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1
Rehman, Eid, Muhammad Sher, Syed Hussnain Abbas Naqvi, Khan Badar Khan, and Kamran Ullah. "Energy Efficient Secure Trust Based Clustering Algorithm for Mobile Wireless Sensor Network." Journal of Computer Networks and Communications 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/1630673.
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The main benefit of selecting a suitable node as cluster head (CH) in clustering for wireless mobile sensor networks (MWSNs) is to prolong the network lifetime. But the safe selection of CH is a challenging task by taking security into account. Mostly CH selection algorithms in MWSN do not consider security when selecting CH. We have proposed secure CH selection algorithm by calculating weight of each node to deal with secure selection using minimum energy consumption. The weight of node is a combination of different metrics including trust metric (behaviors of sensor node) which promotes a secure decision of a CH selection; in terms of this, the node will never be a malicious one. The trust metric is definitive and permits the proposed clustering algorithm to keep away from any malignant node in the area to select a CH, even if the rest of the parameters are in its favor. Other metrics of node include waiting time, connectivity degree, and distance among nodes. The selection of CHs is completed utilizing weights of member nodes. The preparatory outcomes acquired through simulation exhibit the adequacy of our proposed scheme as far as average rate of avoiding malicious node as a CH, energy efficiency, and some other performance parameters are concerned.
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Fallo, Kristoforus, Waskitho Wibisono, and Kun Nursyaful Priyo Pamungkas. "Pengembangan mekanisme grid based clustering untuk peningkatan kinerja LEACH pada lingkungan Wireless Sensor Network." Register: Jurnal Ilmiah Teknologi Sistem Informasi 5, no. 2 (July 1, 2019): 164. http://dx.doi.org/10.26594/register.v5i2.1708.
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Development of a grid-based clustering mechanism to improve LEACH performance in the Wireless Sensor Network environmentLow Energy Adaptive Clustering Hierarchy (LEACH) merupakan algoritma routing pada Wireless Sensor Network (WSN) berbasis cluster. LEACH memilih sebuah node sebagai cluster head (CH) yang tugasnya untuk melakukan komunikasi dengan sink maupun guna mengumpulkan data dari member node. Persebaran CH pada LEACH yang dikatakan acak, kadang mengalami masalah mengingat rumus probabilitas pada tiap round. Hal ini akan menyebabkan CH yang terpilih bisa berada di tepi area, juga terjadinya pemborosan energi karena jalur yang terbentuk akan menjadi panjang. Oleh karena itu, kami ingin mengembangkan routing protocol G-LEACH menggunakan teknik merge CH dalam suatu area (grid) disertai beberapa parameter yang relevan, seperti posisi node, node dengan sisa energi terbesar, dan jarak yang dihitung dalam tiga jarak yaitu jarak node menuju cluster center, jarak node menuju merge CH, dan jarak merge CH menuju sink. Hasil pengujian menunjukan bahwa dengan menggabungkan cluster (merge CH) pada transmisi data menuju sink pada protokol G-LEACH dapat menghasilkan masa hidup jaringan yang lebih lama pada seluruh operasi node, energi yang dibutuhkan pada semua node lebih rendah, dan lebih banyak paket data yang dikirim dan diterima oleh sink. Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing algorithm in a cluster-based Wireless Sensor Network (WSN). LEACH selects a node as a cluster head (CH) whose responsibility is for communicating with sinks and collect data from the node members. The distribution of CH on LEACH, which is basically random, sometimes has a problem in remembering the probability formula on each round. This may make the selected CH on the edge of the area as well as generate energy waste because the pathway formed will be lengthy. Therefore, we would like to develop the G-LEACH routing protocol using a merge CH technique in one area (grid) with several relevant parameters, such as the position of the node, the node with the largest remaining energy, and the distance calculated in three distances: the distance of the node to the clustercenter, the distance of the node to the merge CH, and the distance of the merge CH to the sink. The test result showed that combining clusters (merge CH) in the data transmission to the sink in the G-LEACH protocol could produce a longer network life on all node operations, lower energy required for all nodes, and more data package sent and received by the sink.
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Et. al., Heba Hussain Hadi,. "Energy Efficient Routing Protocall By One Way Multi-Hope Sensor Nodes." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 7 (June 13, 2021): 3401–10. http://dx.doi.org/10.17762/turcomat.v12i7.4540.
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Multi-hope is widely used for data aggregation and transmission in various applications. The resource availability determines the life time of a WSN. Sensor nodes are powered by a tiny battery that supplies the required energy for the sensor and transmitter. The residual energy available at any moment decides the fitness of the sensor node. The sensor node senses the environment and transmits the data to the sink. Efficient data transmission and aggregation with less energy consumption can prolong the lifetime of the sensor network. The sensor node that is inside the coverage area of the sink can directly transmit the data to sink in a single-hop transmission. The sensor node that is not inside the coverage area should transmit the data to the neighbor node which is in the coverage area of the sink. The data is then turn transmitted by the node close to it fall in multi-hop transmission involving a number of intermediate nodes to forward the data to the sink and consumes extra energy for the forwarding process. The formation clusters and data transmission of data by Cluster Heads (CH) can eliminate many nodes involved in the transmission of same data. Clusters are a group of self-organized nodes in a geographic location that can communicate among them. A node in a cluster with higher residual energy will be acting as CH and all other nodes in the cluster transmit the data to the CH. The CH transmits the aggregated data to the sink. The CH transmits the data to the sink either in single-hop transmission or multi-hop transmission. The cluster head consumes more energy than other nodes in the cluster as it is involved in aggregation and transmission process.
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Mote, Tushar S., and S. K. Jagtap. "Adaptive Threshold Residual Energy-Based Efficient Sensor Network Protocol (ATREEN)." Journal of Sensors 2023 (July 26, 2023): 1–7. http://dx.doi.org/10.1155/2023/1629438.
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Wireless sensor network (WSN) hierarchical (clustering) routing involves the gathering of sensor nodes to form clusters in which sensor node communicates to cluster head (CH). The CH is responsible for data aggregation and forwarding collected data toward base station (BS). Energy expenditure in usual protocols becomes unequal because of clusters having diverse lengths. In this paper, we propose another new enhanced clustering protocol called adaptive threshold residual energy-based efficient sensor network protocol (ATREEN) for adaptive selection of CH in WSNs. In ATREEN, CHs are chosen by comparing threshold of node value with respect to distance between cluster member and CH, residual energy of sensor nodes, and position of sensor node with respect to BS. Simulation results show that ATREEN protocol extends network lifetime and stability with decline in energy dissipation compared to clustering protocols such as low-energy adaptive clustering hierarchy (LEACH), power-efficient gathering in sensor information systems (PEGASIS), and distributed energy-efficient clustering (DEEC) scheme for heterogeneous WSNs.
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Fallo, Kristoforus, and Budiman Baso. "Analisis Perbandingan Teknik Pemilihan Cluster Head Pada Wireless Sensor Network Berbasis Clustering Menggunakan Algoritma Routing Protocol LEACH dan G-LEACH." Journal of Information and Technology 3, no. 1 (February 27, 2023): 1–5. http://dx.doi.org/10.32938/jitu.v3i1.3795.
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Wireless Sensor Network (WSN) is a series of wireless networks consisting of several nodes in a limited area. Low Energy Adaptive Clustering Hierarchy (LEACH) and Grid-Based Low Energy Adaptive Clustering Hierarchy (G-LEACH) methods are clustering methods used to collet data by clustering nodes in the WSN area. The clustering process for both methods is the same, namely by select node as the Cluster head (CH) whose job is to collet data from other nodes to the sink. The selection of CH is carried out in each round by taking into account the probability formula used and the largest the remaining energy at that node. This study aims to determine the quality comparison of CH selection techniques in clustering-based routing protocol on WSN. The result of the study show that the G-LEACH routing protocol has good quality CH selection techniques and a long network lifetime compared to LEACH but requires a long time to reach the CH selection process
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Gupta, Amit, Mahesh Motwani, and J. L. Rana. "Cluster Formation and Maintenance Techniques for Mobile Adhoc Networks with Improved Quality of Service." International Journal of Emerging Technology and Advanced Engineering 11, no. 8 (August 19, 2021): 97–110. http://dx.doi.org/10.46338/ijetae0821_12.
