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Journal articles on the topic 'Clustered Routing'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Aziz, Layla, Hanane Aznaoui, and Said Raghay. "Graph-based optimal routing in clustered WSNs." International Journal of Ad Hoc and Ubiquitous Computing 37, no. 4 (2021): 207. http://dx.doi.org/10.1504/ijahuc.2021.10040650.

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2

Aziz, Layla, Said Raghay, and Hanane Aznaoui. "Graph-based optimal routing in clustered WSNs." International Journal of Ad Hoc and Ubiquitous Computing 37, no. 4 (2021): 207. http://dx.doi.org/10.1504/ijahuc.2021.117326.

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3

Tufail, Ali. "Reliable Latency-Aware Routing for Clustered WSNs." International Journal of Distributed Sensor Networks 8, no. 3 (2012): 681273. http://dx.doi.org/10.1155/2012/681273.

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4

Aráoz, Julián, Elena Fernández, and Carles Franquesa. "The Clustered Prize-Collecting Arc Routing Problem." Transportation Science 43, no. 3 (2009): 287–300. http://dx.doi.org/10.1287/trsc.1090.0270.

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5

Politi, Christina, Vasilis Anagnostopoulos, and Alexandros Stavdas. "Cross-layer routing in clustered optical networks." Photonic Network Communications 25, no. 1 (2012): 1–9. http://dx.doi.org/10.1007/s11107-012-0385-8.

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6

Battarra, Maria, Güneş Erdoğan, and Daniele Vigo. "Exact Algorithms for the Clustered Vehicle Routing Problem." Operations Research 62, no. 1 (2014): 58–71. http://dx.doi.org/10.1287/opre.2013.1227.

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7

Corberán, Ángel, Elena Fernández, Carles Franquesa, and José María Sanchis. "The Windy Clustered Prize-Collecting Arc-Routing Problem." Transportation Science 45, no. 3 (2011): 317–34. http://dx.doi.org/10.1287/trsc.1110.0370.

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8

Lin, Chen-Wan, and Bang Ye Wu. "On the minimum routing cost clustered tree problem." Journal of Combinatorial Optimization 33, no. 3 (2016): 1106–21. http://dx.doi.org/10.1007/s10878-016-0026-8.

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9

Vidal, Thibaut, Maria Battarra, Anand Subramanian, and Güneş Erdogˇan. "Hybrid metaheuristics for the Clustered Vehicle Routing Problem." Computers & Operations Research 58 (June 2015): 87–99. http://dx.doi.org/10.1016/j.cor.2014.10.019.

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10

Mohammad Osman, Et al. "Communication and Content Trust Aware Routing For Clustered IoT Network." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1614–23. http://dx.doi.org/10.17762/ijritcc.v11i10.8713.

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Security has become a major concern in practical applications related to Internet of Things, a Trust Aware Routing is found as second line of defence. To ensure a secure and hassle-free communication in IoT, this paper proposes a new routing strategy called as Communication and Content Trust Aware Routing (CCTAR) for Clustered IoT network. CCTAR is applied on a clustered IoT network in which the entire nodes are clustered into different clusters. Distance, initial energy, transmission range, angle of overlap and the sensing range are the fur major metrics used to cluster the network into hiera

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11

Kurle, Aishwarya, and K. R. Radhika. "Machine Learning Based Trust Routing for Clustered IoT devices." International Journal of Innovative Research in Applied Sciences and Engineering 4, no. 3 (2020): 675–80. http://dx.doi.org/10.29027/ijirase.v4.i3.2020.675-680.

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12

Tripathi, Meenakshi, M. S. Gaur, Vijay Laxmi, and R. B. Battula. "Balanced energy routing protocol for clustered wireless sensor network." International Journal of Information and Communication Technology 11, no. 3 (2017): 396. http://dx.doi.org/10.1504/ijict.2017.086833.

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13

Laxmi, Vijay, Meenakshi Tripathi, M. S. Gaur, and R. B. Battula. "Balanced energy routing protocol for clustered wireless sensor network." International Journal of Information and Communication Technology 11, no. 3 (2017): 396. http://dx.doi.org/10.1504/ijict.2017.10007931.

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14

Hoogeboom, Maaike, Maria Battarra, Güneş Erdoǧan, and Daniele Vigo. "Erratum—Exact Algorithms for the Clustered Vehicle Routing Problem." Operations Research 64, no. 2 (2016): 456–57. http://dx.doi.org/10.1287/opre.2016.1491.

