs." Sensors 25, no. 3 (2025): 780. https://doi.org/10.3390/s25030780.

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The performance of passive target localization is affected by the positions of unmanned aerial vehicles (UAVs) at a large scale. In this paper, to improve resource utilization efficiency and localization accuracy, the node selection problem and the path optimization problem are jointly investigated. Firstly, the target passive localization model is established and the Chan-based time difference of arrival (TDOA) localization method is introduced. Then, the Cramer–Rao lower bound (CRLB) for Chan-TDOA localization is derived, and the problems of node selection and path optimization are formulate

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Samuel, Rajula Angelin, and D. Shalini Punithavathani. "Designing a New Scalable Autoconfiguration Protocol with Optimal Header Selection for Large Scale MANETs." Journal of Circuits, Systems and Computers 29, no. 05 (2019): 2050068. http://dx.doi.org/10.1142/s0218126620500681.

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Autoconfiguration in mobile ad hoc network (MANET) is a challenging task to be accomplished in hostile environment. Moreover, a mobile node in MANET is usually configured with a unique IP address for providing better communication and to connect it with an IP network. Essentially, the nodes in wired networks are autoconfigured using a commonly known Dynamic Host Configuration Protocol (DHCP) server. However, MANET exhibits the intrinsic characteristics (i.e., distributed, dynamic and multi-hop) in nature; hence, it is hard to adopt DHCP server for autoconfiguration of nodes in MANET without ap

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Yang, Dingcheng, Chuanqi Zhu, Lin Xiao, Xiaomei Shen, and Tiankui Zhang. "An Energy-Efficient Scheme for Multirelay Cooperative Networks with Energy Harvesting." Mobile Information Systems 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/5618935.

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This study investigates an energy-efficient scheme in multirelay cooperative networks with energy harvesting where multiple sessions need to communicate with each other via the relay node. A two-step optimal method is proposed which maximizes the system energy efficiency, while taking into account the receiver circuit energy consumption. Firstly, the optimal power allocation for relay nodes is determined to maximize the system throughput; this is based on directional water-filling algorithm. Secondly, using quantum particle swarm optimization (QPSO), a joint relay node selection and session gr

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Wang, Zhen, Jin Duan, Haobo Xu, Xue Song, and Yang Yang. "Enhanced Pelican Optimization Algorithm for Cluster Head Selection in Heterogeneous Wireless Sensor Networks." Sensors 23, no. 18 (2023): 7711. http://dx.doi.org/10.3390/s23187711.

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In the research of heterogeneous wireless sensor networks, clustering is one of the most commonly used energy-saving methods. However, existing clustering methods face challenges when applied to heterogeneous wireless sensor networks, such as energy balance, node heterogeneity, algorithm efficiency, and more. Among these challenges, a well-designed clustering approach can lead to extended node lifetimes. Efficient selection of cluster heads is crucial for achieving optimal clustering. In this paper, we propose an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS) to

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Bhanu, Nageswaran Usha, Prathaban Banu Priya, Tiruveedhula Sajana, et al. "Dingo algorithm-based forwarder selection and huffman coding to improve authentication." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 1 (2023): 432. http://dx.doi.org/10.11591/ijeecs.v32.i1.pp432-440.

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<span>In wireless sensor network (WSN), the high volume of observe and transmitted data among sensor nodes make it requires to maintain the security. Even though numerous secure data transmission approaches designed over a network, an inadequate resource and the complex environment cause not able to used in WSNs. Moreover, secure data communication is a big challenging problem in WSNs especially for the military application. This paper proposes a dingo algorithm-based forwarder selection and huffman coding (DAHC) to improve authentication in internet of things (IoT) WSN. Initially, it de

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Guo, Kai, and Yang Lv. "Optimizing Routing Path Selection Method Particle Swarm Optimization." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 12 (2020): 2059042. http://dx.doi.org/10.1142/s0218001420590429.

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In view of the two shortcomings of the AODV routing protocol, they do not consider the bandwidth, delay and cost in the actual network, and the routing table has only one path from the basic node to the target node. This paper attempts to improve the AODV protocol by using particle swarm optimization. Through simulation experiments, this paper compares four improved particle swarm optimization algorithms, inertia weight, linear decline, shrinkage factor and chaos, and finds that ACPSO can find the optimal path faster and transmit data quickly. So, this paper uses chaotic particle swarm optimiz

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Shashi, Raj K., and G. K. Siddesh. "MULTI-OBJECTIVE OPTIMIZATION ASSISTED NETWORK CONDITION AWARE QOS-ROUTING PROTOCOL FOR MANETS: MNCQM." International Journal of Computer Networks & Communications (IJCNC) 11, no. 4 (2019): 1–23. https://doi.org/10.5281/zenodo.3361215.

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The exponential rise in wireless communication systems and allied applications has revitalized academiaindustries to achieve more efficient data transmission system to meet Quality-of-Service (QoS) demands. Amongst major wireless communication techniques, Mobile Ad-hoc Network (MANET) is found potential to provide decentralized and infrastructure less communication among multiple distributed nodes across network region. However, dynamic network conditions such as changing topology, congestion, packet drop, intrusion possibilities etc often make MANET’s routing a tedious task. On the othe

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