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— In an Adhoc Network, every node is mobile and self-contained. As these networks lack infrastructure, highly adaptive algorithms are required to deal with frequent mobility changes by member nodes as well as Cluster Head (CH) nodes. The weighted clustering algorithms contribute significantly to cluster-based routing. In these algorithms, the selection of cluster heads is the most important task. In weighted clustering methods, the selected CH did their best to serve the network. However, the CH may become overloaded due to the arrival of nodes greater than their desired threshold value. In this case, the CH can become a bottleneck as it is unable to cope with rapidly increasing loads which ultimately degrade the network performance. In this paper, we address three network issues (i) Member Node movement (ii) Cluster head Node movement, and (iii) Overload at the Cluster head node caused due to mobility of nodes. Our proposed method Cluster Formation and Maintenance Techniques for Mobile Adhoc Networks with Improved Quality of Service (CFMIQS) include various adaptive algorithms to provide solutions to deal with these network issues and improve network Quality of Service (QoS). The Simulated Results are compared with the K-means AODV algorithm, the results showed better Packet Delivery Fraction (PDF) and Throughput values. Keywords— Cluster partition, MANET, Primary Cluster head, QoS, Secondary Cluster head
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Khalifeh, Ala’, Husam Abid, and Khalid A. Darabkh. "Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks." Sensors 20, no. 13 (July 3, 2020): 3719. http://dx.doi.org/10.3390/s20133719.
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Wireless sensor networks (WSNs) are increasingly gaining popularity, especially with the advent of many artificial intelligence (AI) driven applications and expert systems. Such applications require specific relevant sensors’ data to be stored, processed, analyzed, and input to the expert systems. Obviously, sensor nodes (SNs) have limited energy and computation capabilities and are normally deployed remotely over an area of interest (AoI). Therefore, proposing efficient protocols for sensing and sending data is paramount to WSNs operation. Nodes’ clustering is a widely used technique in WSNs, where the sensor nodes are grouped into clusters. Each cluster has a cluster head (CH) that is used to gather captured data of sensor nodes and forward it to a remote sink node for further processing and decision-making. In this paper, an optimization algorithm for adjusting the CH location with respect to the nodes within the cluster is proposed. This algorithm aims at finding the optimal CH location that minimizes the total sum of the nodes’ path-loss incurred within the intra-cluster communication links between the sensor nodes and the CH. Once the optimal CH is identified, the CH moves to the optimal location. This suggestion of CH re-positioning is frequently repeated for new geometric position. Excitingly, the algorithm is extended to consider the inter-cluster communication between CH nodes belonging to different clusters and distributed over a spiral trajectory. These CH nodes form a multi-hop communication link that convey the captured data of the clusters’ nodes to the sink destination node. The performance of the proposed CH positioning algorithm for the single and multi-clusters has been evaluated and compared with other related studies. The results showed the effectiveness of the proposed CH positioning algorithm.
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L., Rajesh, and Mohan H. S. "Shuffled Shepherd Squirrel Optimization and Fractional LMS Model for In-Network Aggregation in Wireless Sensor Network." International Journal of Business Data Communications and Networking 18, no. 1 (January 1, 2022): 1–20. http://dx.doi.org/10.4018/ijbdcn.309412.
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The wireless sensor network (WSN) is commonly based on small node collaboration. These nodes are specified by wireless communication, low price, and energy consumption. Moreover, the WSN can be utilized to compute pressure, temperature, as well as monitoring health, military supervision, and so on. A variety of WSN applications need to gather data from sensor nodes based on sink. In this paper, shuffled shepherd squirrel optimization (SSSOA) technique is devised for in-network aggregation in WSN. Here, the path is formulated from source node to destination through routing process, and source node broadcasts a packet concurrently to destination. The WSN is initiated, and the suitable cluster head (CH) is selected from all nodes. Consequently, CH is selected based on the developed shuffled shepherd squirrel optimization (SSSOA) method.
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Subramani, Neelakandan, Abbas Mardani, Prakash Mohan, Arunodaya Raj Mishra, and Ezhumalai P. "A fuzzy logic and DEEC protocol-based clustering routing method for wireless sensor networks." AIMS Mathematics 8, no. 4 (2023): 8310–31. http://dx.doi.org/10.3934/math.2023419.
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<abstract> <p>Power-efficient wireless sensor network routing techniques (WSN). Clustering is used to extend WSNs' lifetimes. One node act as the cluster head (CH) to represent the others in communications. The member nodes are less important than the cluster hub (CH) in the clustering procedure. Fuzzy techniques based on clustering theory may provide evenly distributed loads. In this study, we provide a fuzzy-logic-based solution that factors in distance to base station (BS), number of nodes, remaining energy, compactness, distance to communicate within a cluster, number of CH, and remaining energy. Fuzzy clustering has a preliminary and final step. First, we select CH based on distance to the base station (BS), remaining node vigor, and node compactness. In the second phase, clusters are created by combining nodes that aren't already in a CH, using density, outstanding vigor, and detachment as limitations. The proposed solution increases load balancing and node longevity. This work provides a unique hybrid routing technique for forming clusters and managing data transfer to the base station. Simulation findings confirm the protocol's functionality and competence. Reduced energy use keeps network sensor nodes online longer. The framework outperforms Stable Election Protocol (SEP), hybrid energy-efficient distributed clustering (HEED), and Low Energy Adaptive Clustering Hierarchy (LEACH). Using the nodes' energy levels to create a grid pattern for the clusters gave four clusters. In addition, the proposed method has a 4347%, 41.46%, 39.26%, 37.57% and 35.67% reduction in average energy consumption when compared with the conventional algorithms. The proposed technologies could increase the network's lifetime, stability interval, packet transfer rate (throughput), and average energy. The suggested protocol is at least 50% better in every statistic that was looked at, such as network lifetime, stability interval, packet transmission rate (throughput), and average energy use.</p> </abstract>
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Devika, G., D. Ramesh, and Asha Gowda Karegowda. "Analysis of Binary and Discrete Grey Wolf Optimization Algorithms Applied for Enhancing Performance of Energy Efficient Low Energy Adaptive Clustering Hierarchy." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 3850–59. http://dx.doi.org/10.1166/jctn.2020.8974.
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Wireless sensor networks (WSN) are a yield of advancement in information technology and the requirement of large-scale communication infrastructures. Routing of data via selected paths is a critical task in WSN as process need to be carried on under resource constraint situations. This route identification problem can be better handled by employing appropriate heuristic bio-inspired computational intelligence optimization method. The most frequently applied routing is hierarchical routing algorithm is Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm which has limitations in identifying energy efficient inter and intra route communication, identification of number of cluster head (CH), an eminent node to communicate to CH and Base Station (BS), selection of CH, and computing residual energy level, etc. Hence, researchers are focusing on boosting the capability of LEACH clustering algorithm by applying heuristic bio-inspired computational intelligence optimization methods. The proposed work is an attempt in this direction through applying heuristic bio-inspired Grey Wolf Optimization algorithm (GWO) for improving the performance of LEACH algorithm. In this paper, focus is given to increase the overall network time by adapting two modifications to conventional algorithms (i) selection of vice cluster head (VCH) in addition to CH (VCH node will replace the CH when CH when CH node goes down due to unexpected reasons as sensor node work under critical and uninterruptable environments and (ii) selection of intra and inter relay nodes (intra relay node will enhance the life span during CH data gathering and inter relay node will further enhance the life span of CH by acting as a mediator between CH an BS). The Spyder-py3 tool is used to simulate the proposed algorithms, LEACH Binary Grey Wolf search based Optimization (LEACH-BGWO) and LEACH Discrete Grey Wolf search based Optimization (LEACH-DGWO) protocols. The proposed work is compared with cluster based LEACH algorithm, chain based power-efficient gathering in sensor information systems (PEGASIS) algorithm, bio-inspired GWO and Genetic Algorithm data Aggregation (GADA) LEACH protocols. The results prove that both proposed algorithms outperformed other conventional algorithms in terms of prolonged network lifespan and increased throughput. Among proposed algorithms LEACH-BGWO outperformed LEACH-DGWO
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Mahdi, Omar Adil, Ahmed Basil Ghazi, and Yusor Rafid Bahar Al-Mayouf. "Void-hole aware and reliable data forwarding strategy for underwater wireless sensor networks." Journal of Intelligent Systems 30, no. 1 (January 1, 2021): 564–77. http://dx.doi.org/10.1515/jisys-2020-0137.