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15

Sun, Qian, Jialong Pang, Xiaoyi Wang, Zhiyao Zhao, and Jing Li. "A Clustered Routing Algorithm Based on Forwarding Mechanism Optimization." IEEE Sensors Journal 24, no. 22 (2024): 38071–81. http://dx.doi.org/10.1109/jsen.2024.3467055.

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16

Santhiya, K. G., and N. Arumugam. "A Novel Adaptive Bio-Inspired Clustered Routing for MANET." Procedia Engineering 30 (2012): 711–17. http://dx.doi.org/10.1016/j.proeng.2012.01.918.

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17

Hintsch, Timo, and Stefan Irnich. "Exact solution of the soft-clustered vehicle-routing problem." European Journal of Operational Research 280, no. 1 (2020): 164–78. http://dx.doi.org/10.1016/j.ejor.2019.07.019.

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18

Gupta, Hari Prabhat, S. V. Rao, Amit Kumar Yadav, and Tanima Dutta. "Geographic Routing in Clustered Wireless Sensor Networks Among Obstacles." IEEE Sensors Journal 15, no. 5 (2015): 2984–92. http://dx.doi.org/10.1109/jsen.2014.2385734.

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19

Mohan, Ashwala, and Dr Bhanu Bhaskara. "Multi-dimensional trust aware routing for clustered IOT framework." International Journal of Engineering & Technology 7, no. 4.20 (2018): 15. http://dx.doi.org/10.14419/ijet.v7i4.20.22114.

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With the increased interest in the utilization of smart applications, the IoT has gained a lot of popularity in the real world scenario. Due to the integration of different heterogeneous devices in a single network, various types of security issues will arise in the IoT. To ensure more security in IoT, this paper proposes a new trust aware routing framework based on the inherent communication and data properties of devices connected in the network. A new trust metric is derived in this paper by combining two different trusts based on the communication between nodes and the information passing

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20

Khedr, Ahmed M., and Raj P. V. Pravija. "A hybrid MGO-JAYA based clustered routing for FANETs." Vehicular Communications 45 (February 2024): 100729. http://dx.doi.org/10.1016/j.vehcom.2024.100729.

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21

Weber, Maximilian, Ghofrane Fersi, Robert Fromm, and Faouzi Derbel. "Wake-Up Receiver-Based Routing for Clustered Multihop Wireless Sensor Networks." Sensors 22, no. 9 (2022): 3254. http://dx.doi.org/10.3390/s22093254.

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The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained networks. This technology allows energy-autonomous on-demand communication for continuous monitoring instead of the conventional radio. The routing process is one of the most energy and time-consuming processes in WSNs. It is, hence, crucial to conceive an energy-efficient routing process. In this paper, we propose a novel

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22

Diksha, Pandita, and Kumar Malik Ravi. "A Survey on Clustered and Energy Efficient Routing Protocols for Wireless Sensor Networks." International Journal of Trend in Scientific Research and Development 2, no. 6 (2018): 1026–30. https://doi.org/10.31142/ijtsrd18758.

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The main issue in WSN is energy limited characteristic of the sensor node. So the problem is to have the routing protocol in such the manner that it should be energy efficient in order to increase the life time of the whole WSN. Hierarchical routing architecture divides the whole network in to a group of cluster and only cluster head is responsible to forwarding the data to base station directly or via other cluster heads. In location based architecture of routing, localization of the sensor node is to be used to compute the path to the sensed data. During the creation of network topology, the

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23

Mahboub, Aziz, Mounir Arioua, and El Mokhtar En-Naimi. "Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2054. http://dx.doi.org/10.11591/ijece.v7i4.pp2054-2060.

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Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on K-Means clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimi

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24

Alqahtani, Jarallah, Hassan H. Sinky, and Bechir Hamdaoui. "Clustered Multicast Source Routing for Large-Scale Cloud Data Centers." IEEE Access 9 (2021): 12693–705. http://dx.doi.org/10.1109/access.2021.3051874.

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25

Grewal, Kiranjot, and Manoj Kumar. "A Clustered based Approach for Energy Efficient Routing in WSNs." International Journal of Computer Applications 169, no. 3 (2017): 36–39. http://dx.doi.org/10.5120/ijca2017914633.