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Abstract Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data communication processes with sink node. As such, failure in communicating nodes would lead to a significant network void-holes problem. Considering the limited energy resources of nodes in UWSNs along with the heavy load of CHs in the routing process, this paper proposes a void-holes aware and reliable data forwarding strategy (VHARD-FS) in a proactive mode to control data packets delivery from CH nodes to the sink in UWSNs. In the proposed strategy, each CH node is aware of its neighbor’s performance ranking index to conduct a reliable packet transmission to the sink via the most energy-efficient route. Extensive simulation results indicate that the VHARD-FS outperforms existing routing approaches while comparing energy efficiency and network throughput. This study helps to effectively alleviate the resource limitations associated with UWSNs by extending network life and increasing service availability even in a harsh underwater environment.
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Sumiharto, Raden, Rosyidatul Ilma, and Rif’Atunnisa Rif’Atunnisa. "Metode Routing Protokol LEACH pada Jaringan Sensor Nirkabel Studi Kasus Sistem Pemantauan Suhu dan Kelembaban Udara." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 9, no. 1 (April 30, 2019): 87. http://dx.doi.org/10.22146/ijeis.44449.
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Wireless Sensor Network (WSN) is a wireless network consisting of a group of nodes scattered in a certain area. Each node has the ability to gather data around it and communicate with other nodes. In WSN, energy efficiency is important to maintain the lifetime of a network. A WSN consisting of several clusters and having a Cluster Head (CH) in each cluster requires a CH change mechanism in each cluster so that the network lifetime is longer.The LEACH algorithm is implemented on a system consisting of 9 sensor nodes and 1 sink node. Each sensor node monitors the temperature and humidity of the surrounding air. System testing is done by varying the number of data snippets per CH selection process in each LEACH cycle. Based on the results of testing, the application of the LEACH algorithm can increase network lifetime. The LEACH algorithm with 70 data snippets is an optimal state that results in a network lifetime of 7,387 seconds, whereas with the same number of data snippets when using a non-LEACH algorithm the network lifetime can only reach 5,565 seconds.
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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 (May 31, 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 which ultimately prolongs the lifespan of wireless network. Initially, cluster are formed in the network by selecting the nodes randomly. After this, four important parameters which included, residual energy, distance to sink, average distance to CH neighbor node and delay are taken into consideration and on the basis of these factors’ fitness value is calculated by the chaotic-YSGA technique. The node whose fitness value came out to be highest of all other nodes, is selected as the CH in that particular cluster. In addition, the Huffman data compression technique is used in the proposed system to reduce energy consumption in nodes. Finally, the performance of the proposed Chaotic-YSGA model is analyzed and compared with conventional energy efficient models in MATLAB software in terms of alive node, dead nodes, throughput, residual energy, FND, HND and LND. Keywords: WSN, Energy Efficiency, CH selection, Optimization Algorithms.
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Lee, Jong-Yong, and Daesung Lee. "Improvement of CH election in three-level heterogeneous WSN." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 1 (January 1, 2019): 272. http://dx.doi.org/10.11591/ijeecs.v13.i1.pp272-278.
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<p>A Wireless Sensor Network is a wirelessly configured Sensor Node with limited power such as a battery. There are many Wireless Sensor Network Protocols to increase energy efficiency, among which LEACH Protocol and SEP are typical. The LEACH Protocol is mainly used for homogeneous sensor networks with the same initial energy, and SEP is used for heterogeneous sensor networks with different initial energies. In the case of SEP-E, another heterogeneous sensor with different initial energy is added. SEP and SEP-E provide a higher probability of Cluster Head election for node types with more energy than Normal Nodes. Since the current residual energy of the node is not confirmed, even if the energy is low, the Cluster Head may be elected because of the node type. In this paper, considering the residual energy of a node when a Cluster Head is elected, we increase the probability of electing a Cluster Head with more residual energy. Cluster Head consumes a lot of energy. A node with a lot of residual energy is elected as a Cluster Head, so the network lifetime can be used for a long time.</p>
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Malik, Tauqeer Safdar, Jawad Tanveer, Shahid Anwar, Muhammad Rafiq Mufti, Humaira Afzal, and Ajung Kim. "An Efficient and Secure Fog Based Routing Mechanism in IoT Network." Mathematics 11, no. 17 (August 24, 2023): 3652. http://dx.doi.org/10.3390/math11173652.
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The Internet of Things (IoT) networks are the most prone to internal as well as external attacks in addition to energy consumption problems. Conventional security solutions are not able to address these issues effectively due to the limited resources of sensor nodes participating in IoT communications. In this work, an Efficient and Secure Fog Based Routing Mechanism (ESFRM) is proposed to protect the network from faulty internal as well as external attacks. Every node participating in IoT communications calculates the comprehensive trust value of the next intermediate node which is the addition of direct trust, indirect trust and energy trust values before forwarding the data. This comprehensive trust value is then compared with the comprehensive threshold trust value to decide whether the particular node is a rogue node or a valid normal node. Further, an enhanced RSA (Rivest, Shamir, Adleman) algorithm is implemented to provide three levels of data security from Cluster Head (CH) to fog node, from fog node to cloud server and directly from CH to cloud server. For this purpose, an efficient CH selection technique is also proposed in this work. The proposed methodology is compared with the Secure Energy-efficient Fog-based Routing (SEFR) protocol and Trust-aware Secure Routing Protocol (TSRP). The evaluation results show that the proposed ESFRM outperforms the conventional schemes with respect to energy consumption, malicious node detection and transmission rate.
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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 (October 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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Han, Yamin, Heejung Byun, and Liangliang Zhang. "Energy-Balanced Cluster-Routing Protocol Based on Particle Swarm Optimization with Five Mutation Operators for Wireless Sensor Networks." Sensors 20, no. 24 (December 16, 2020): 7217. http://dx.doi.org/10.3390/s20247217.
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Prolonging the network lifetime is one of the fundamental requirements in wireless sensor networks (WSNs). Sensor node clustering is a very popular energy conservation strategy in WSNs, allowing to achieve energy efficiency, low latency, and scalability. According to this strategy, sensor nodes are grouped into several clusters, and one sensor node in each cluster is assigned to be a cluster head (CH). The responsibility of each CH is to aggregate data from the other sensor nodes within its cluster and send these data to the sink. However, the distribution of sensor nodes in the sensing region is often non-uniform, which may lead to an unbalanced number of sensor nodes between clusters and thus unbalanced energy consumption between CHs. This, in turn, may result in a reduced network lifetime. Furthermore, a different number of clusters lead to a different quality of service of a WSN system. To address the problems of unbalanced number of sensor nodes between clusters and selecting an optimal number of clusters, this study proposes an energy-balanced cluster-routing protocol (EBCRP) based on particle swarm optimization (PSO) with five mutation operators for WSNs. The five mutation operators are specially proposed to improve the performance of PSO in optimizing sensor node clustering. A rotation CH selection scheme based on the highest residual energy is used to dynamically select a CH for each cluster in each round. Simulation results show that the proposed EBCRP method performs well in balancing energy consumption and prolonging the network lifetime.
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Reddy, Kummathi Chenna, Venkatesh S N, Manjula K B, and Boban Mathews. "Lifetime Enhancement Of Wireless Sensor Networks Using Energy Centric Clustering Algorithm." International Journal of Advanced Networking and Applications 13, no. 05 (2022): 5095–101. http://dx.doi.org/10.35444/ijana.2022.13501.
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The major issue in Wireless Sensor Networks (WSN) is energy consumption. Over the past years, various protocols have been proposed to prolong the lifetime and minimize the energy consumption of the sensor node. The main limitations in WSN are limited battery capacity, communication range and storage capacity. A suitable routing protocol is required to improve the network lifetime and minimize energy consumption. In this paper, we propose an Energy Centric Clustering Routing Protocol for WSNs (EC2RP). In EC2RP, node residual energy and distance parameters are considered. Further, the data aggregation rate is proposed which allows the cluster heads (CH) nodes to aggregate the data before it sending to the next CH node or base station node. The simulation results show that EC2RP reduces energy consumption and extends the network lifetime.
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Galluccio, Laura, Joannes Sam Mertens, and Giacomo Morabito. "Clustered Distributed Learning Exploiting Node Centrality and Residual Energy (CINE) in WSNs." Network 3, no. 2 (April 23, 2023): 253–68. http://dx.doi.org/10.3390/network3020013.
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With the explosion of big data, the implementation of distributed machine learning mechanisms in wireless sensor networks (WSNs) is becoming required for reducing the number of data traveling throughout the network and for identifying anomalies promptly and reliably. In WSNs, the above need has to be considered along with the limited energy and processing resources available at the nodes. In this paper, we tackle the resulting complex problem by designing a multi-criteria protocol CINE that stands for “Clustered distributed learnIng exploiting Node centrality and residual Energy” for distributed learning in WSNs. More specifically, considering the energy and processing capabilities of nodes, we design a scheme that assumes that nodes are partitioned in clusters and selects a central node in each cluster, called cluster head (CH), that executes the training of the machine learning (ML) model for all the other nodes in the cluster, called cluster members (CMs). In fact, CMs are responsible for executing the inference only. Since the CH role requires the consumption of more resources, the proposed scheme rotates the CH role among all nodes in the cluster. The protocol has been simulated and tested using real environmental data sets.
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Saini, Hardeep S., and Dinesh Arora. "A Split Network based Routing Approach in Wireless Sensor Network to Enhance Network Stability." International Journal of Sensors, Wireless Communications and Control 9, no. 4 (September 17, 2019): 480–87. http://dx.doi.org/10.2174/2210327909666190208152955.
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Background & Objective: The operating efficiency of a sensor network totally relies upon the energy that is consumed by the nodes to perform various tasks like data transmission etc. Thus, it becomes mandatory to consume the energy in an intelligent way so that the network can run for a long period. This paper proposed an energy efficient Cluster Head (CH) selection mechanism by considering the distance to Base Station (BS), distance to node and energy as major factors. The concept of volunteer node is also introduced with an objective to reduce the energy consumption of the CH to transmit data from source to BS. The role of the volunteer node is to transmit the data successfully from source to destination or BS. Conclusion: The results are observed with respect to the Alive nodes, dead nodes and energy consumption of the network. The outcome of the proposed work proves that it outperforms the traditional mechanisms.
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Chen, Jing, Chun-xiao Li, Si-hui Shao, Ming-hua Yao, Yi-jin Su, and Rong Wu. "The association between conventional ultrasound and contrast-enhanced ultrasound appearances and pathological features in small breast cancer." Clinical Hemorheology and Microcirculation 80, no. 4 (April 6, 2022): 413–22. http://dx.doi.org/10.3233/ch-211291.
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OBJECTIVE: To investigate the association between ultrasound appearances and pathological features in small breast cancer. MATERIALS AND METHODS: A total of 186 small breast cancers in 186 patients were analyzed in this retrospective study from January 2015 to December 2019 according to pathological results. Forty-seven cases of axillary lymph node metastasis were found. All patients underwent radical axillary surgery following conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations. The association between ultrasound appearances and pathological features was analyzed using univariate distributions and multivariate analysis. Then, a logistic regression model was established using the pathological diagnosis of lymph node metastasis and biochemical indicators as the dependent variable and the ultrasound appearances as independent variables. RESULTS: In small breast cancer, risk factors of axillary lymph node metastasis were crab claw-like enhancement on CEUS and abnormal axillary lymph nodes on US. The logistic regression model was established as follows: (axillary lymph node metastasis) = 1.100×(crab claw-like enhancement of CEUS) + 2.749×(abnormal axillary lymph nodes of US) –5.790. In addition, irregular shape on CEUS and posterior echo attenuation on US were risk factors for both positive estrogen receptor and progesterone receptor expression, whereas calcification on US was a risk factor for positive Her-2 expression. A specific relationship could be found using the following logistic models: (positive ER expression) = 1.367×(irregular shape of CEUS) + 1.441×(posterior echo attenuation of US) –5.668; (positive PR expression) = 1.265×(irregular shape of CEUS) + 1.136×(posterior echo attenuation of US) –4.320; (positive Her-2 expression) = 1.658×(calcification of US) –0.896. CONCLUSION: Logistic models were established to provide significant value for the prediction of pre-operative lymph node metastasis and positive biochemical indicators, which may guide clinical treatment.
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D, Rajesh. "Energy-Resourceful Routing by Fuzzy Based Secured CH Clustering for Smart Dust." International Journal of Electrical and Electronics Research 10, no. 3 (September 30, 2022): 659–63. http://dx.doi.org/10.37391/ijeer.100340.
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Smart Dust Network (SDN) consists of no-infrastructure, sovereign network, smart dust nodes are associated with wireless paths in multihop fashion. No-infrastructure and mobility atmosphere contains complexity to establish an innovative secure routing approach for MWSN. The major problem in MWSN is in routing because of its scarce resource accessibility and mobility in nature. Energy-resourceful routing is indispensable since each smart dust node is containing constrained battery energy. Power breakdown of a particular smart dust node splits network design. So MWSN routing utilizes offered battery power in successful manner to amplify network life. Fuzzy Based Secured CH Clustered (FSCC) approach identifies trustworthy and loop-open path among smart dust nodes by deciding a finest cluster-head. FSCC utilize velocity, signal potency and lingering energy as parameters to discover resourceful cluster-head. Smart dust nodes applying fuzzy rules to evaluate node cost. Smart dust node with maximum cost is decided as cluster-head. Cluster-head accomplishes event exchange among base station. Consequently, FSCC conserve constant network by diminishing re-association of entire smart dust nodes, re-selection of cluster-head and re-clustering. FSCC approach retains packet-delivery, delay, energy utilization by 88.073%, 16.485 %, and 24.6813% than offered AODV and FCESRB methodologies.
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Song, Liu, He, and Jiang. "Research on Data Fusion Scheme for Wireless Sensor Networks with Combined Improved LEACH and Compressed Sensing." Sensors 19, no. 21 (October 29, 2019): 4704. http://dx.doi.org/10.3390/s19214704.
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There are a lot of redundant data in wireless sensor networks (WSNs). If these redundant data are processed and transmitted, the node energy consumption will be too fast and will affect the overall lifetime of the network. Data fusion technology compresses the sampled data to eliminate redundancy, which can effectively reduce the amount of data sent by the node and prolong the lifetime of the network. Due to the dynamic nature of WSNs, traditional data fusion techniques still have many problems. Compressed sensing (CS) theory has introduced new ideas to solve these problems for WSNs. Therefore, in this study we analyze the data fusion scheme and propose an algorithm that combines improved clustered (ICL) algorithm low energy adaptive clustering hierarchy (LEACH) and CS (ICL-LEACH-CS). First, we consider the factors of residual energy, distance, and compression ratio and use the improved clustered LEACH algorithm (ICL-LEACH) to elect the cluster head (CH) nodes. Second, the CH uses a Gaussian random observation matrix to perform linear compressed projection (LCP) on the cluster common (CM) node signal and compresses the N-dimensional signal into M-dimensional information. Then, the CH node compresses the data by using a CS algorithm to obtain a measured value and sends the measured value to the sink node. Finally, the sink node reconstructs the signal using a convex optimization method and uses a least squares algorithm to fuse the signal. The signal reconstruction optimization problem is modeled as an equivalent l1-norm problem. The simulation results show that, compared with other data fusion algorithms, the ICL-LEACH-CS algorithm effectively reduces the node’s transmission while balancing the load between the nodes.