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26

Kumar Dutta, Ashit, Yasser Albagory, Majed Alsanea, Abdul Rahaman Wahab Sait, and Hazim Saleh AlRawashdeh. "Fuzzy with Metaheuristics Based Routing for Clustered Wireless Sensor Networks." Intelligent Automation & Soft Computing 35, no. 1 (2023): 367–80. http://dx.doi.org/10.32604/iasc.2023.027076.

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27

Bansal, K., and P. Singh. "Energy Eficient Hierarchical Clustered Based Routing for Underwater Sensor Networks." International Journal of Computer Sciences and Engineering 5, no. 11 (2017): 115–19. http://dx.doi.org/10.26438/ijcse/v5i11.115119.

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28

Long, Xin, and Jianxin Wang. "Research on clustered routing optimization-based improved ant colony algorithm." Journal of Physics: Conference Series 2849, no. 1 (2024): 012065. http://dx.doi.org/10.1088/1742-6596/2849/1/012065.

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Abstract This paper addresses limitations in the traditional LEACH protocol, characterized by singular considerations in cluster head election and a single-hop data transfer mode, leading to imbalanced network electricity and early node depletion. An enhanced LEACH protocol is proposed, incorporating an improved ant colony algorithm. During cluster head election, the algorithm integrates energy, distance, and density factors to calculate the probability of node election, choosing the most suitable candidate. To create links and speed up data transfer, the method uses the augmented ant colony a

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29

Naidja, Miloud, and Azeddine Bilami. "A dynamic self-organising heterogeneous routing protocol for clustered WSNs." International Journal of Wireless and Mobile Computing 12, no. 2 (2017): 131. http://dx.doi.org/10.1504/ijwmc.2017.084182.

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30

Sanvito, Davide, Ilario Filippini, Antonio Capone, Stefano Paris, and Jérémie Leguay. "Clustered robust routing for traffic engineering in software-defined networks." Computer Communications 144 (August 2019): 175–87. http://dx.doi.org/10.1016/j.comcom.2019.06.002.

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31

Tao, Yaling, Yongbing Zhang, and Yusheng Ji. "Flow-balanced routing for multi-hop clustered wireless sensor networks." Ad Hoc Networks 11, no. 1 (2013): 541–54. http://dx.doi.org/10.1016/j.adhoc.2012.08.001.

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32

Hintsch, Timo, and Stefan Irnich. "Large multiple neighborhood search for the clustered vehicle-routing problem." European Journal of Operational Research 270, no. 1 (2018): 118–31. http://dx.doi.org/10.1016/j.ejor.2018.02.056.

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33

Zhao, Bin, and Kyung-Oh Lee. "A Clustered Directed Diffusion Routing Protocol for Wireless Sensor Network." Journal of the Korea Society of Computer and Information 16, no. 2 (2011): 165–72. http://dx.doi.org/10.9708/jksci.2011.16.2.165.

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34

Jadidoleslamy, Hossein. "A Hierarchical Multipath Routing Protocol in Clustered Wireless Sensor Networks." Wireless Personal Communications 96, no. 3 (2017): 4217–36. http://dx.doi.org/10.1007/s11277-017-4382-1.

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35

Li, Zexu, Yong Li, and Wenbo Wang. "Deep reinforcement learning-based collaborative routing algorithm for clustered MANETs." China Communications 20, no. 3 (2023): 185–200. http://dx.doi.org/10.23919/jcc.2023.03.014.

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36

Aziz, Mahboub, Arioua Mounir, and Mokhtar En-Naimi El. "Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2054–60. https://doi.org/10.11591/ijece.v7i4.pp2054-2060.

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Abstract:

Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and o

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37

Miao, Yihao, and Xiaoguang Bao. "An Improved Genetic Algorithm for Solving the Semi-Soft Clustered Vehicle Routing Problem." Applied Sciences 15, no. 9 (2025): 4871. https://doi.org/10.3390/app15094871.

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The Semi-Soft Clustered Vehicle Routing Problem (SemiSoftCluVRP) is a relaxed version of the Clustered Vehicle Routing Problem (CluVRP) and an enhanced variant of the Soft Clustered Vehicle Routing Problem (SoftCluVRP). In the SemiSoftCluVRP, all customers are partitioned into several clusters, and these clusters are further divided into two types: hard clusters and soft clusters. Within a hard cluster, customers must be served by the same vehicle without interruption, whereas within a soft cluster, customers must also be served by the same vehicle, but interruptions are permitted. To solve th

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38

Sheenam. "MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS." International Journal on Foundations of Computer Science & Technology (IJFCST) 5, no. 6 (2023): 18. https://doi.org/10.5281/zenodo.8120899.