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Molk, Ali Mohammad Norouzzadeh Gil, Seyed Mohsen Ghoreishi, Fatemeh Ghasemi, and Iraj Elyasi. "Improve Performances of Wireless Sensor Networks for Data Transfer Based on Fuzzy Clustering and Huffman Compression." Journal of Sensors 2022 (September 22, 2022): 1–16. http://dx.doi.org/10.1155/2022/3860682.
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In today’s world, the main challenge is to save use energy optimally. The IoT devices generate a large amount of data for wide applications. Considering the application perspective in the IoT market, in one instance of the IoT technology, that is a wireless sensor network, factors like energy, storage capacity, computation power, and limitations of communication bandwidth resources are the reason for using data fusion. Data fusion and aggregation in wireless sensor networks (WSNs) such that minimum energy is consumed are an essential issue. In most clustering models, data aggregation is carried out by the cluster-head (CH). In the proposed algorithm, data aggregation in the cluster-head is carried out using the lossless cascode Huffman compression algorithm. Due to the correlation among data of nodes, the data sensed by each node is compared with the data of the cluster-head node; after removing redundancy, the coded data is transmitted to the main node. The CH node is selected by an algorithm based on fuzzy logic according to the residual energy of the node and the distance of the node from the sink node. Various fuzzy type-I systems of Mamdani and Takagi-Sugeno and type-II systems are used. In this paper, the CH selection algorithms are evaluated using three scenarios in terms of the number of live nodes, received packets and CHs, proper distribution rate, and other parameters of the LEACH protocol, network lifetime, and network energy. In the following, to demonstrate the performance of this new algorithm, simulations are performed in MATLAB based on the proposed method. The results show that the proposed compression algorithm in environments with high data correlation improves the compression rate by 8% compared to the conventional Huffman compression, while in environments with low data correlation, these two algorithms perform almost the same. This compression helps reduce the energy consumption of the network.
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Anees, Junaid, and Hao-Chun Zhang. "FLOC: Hesitant Fuzzy Linguistic Term Set Analysis in Energy Harvesting Opportunistic Clustering Using Relative Thermal Entropy and RF Energy Transfer." International journal of Computer Networks & Communications 14, no. 02 (March 31, 2022): 19–39. http://dx.doi.org/10.5121/ijcnc.2022.14202.
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Limited energy resources and sensor nodes’ adaptability with the surrounding environment play a significant role in the sustainable Wireless Sensor Networks. This paper proposes a novel, dynamic, selforganizing opportunistic clustering using Hesitant Fuzzy Linguistic Term Analysis- based Multi-Criteria Decision Modeling methodology in order to overcome the CH decision-making problems and network lifetime bottlenecks. The asynchronous sleep/awake cycle strategy could be exploited to make an opportunistic connection between sensor nodes using opportunistic connection random graph. Every node in the network observe the node gain degree, energy welfare, relative thermal entropy, link connectivity, expected optimal hop, link quality factor etc. to form the criteria for Hesitant Fuzzy Linguistic Term Set. It makes the node to evaluate its current state and make the decision about the required action (‘CH’, ‘CM’ or ‘relay’). Our proposed scheme leads to an improvement in network lifetime, packet delivery ratio and overall energy consumption against existing benchmarks.
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Mishra, Pankaj Kumar, and Shashi Kant Verma. "FFMCP: Feed-Forward Multi-Clustering Protocol Using Fuzzy Logic for Wireless Sensor Networks (WSNs)." Energies 14, no. 10 (May 16, 2021): 2866. http://dx.doi.org/10.3390/en14102866.
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The restriction on the battery life of sensors is a bottleneck for wireless sensor networks (WSNs). This paper proposes a new feed-forward multi-clustering protocol (FFMCP) to boost the network lifetime. The utilization of fuzzy logic helps to overcome the uncertainties in the value of input parameters. The proposed protocol selects the most suitable cluster heads (CHs) using the multi-clustering method. A multi-clustering technique is defined utilizing the node’s information of the previous round and a fuzzy inference system to decide the CHs. The sensor nodes spend energy due to non-uniform CH distribution and long-distance data transmission by member nodes. The main focus of the proposed protocol is to reduce the member node distance. Our proposal distributes CH nodes uniformly using unequal clustering. The simulation outcome reveals that the proposed algorithm(FFMCP) has better performance in terms of tenth node death (TND), half node death (HND), remaining energy after 800 rounds (E_800), and average energy spent per round (AVG_PR) as compared to standard clustering schemes in the past.
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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 (December 28, 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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Gao, Lu, and Zhong Min Li. "A New Approach for Solving Cluster Head Uneven Distribution in Wireless Sensor Network." Applied Mechanics and Materials 462-463 (November 2013): 51–54. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.51.
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In the applications of Wireless Sensor Networks (WSNs), the factor affecting the performance is energy consumption. In all operations in the WSN, Data transmission consumes a lot of energy because of its frequency. LEACH is proposed to reduce transmission distance. Cluster Head (CH) is selected randomly without any parameter, so CHs distribution is uneven and the distance between some nodes and their connected nodes is remote, which causes shortening system lifetime. In this paper, we proposed a new LEACH-based algorithm. The main purpose of new algorithm is to make CHs distribution even. In the improved algorithm, a node connects to a CH or acts as a temp CH based on the distance to the closest CH. The results of simulation show that improved LEACH algorithm increases energy efficiency and prolongs the network lifetime.
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Hu, Huangshui, Yuxin Guo, Chuhang Wang, Dong Gao, and Qinxue Liu. "Optimal Relay Angle-Based Clustering Routing Protocol for Wireless Sensor Networks." Journal of Sensors 2022 (June 20, 2022): 1–18. http://dx.doi.org/10.1155/2022/5751155.
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In this paper, a novel optimal relay angle-based clustering routing protocol called RACR is proposed to balance nodes’ energy consumption and prolong the network lifespan of wireless sensor networks (WSNs). In RACR, each node considers the parameters residual energy, number of neighbors, and average distance with neighbors as a criteria to determine whether to become a cluster head (CH) which cooperates with its neighbors to form a cluster. Afterward, the optimal relay angle is calculated for each CH to find its best relay node according to a target function considering the least energy consumption, which is applied to reduce the search range for finding routing paths. Consequently, all the CHs can find their best next-hop nodes within the determined field according to their residual energy, distance to the next-hop CH, and loads. Iteratively, the CHs obtain their best routing paths to the BS in the end. Simulation results demonstrate its effectiveness of RACR in terms of energy consumption, standard deviation of residual energy, data communication delay, network throughput, and lifespan.
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Wang, Shubin, Huiqin Liu, and Kun Liu. "An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/136948.
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Cooperative spectrum sensing (CSS) is a very important technique in cognitive wireless sensor networks, but the channel and multipath affect the sensing performance. For improving the sensing performance, this paper incorporates a modified double-threshold energy detection (MDTED) and the location and channel information to improve the clustering cooperative spectrum sensing (CCSS) algorithm. Within each cluster, the cognitive node with the best channel quality to the fusion center (FC) is chosen as the cluster head (CH), and each node uses the MDTED. The detective information is sent to CH, and CH makes the decision of the cluster. The decision information is sent to FC by each CH, and FC uses the “or” rule to fuse all clusters’ decision information and makes a final decision. Since MDTED needs to transfer large traffic and occupy channel widely, this paper further optimizes the improved algorithm. Ensuring the detection performance, the cognitive nodes participating in the sensing are properly reduced. Simulation results show that the detecting accuracy of the improved algorithm is higher than conventional CSS, and the improved algorithm can also significantly improve collaborative sensing ability. For the optimization of cognitive nodes’ number, the detection probability of the network can be obviously increased.