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Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and communicating abilities. One of current concerns in wireless sensor networks is developing a stable clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery power. In the recent times, many routing protocols have been proposed increasing the network lifetime, stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of hierarchical clustered network with sensor nodes of two-level heterogeneity. The main a

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39

Liu, Zhen Xiang, Yong Heng Shi, Xin Wang, and Ming Xing Feng. "Research on Wireless Sensor Monitoring Networking Technology for Coal Mine Safety." Applied Mechanics and Materials 241-244 (December 2012): 960–66. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.960.

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According to the demand of coal mine safety monitoring, this paper proposes an improved clustered wireless sensor networking scheme. It analyzes the node sleep and wake-up mechanism, topology control, routing protocol, and designs the corresponding routing protocol LEACH-i. Finally, it carries out the system simulation.

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40

Pandita, Diksha, and Ravi Kumar Malik. "A Survey on Clustered and Energy Efficient Routing Protocols for Wireless Sensor Networks." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (2018): 1026–30. http://dx.doi.org/10.31142/ijtsrd18758.

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41

Batra, Dolly, Vishal Kumar, and Richa Sawhney. "Tree-Based Energy Efficient Clustered Routing Strategy for Wireless Sensor Networks." International Journal of Computer Applications 180, no. 25 (2018): 32–36. http://dx.doi.org/10.5120/ijca2018916590.

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42

Gupta, B., S. Rahimi, R. Jandhyala, and V. Doraiswamy. "A low-overhead DVR based multicast routing protocol for clustered MANET." Journal of Computational Methods in Sciences and Engineering 6, s1 (2007): S135—S146. http://dx.doi.org/10.3233/jcm-2006-6s111.

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43

BHEEMALINGAIAH, M., M. M. NAIDU, and D. Sreenivasa RAO. "Energy Aware Clustered Based Multipath Routing in Mobile Ad Hoc Networks." International Journal of Communications, Network and System Sciences 02, no. 02 (2009): 123–30. http://dx.doi.org/10.4236/ijcns.2009.22014.

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44

Daanoune, Ikram, Abdennaceur Baghdad, and Waheed Ullah. "Adaptive coding clustered routing protocol for energy efficient and reliable WSN." Physical Communication 52 (June 2022): 101705. http://dx.doi.org/10.1016/j.phycom.2022.101705.

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45

Kumar Dutta, Ashit, S. Srinivasan, Bobbili Prasada Rao, et al. "Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN." Computers, Materials & Continua 71, no. 2 (2022): 3785–801. http://dx.doi.org/10.32604/cmc.2022.023657.

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46

Halwan, V., F. Ozguner, and A. Dogan. "Routing in wormhole-switched clustered networks with applications to fault tolerance." IEEE Transactions on Parallel and Distributed Systems 10, no. 10 (1999): 1001–11. http://dx.doi.org/10.1109/71.808138.

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47

Amjad, Muhammad, Muhammad Khalil Afzal, Tariq Umer, and Byung-Seo Kim. "QoS-Aware and Heterogeneously Clustered Routing Protocol for Wireless Sensor Networks." IEEE Access 5 (2017): 10250–62. http://dx.doi.org/10.1109/access.2017.2712662.

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48

Horvat-Marc, Andrei, Levente Fuksz, Petrică C. Pop, and Daniela Dănciulescu. "A decomposition-based method for solving the clustered vehicle routing problem." Logic Journal of the IGPL 26, no. 1 (2017): 83–95. http://dx.doi.org/10.1093/jigpal/jzx037.

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49

Zahedi, Zeynab Molay, Reza Akbari, Mohammad Shokouhifar, Farshad Safaei, and Ali Jalali. "Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks." Expert Systems with Applications 55 (August 2016): 313–28. http://dx.doi.org/10.1016/j.eswa.2016.02.016.

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50

Lakshmi, N. V. S. Sree Rathna, S. Babu, and N. Bhalaji. "Analysis of clustered QoS routing protocol for distributed wireless sensor network." Computers & Electrical Engineering 64 (November 2017): 173–81. http://dx.doi.org/10.1016/j.compeleceng.2016.11.019.

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