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Zhang, Yu Cheng, Xing Guo Qiu, and Zhan Jun Hao. "A Hierarchical and Clustering Strategy for Routing in WSN Based on Ant Colony Optimization." Advanced Materials Research 915-916 (April 2014): 1251–58. http://dx.doi.org/10.4028/www.scientific.net/amr.915-916.1251.
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Since the energy of wireless sensor nodes is limited, the protocols of wireless sensor network (WSN) we design should care about problems of balancing energy of nodes. After analyzing current algorithms, this paper puts forward an hierarchical and clustering strategy for routing based on Ant Colony Optimization (HC-ACO). The protocol divides the nodes into fixed clusters, each cluster selects a Cluster Header (CH) and switches the CH by its energy and other restrictive conditions. And it adopts ACO to search the optimal path between the CHs and Sink node. The simulation indicates the protocol can balance energy consumption of nodes of network.
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Reddy, V. S. N., and J. Mungara. "Artificial Intelligence Machine Learning in Healthcare System for improving Quality of Service." CARDIOMETRY, no. 25 (February 14, 2023): 1161–67. http://dx.doi.org/10.18137/cardiometry.2022.25.11611167.
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A vital element of widespread patient monitoring is consistency in transmission between the patients and the healthcare professionals not including time and position dependencies. Artificial intelligence (AI) and machine learning (ML) techniques have a vast possibility to proficiently handle the automated function of the mobile nodes distributed in the Mobile ad-hoc network (MANET). ML is a part of AI in that the computer algorithms learn themselves by improving from historical experiences. The main issues in MANET are autonomous operation, maximization of a lifetime, coverage of the network, energy utilization, connectivity issues, quality of service, high bandwidth necessity, communication protocol design, etc. ML is valuable for data aggregation, and it saves the energy of mobile nodes and enhances the network lifetime. In this paper, we propose an Artificial Intelligence Machine Learning Algorithm for improving the Quality of Service in MANET (AIMQ). ML techniques based on artificial neural networks (ANN) algorithm is helpful for data aggregation tasks. This approach formed the clusters by node mobility and connectivity. Glowworm Swarm Optimization (GSO) algorithm is applied in every cluster to choose a proficient Cluster Head (CH). Here, we choose the CH by GSO fitness function based on mobile node degree, node distance, node reliability, and energy. ANN algorithm recognizes and chooses the data aggregator with great energy and more extended stability. It updates the weight of input parameters such as node energy, node degree, packet loss ratio, and node delay to reduce the errors. It minimizes the repetitive CHs selection and member nodes’ re-affiliation in a cluster.
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Gao, Lu, and Zhong Min Li. "EW-LEACH: Energy Weight-Based Routing Techniques in WSNs." Applied Mechanics and Materials 448-453 (October 2013): 2612–15. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2612.
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Wireless Sensor Networks (WSNs) play more and more important role in all kinds of applications. Because of its characteristics, energy consumption is an open issue in research field. In LEACH Cluster Head (CH) is selected randomly without any parameter, such as node energy, distance. There exists a probability that energy consumption is unbalanced in WSN, which causes shortening its lifetime. In this paper, we proposed a new LEACH-based protocol, Energy Weight LEACH (EW-LEACH). The main purpose of EW-LEACH is to provide important parameters, node energy, to determine the CH selection strategy. Node energy acts as a weight to alter the probability that a node becomes CH. The results of simulation show that EW-LEACH increases energy efficiency and prolong the network lifetime.
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Jaisakthi, K., and S. Nithyadhevi. "Location Privacy and Lifetime Maximization using Low Energy Adaptive Technique in WSN." International Journal of Advance Research and Innovation 3, no. 1 (2015): 48–51. http://dx.doi.org/10.51976/ijari.311508.
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In a sensor network, an important problem is to provide privacy to the event detecting sensor node and integrity to the data gathered by the node. In the privacy preserving location monitoring system for wireless sensor networks can be design to enable the system to provide high quality location monitoring services for system users, while preserving personal location privacy. Hybrid Cluster Structure (CS) used for sensor networks to improve the lifetime by using Low Energy Adaptive (LEA) protocol. The sensor nodes are organized into clusters. Within a cluster, nodes transmit data to cluster head (CH) without using Cluster Structure. All CHs are interconnected in CS mode to transmit data to sink. Hybrid Cluster Structure (CS) used for sensor networks. The sensor nodes are organized into clusters. Within a cluster, nodes transmit data to cluster head (CH) without using Cluster Structure.CH can be select by using stochastic algorithm. All CHs are interconnected in CS mode to transmit data to sink.
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Amgoth, Nageswar, Rajendra Bhukya, and Nirmala Lavadya. "Clustered Relay Node Placement for WSN through Metaheuristics Algorithm." International Journal of Intelligent Engineering and Systems 13, no. 6 (December 31, 2020): 67–80. http://dx.doi.org/10.22266/ijies2020.1231.07.
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In the field of Wireless Sensor Networks (WSNs), after the deployment of sensor nodes, transmission of data with an effective energy is becoming a critical issue due to the limited battery of sensor nodes. To solve this issue, most of the past developed approaches focused on the implementation of clustering in which the sensor nodes forward their data through Cluster Heads (CHs) to Base Station (BS). However, the main issue is to select an optimal CH or CHs such that every sensor node is ensured with at least one path to base station, directly, through CHs or through relay nodes. Towards this objective, we have proposed a new method called Multi-Objective Assisted Clustered Relay Node Placement (MOCRNP) to achieve improved energy efficiency along with an enhanced network lifespan. Firstly, to select the CH, the Multi-Objective Genetic Algorithm is introduced based on energy, distance and node density. Secondly, in the process of rely node placement, Multi-objective firefly algorithm is introduced and for this purpose, two constraints such as Coverage and Connectivity are considered. We have conducted several experimentations using several setups of the WSN and the performance is evaluated in terms of Network lifetime, average energy consumption, average residual energy, and throughput. On an average, the proposed approach has gained an improvement of 150 sec network lifetime, 104 Kbps Throughput when compared with state-of-art methods.
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Aidil Saputra Kirsan, Udin Harun Al Rasyid, Iwan Syarif, and Dian Neipa Purnamasari. "Energy Efficiency Optimization for Intermediate Node Selection Using MhSA-LEACH: Multi-hop Simulated Annealing in Wireless Sensor Network." EMITTER International Journal of Engineering Technology 8, no. 1 (June 2, 2020): 1–18. http://dx.doi.org/10.24003/emitter.v8i1.459.
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Energy usage on nodes is still a hot topic among researchers on wireless sensor networks. This is due to the increasing technological development increasing information requirements and caused the occurrence of information exchange continuously without stopping and impact the decline of lifetime nodes. It takes more effort to manually change the energy source on nodes in the wireless sensor network. The solution to such problems is to use routing protocols such as Low Energy Adaptive Clustering Hierarchy (LEACH). The LEACH protocol works by grouping nodes and selecting the Cluster Head (CH) in charge of delivering data to the Base Station (BS). One of the disadvantage LEACH protocols, when nodes are far from the CH, will require a lot of energy for sending data to CH. One way to reduce the energy consumption of each node-far is to use multi-hop communication. In this research, we propose a multi-hop simulated annealing (MhSA-LEACH) with an algorithm developed from the LEACH protocol based on intra-cluster multi-hop communication. The selection of intermediate nodes in multi-hop protocol is done using Simulated Annealing (SA) algorithm on Traveling Salesman Problem (TSP). Therefore, the multi-hop nodes are selected based on the shortest distance and can only be skipped once by utilizing the probability theory, resulting in a more optimal node path. The proposed algorithm has been compared to the conventional LEACH protocol and the Multi-Hop Advance Heterogeneity-aware Energy Efficient (MAHEE) clustering algorithm using OMNeT++. The test results show the optimization of MhSA-LEACH on the number of packets received by BS or CH and the number of dead or alive nodes from LEACH and MAHEE protocols.
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Han, Tao, Seyed Bozorgi, Ayda Orang, Ali Hosseinabadi, Arun Sangaiah, and Mu-Yen Chen. "A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes." Sustainability 11, no. 3 (January 31, 2019): 746. http://dx.doi.org/10.3390/su11030746.
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The Internet of things (IoT) provides the possibility of communication between smart devices and any object at any time. In this context, wireless nodes play an important role in reducing costs and simple use. Since these nodes are often used in less accessible locations, recharging their battery is hardly feasible and in some cases is practically impossible. Hence, energy conservation within each node is a challenging discussion. Clustering is an efficient solution to increase the lifetime of the network and reduce the energy consumption of the nodes. In this paper, a novel hybrid unequal multi-hop clustering based on density (HCD) is proposed to increase the network lifetime. In the proposed protocol, the cluster head (CH) selection is performed only by comparing the status of each node to its neighboring nodes. In this new technique, the parameters involving energy of nodes, the number of neighboring nodes, the distance to the base station (BS), and the layer where the node is placed in are considered in CH selection. So, in this new and simple technique considers energy consumption of the network and load balancing. Clustering is performed unequally so that cluster heads (CHs) close to BS have more energy for data relay. Also, a hybrid dynamic–static clustering was performed to decrease overhead. In the current protocol, a distributed clustering and multi-hop routing approach was applied between cluster members (CMs), to CHs, and CHs to BS. HCD is applied as a novel assistance to cluster heads (ACHs) mechanism, in a way that a CH accepts to use member nodes with suitable state to share traffic load. Furthermore, we performed simulation for two different scenarios. Simulation results showed the reliability of the proposed method as it was resulted in a significant increase in network stability and energy balance as well as network lifetime and efficiency.
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Gurunathan, Vishnupriya, Anusha Sakthivel, and Kavitha Datchanamoorthy. "Fuzzy based clustering and improved ant colony optimization for collecting data via mobile sink in wireless sensor networks." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 1 (October 1, 2023): 276. http://dx.doi.org/10.11591/ijeecs.v32.i1.pp276-283.
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<span>Energy efficient routing of data from sensor to base station (BS) is attained utilizing the clustering of sensor nodes, thus minimizing the number of hops and circling the task of the cluster head (CH) sporadically. In addition, the clusters near to the BS take a substantial load over multi-hop communication. The hot spot problem affects wireless sensor networks (WSNs) with BS nodes, which is caused by sensor nodes close to the BS allowing for increased traffic load. So, the entire network lifespan is minimized owing to the element some nodes drain their energy resources much faster equated to the break. To solve these issues fuzzy based clustering and form the optimal route (FCOR) by mobile sink (MS) approach for efficient data collection is proposed. The fuzzy logic method is used for elected the CH by node remaining energy, node connectivity and node distance parameters. Discovering an optimal movable trajectory for the MS is serious so as to attain energy efficiency. Improved ant colony optimization (IACO) method is a better solution to discovering an optimal traversal route. Simulation results proves that FCOR increases the energy efficiency, throughput and minimized the network delay in the WSN.</span>
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Geisberger, Robert, and Dennis Schieferdecker. "Heuristic Contraction Hierarchies with Approximation Guarantee." Proceedings of the International Symposium on Combinatorial Search 1, no. 1 (August 25, 2010): 31–38. http://dx.doi.org/10.1609/socs.v1i1.18161.
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We present a new heuristic point-to-point shortest path algorithm based on contraction hierarchies (CH). Given an epsilon >= 0, we can prove that the length of the path computed by our algorithm is at most (1 + ε) times the length of the optimal (shortest) path. Exact CH is based on node contraction: removing nodes from a network and adding shortcuts to preserve shortest path distances. Our heuristic CH tries to avoid adding shortcuts even when a replacement path is (1+epsilon) times longer. However, we cannot avoid all such shortcuts, as we need to ensure that errors do not stack. Combinations with goal-directed techniques bring further speed-ups.
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Chao Wang, Chao Wang, Wen-Wen Zha Chao Wang, Cheng Zhu Wen-Wen Zha, Wen-Yang Wang Cheng Zhu, Guang-Bo Li Wen-Yang Wang, Liang Tao Guang-Bo Li, Hui-Min Ma Liang Tao, and Jun Jiao Hui-Min Ma. "LEACH Clustering Routing Protocol Based on Balanced Energy Consumption." 電腦學刊 33, no. 5 (October 2022): 151–62. http://dx.doi.org/10.53106/199115992022103305013.
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<p>Faced with the problems of unbalanced energy consumption (EC) and short lifetime of nodes in Wireless Sensor Networks (WSN), a Low Energy Adaptive Clustering Hierarchy (LEACH) clustering routing protocol based on energy balance, namely LEACH-EB (LEACH Based on Energy Balance) protocol was proposed. At the initial selection stage, the nodes which are close to the base station (BS) with great remaining energy and many neighbor nodes are selected as the cluster heads (CHs); then, the non-CH nodes enter the clusters which have the least costs based on the strength and remaining energy of the communication signals between themselves and different CHs. At the data transmission stage, if the CH which sends the information is one hop away from BS, the CH needs to select a neighbor CH with the largest forwarding probability as the next hop relay node based on the remaining energy of each neighbor CH, the number of nodes in the cluster, and the distance from BS. The selected neighbor CH continues to determine the next hop in the above manner until the data is successfully sent to BS. Simulation tests show that LEACH-EB protocol can receive more data and extend the network life cycle by 60%, 43.1%, and 13.36% compared with LEACH, LEACH-C, and FIGWO, respectively. </p> <p> </p>
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Li, Zhong Min. "Energy Consumption Balance LEACH Routing Protocol for Wireless Sensor Networks." Applied Mechanics and Materials 536-537 (April 2014): 744–47. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.744.
Full textAbstract:
Energy consumption is an open issue in research field of Wireless Sensor Networks (WSNs). Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is the most additional routing protocol in WSNs. In LEACH, Cluster Head (CH) is selected randomly, not considering any parameter such as node energy, distance, which causes shortening its lifetime while energy consumption is unbalanced in WSNs. In this paper, it proposes a new LEACH-based protocol, energy consumption balance LEACH protocol. Firstly, all nodes are grouped based on their locations, and a CH is elected in every group, which ensures CHs even distribution in the network area. And an important factor selecting CHs, node energy is considered, which further energy consumption in WSNs. The results of simulation show that ECB-LEACH can increase energy efficiency and prolong the network lifetime.
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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 (June 8, 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 remaining node energy is used to calculate the mean energy of the entire network. The most likely nodes are picked as the CH, which gathers packets from the cluster members through multi-hop communication. The fundamental idea is to partition a top-secret communication into several shares and then forward the shares via numerous routes to the destination. The Coral Reef Optimization method is used in this work to perform optimum multipath routing. The thorough simulation findings validate the feasibility and efficacy of the suggested strategy in comparison to Butterfly optimization algorithm (BA), Whale Optimization algorithm (WOA) and BAT algorithm techniques.
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Preethi Author, R., and Dr R. Anbuselvi Author. "A Game Theory Approach for Efficient Node Clustering Based on Unstable Ranging Transmission in MANET." International Journal of Engineering & Technology 7, no. 2.22 (April 20, 2018): 21. http://dx.doi.org/10.14419/ijet.v7i2.22.11802.
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In Mobile Ad Hoc Network (MANET), improving scalability, energy efficiency and network lifetime are the most important and challenging issues. Node Clustering is a well known solution for handling these issues. While existing work focused on stable transmission range, this paper uses unstable ranges transmission for clustering nodes in network. Game theory has been used in fields of science such as economics and biology, but recently it was used in MANET for clustering problem. Grouping mobile nodes into convenient clusters can reduce routing overhead and provide more scalable solution. The main objective of this work is to clustering of nodes in MANET and selects energy efficient cluster head to improve the network lifetime using game theoretical model. This paper proposes an efficient algorithm for Node Clustering based on Unstable Ranging Transmission (NCURT). In addition to this, a game theory based cluster head (CH) selection algorithm is proposed to selects CH based on Evolutionary game theory approach where each node behaves selfish or unselfish based on the strategy selection. Analytical and simulation studies are carried out to assess the performance of the proposed cluster formation and cluster head selection algorithm. The numerical results verify that the proposed approach is effective and efficient to guarantee life time and energy efficiency in MANET.
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Prashanth, Jangiti Siva, and Satyanarayana V. Nandury. "A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN." International Journal of Computers Communications & Control 14, no. 6 (November 27, 2019): 691–709. http://dx.doi.org/10.15837/ijccc.2019.6.3630.
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Envoy Node Identification (ENI) and Halting Location Identifier (HLI) algorithms have been developed to reduce the travel time of Mobile Element (ME) by determining Optimal Path(OP) in Wireless Sensor Networks. Data generated by cluster members will be aggregated at the Cluster Head (CH) identified by ENI for onward transmission to the ME and it likewise decides an ideal path for ME by interfacing all CH/Envoy Nodes (EN). In order to reduce the tour length (TL) further HLI determines finest number of Halting Locations that cover all ENs by taking transmission range of CH/ENs into consideration. Impact of ENI and HLI on energy consumption and travel time of ME have been examined through simulations.
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Jerbi, Wassim, Abderrahmen Guermazi, and Hafedh Trabelsi. "A Clustering Protocol for Maximum Coverage in Large-Scale Wireless Sensor Networks." International Journal of Business Data Communications and Networking 11, no. 2 (July 2015): 1–21. http://dx.doi.org/10.4018/ijbdcn.2015070101.
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The optimum use of coverage in wireless sensor networks (WSNs) is very important. The hierarchical routing protocol LEACH (Low Energy Adaptive Clustering Hierarchy) is referred to as the basic algorithm of distributed clustering protocols. LEACH allows clusters formation. Each cluster has a leader called Cluster Head (CH). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node join a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus several sensor nodes cannot reach any CH. As a result, the remaining part of the controlled field will not be covered; some sensor nodes will be outside the network. To solve this problem, the authors propose O-LEACH (Orphan Low Energy Adaptive Clustering Hierarchy), a routing protocol that takes into account the orphan nodes. O-LEACH presents two scenarios, a gateway and sub cluster that allow the joining of orphan nodes.
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Saini, Vandana, and Meenu Khurana. "A Multi-Zone Based Hierarchical Protocol for Routing in Wireless Sensor Networks." ECS Transactions 107, no. 1 (April 24, 2022): 9489–96. http://dx.doi.org/10.1149/10701.9489ecst.
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Wireless sensor networks (WSNs) are used in many applications due to their small size and low cost. However, due to the limited battery constraint in WSNs, it faces several challenges of node failure, data drop, etc. There are many routing algorithms in the literature that ensures the energy efficiency routing by enhancing the network lifetime. But still the challenges of data aggregation, dynamic path selection needs much attention to further maximize the nodes lifetime. In this paper, a multi-hop routing is proposed with an additionally deployed master node to minimize the load on cluster head (CH) and base station (BS) node. The master node is deployed in the middle of the network, and it has been assumed that a master node is static node with power connection. The proposed network is divided into multiple zones according to nodes energy. The proposed network has shown better throughput and network lifetime. Also, the proposed scheme has shown lesser data drop and failure rate.
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Zheng, Aiyun, Zhen Zhang, Weimin Liu, Jiaxin Liu, Yao Xiao, and Chen Li. "Dual Cluster Head Optimization of Wireless Sensor Networks Based on Multi-Objective Particle Swarm Optimization." Sensors 23, no. 1 (December 26, 2022): 231. http://dx.doi.org/10.3390/s23010231.
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Energy conservation is one of the main problems in a wireless sensor network (WSN). Compared with a single cluster head (CH), a dual CH optimization was proposed for less energy consumption by the WSN and an acquisition delay by the mobile sink (MS). Firstly, a fuzzy c-means clustering algorithm and a multi-objective particle swarm optimization were utilized for the determinations of the first and second CHs. Following that, the ideal trajectory of MS was assessed using the improved ant colony algorithm. Finally, the lifetimes, the death rounds of the first node and the 50% node, and the number of packets received at the base station were compared among the proposed approach. Moreover, five algorithms were compared to validate the optimization, and the improved trajectory was compared with the original one as well. It was found that, for 100 nodes, the number of dead rounds from the proposal increased by 7.9%, 22.9%, 25.1%, 61%, and 74.4% for the first node, and that of the 50% nodes increased by 27.8%, 34.2%, 98.3%, 213.1%, and 211.2%, respectively. The base station packet reception increased by about 19.3%, 53.5%, 27%, 86.8%, and 181.2%, respectively. The trajectory of MS could also decrease by about 10%.
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Sathish, Kaveripakam, Monia Hamdi, Ravikumar Chinthaginjala, Giovanni Pau, Amel Ksibi, Rajesh Anbazhagan, Mohamed Abbas, and Mohammed Usman. "Reliable Data Transmission in Underwater Wireless Sensor Networks Using a Cluster-Based Routing Protocol Endorsed by Member Nodes." Electronics 12, no. 6 (March 8, 2023): 1287. http://dx.doi.org/10.3390/electronics12061287.
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Considering Underwater Wireless Sensor Networks (UWSNs) have limited power resources (low bandwidth, long propagation delays, and non-rechargeable batteries), it is critical that they develop solutions to reduce power usage. Clustering is one solution because it not only saves energy consumption but also improves scalability and data integrity. The design of UWSNs is vital to the development of clustering algorithms. The limited energy of sensor nodes, narrow transmission bandwidth, and unpredictable topology of mobile Underwater Acoustic Wireless Sensor Networks (UAWSNs) make it challenging to build an effective and dependable underwater communication network. Despite its success in data dependability, the acoustic underwater communication channel consumes the greatest energy at a node. Recharging and replacing a submerged node’s battery could be prohibitively expensive. We propose a network architecture called Member Nodes Supported Cluster-Based Routing Protocol (MNS-CBRP) to achieve consistent information transfer speeds by using the network’s member nodes. As a result, we use clusters, which are produced by dividing the network’s space into many minute circular sections. Following that, a Cluster Head (CH) node is chosen for each circle. Despite the fact that the source nodes are randomly spread, all of the cluster heads are linked to the circle’s focal point. It is the responsibility of the MNS-CBRP source nodes to communicate the discovered information to the CH. The discovered data will then be sent to the CH that follows it, and so on, until all data packets have been transferred to the surface sinks. We tested our techniques thoroughly using QualNet Simulator to determine their viability.
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Amalarethinam, Dr D. I. George, and Ms P. Mercy. "Enhanced Quality of Service Strategy for Improving Network Coverage in IOT Applications." Journal of University of Shanghai for Science and Technology 23, no. 05 (May 27, 2021): 694–707. http://dx.doi.org/10.51201/jusst/21/05201.
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The Internet of Things (IoT) is a network that includes physical things capable of aggregating and communicating electronic information. With the advancement in wireless sensor networks, IoT provides highly efficient communication for various real-time applications. IoT networks are large-scale networks where routing can be improved by focusing on the Quality of Service (QoS) Parameter. Network coverage can be enhanced by hierarchical clustering of the nodes which increases the network lifetime. The proposed algorithm Enhanced Fuzzy Based Clustering and Routing Algorithm (EFCRA) performs distance and energy-based cluster head selection to find a new path from source to destination. The algorithm uses Fuzzy c-means clustering to provide optimization in forming cluster centers. The cluster head (CH) is identified based on the minimum distance and maximum energy of the sensor node. The cluster head is updated when its energy is lesser than the threshold value. The distance between sensor nodes and its CH node and then to the destination is computed using Dijkstra’s algorithm. The proposed routing strategy provides improved network coverage and throughput which extends the lifetime of the IoT network.
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Bagherzadeh karimi, Nazli. "Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks." Computer Engineering and Applications Journal 3, no. 3 (September 7, 2014): 172–84. http://dx.doi.org/10.18495/comengapp.v3i3.92.
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In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications.