Relevant bibliographies by topics / Heterogeneous WSN; cluster head; fuzzy logic

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Academic literature on the topic 'Heterogeneous WSN; cluster head; fuzzy logic'

Author: Grafiati
Published: 3 June 2025
Last updated: 22 June 2025

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Journal articles on the topic "Heterogeneous WSN; cluster head; fuzzy logic"

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Hao, ZiQi, ZhenJiang Zhang, and Han-Chieh Chao. "A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks." Journal of Sensors 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/641235.

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As limited energy is one of the tough challenges in wireless sensor networks (WSN), energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We usek-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.
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Anita, Mahato* Kailash Patidar. "A REVIWE ARTICLE OF COMPARITIVELY ANALYSIS OF DEEC PROTOCOL." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 6 (2017): 113–17. https://doi.org/10.5281/zenodo.805385.

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Energy Management can be improved by proficient clustering algorithms in heterogeneous wireless sensor networks. Coordination through cluster head selection provides efficient data aggregation that reduces communication overhead in the network. In this paper, we propose a fuzzy logic approach based DDEEC clustering algorithm which aims to prolong the lifetime of nodes in heterogeneous WSNs. We compare this algorithm with the PSO based DDEEC algorithm and original DDEEC algorithm according to the parameters of first node dies at different rounds and energy-efficiency metrics. The efficiency of proposed optimized fuzzy algorithm is proved by the Matlab experimental results. Simulation results exhibits that the proposed algorithm has higher energy efficiency and can improve life span of a node and data delivery at the base station over its comparatives.
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Rizwan, Muhammad, Muhammad S. Nisar, and Hongbo Jiang. "F-MEEP: Fuzzy Logic Based Multihop Energy Efficient Routing Protocol for HWSN." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 14 (2016): 7406–15. http://dx.doi.org/10.24297/ijct.v15i14.4796.

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Energy preservation is one of the most important research challenges in Wireless Senor Networks (WSNs). In recent research, topologies and architectures have investigated that allow energy efficiency in WSNs. Clustering is one of the most famous energy efficient techniques. In clustering, the selection of cluster head (CH) and short distance multi-hop energy efficient communication between CH and base station (BS) plays a vital role in order to achieve the desired energy efficiency in the sensor network. In this energy saving solution, we purpose and combine the idea of fuzzy logic based CH selection and multihop short distance communication between CH and base station in order to prolong the stable period and life span of network. Our proposed routing protocol, Fuzzy Logic based Multihop Energy Efficient Routing Protocol (FMEEP) for Heterogeneous WSN, which uses fuzzy logic inference system (FIS) in order to select a qualified CH in the cluster formation process and minimizes the overall energy dissipation in the sensor network. The simulation results have shown that purposed routing scheme outperforms in terms of stability period and network lifetime as compared to previous routing protocols.Â
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Al-Zabin, Lial Raja, Ola A. Al-Wesabi, Hamed Al Hajri, Nibras Abdullah, Baidaa Hamza Khudayer, and Hala Al Lawati. "Probabilistic Detection of Indoor Events Using a Wireless Sensor Network-Based Mechanism." Sensors 23, no. 15 (2023): 6918. http://dx.doi.org/10.3390/s23156918.

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Wireless sensor networks (WSNs) have been commonly utilized in event detection and environmental observation applications. The main aim of event detection is to define the presence or absence of an event. Various existing studies in the field of event detection depend on static or threshold values to reveal the occurrence of an event, which can result in imprecise sensor readings. Recently, many studies have utilized fuzzy logic to treat fluctuating sensor readings; as a result, they have decreased the number of false alarms created. However, there is some attention required when utilizing fuzzy logic. One aspect is that the efficiency and accuracy of the fuzzy membership function can be impacted by the utilization of heterogeneous sensors, which may increase the complexity of the fuzzy logic operation as the number of inputs rises. To address these issues, this paper proposes an approach named Probabilistic Collaborative Event Detection (PCED), which is a hybrid event detection technique that is based on a cluster WSN topology. The PCED approach utilizes a validated probabilistic technique for heterogeneous sensor nodes to transform sensing values into probability formulas and introduces a Cluster Head Decision Mechanism to make decisions based on the aggregated data from the sensors. The proposed approach employs fuzzy logic at the fusion center level to enhance the precision of event detection. The effectiveness of this method is thoroughly evaluated using MATLAB software, demonstrating an improvement in the probability of detection and a decrease in the probability of false alarms. PCED is compared to well-established event detection mechanisms such as the REFD mechanism. The results show that PCED reduces the occurrence of false alarms from 37 to 3 in certain scenarios, while improving detection accuracy by up to 19.4% over REDF and decreasing detection latency by up to 17.5%.
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Avinashjethi, Surender Singh and Yadwinder Singh. "Improved Hybrid Energy Aware Clustered Protocol for IoT Heterogeneous Network for WSN using Fuzzy Logic." International Journal for Modern Trends in Science and Technology 7, no. 07 (2022): 49–53. http://dx.doi.org/10.46501/ijmtst051009.

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The wireless sensor networks consist of numerous small battery-powered nodes. These networks provide a support to IoT applications related to agriculture, healthcare etc. Increasing the lifetime of the sensor nodes is a major issue. To increase the lifespan of the nodes in WSN, in the proposed protocol, clustering protocol have been presented where the cluster heads are selected according to fitness value of the nodes. The performance was evaluated based on number of dead nodes and throughput of the network. The better values of these parameters indicate the proposed protocol outperformed the existing one.
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Sarath kumar, A., M. Durga Kaveri, K. B.V Bhargavi, N. Naga Swetha, and K. Priyanka. "Efficient Routing In Wsn Using Enhanced Fuzzy Logic." International Journal of Engineering & Technology 7, no. 2.17 (2018): 108. http://dx.doi.org/10.14419/ijet.v7i2.17.11719.

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In order to gather info additional precisely, wireless detector networks (WSNs) square measure divided into clusters. The cluster provides a good merit to make longer the period of WSNs. Topical clump comes close to usually use 2 methods: choosing cluster heads with additional enduring energy, and turning cluster heads sporadically, to distribute the energy consumption among nodes in every cluster and extend the network period. However, most of the previous algorithms haven't thought of the expected residual energy, that is, that the predicated left behind energy for being hand-picked as a cluster head and running around. During this paper, a fuzzy-logic-based clump approach [22] with associate degree conservatory to the energy postulation has been planned to lengthen the period of WSNs by equally distributing the work. The simulation results show that the planned come close to is additional more economical than alternative distributed algorithms. It's believed that the practice given during this paper can be any applied to extensive wireless detector networks.
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Safana, H. Abbas, and M. Khanjar Israa. "Fuzzy Logic Approach for Cluster-Head Election in Wireless Sensor Network." International Journal of Engineering Research and Advanced Technology (IJERAT) 5, no. 7 (2019): 14–25. https://doi.org/10.31695/IJERAT.2019.3460.

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<em>Wireless Sensor Network (WSN) consists of small battery-powered sensor nodes with limited energy resources, with sensing, computation, and communications capabilities. One of the crucial issues in WSN is energy consumption thus, poor energy efficient routing. The lifetime of the entire network depending on the energy efficiency of the sensor network which finally requires an energy- efficient routing protocol. This paper provides energy-efficient routing by using a fuzzy logic approach in the cluster-head selection process that provides a completely non-probabilistic approach in order to balance the energy consumption of nodes and prolong the WSN lifetime. This approach uses three fuzzy variables: Residual energy of the nodes, distance to Base station and distance to the cluster-head. Simulations results show that the proposed algorithm improves energy consumption and significantly prolong the network lifetime in wireless sensor networks when compared with LEACH protocol.</em>
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Julie, E. Golden, and S. Tamil Selvi. "Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach." Scientific World Journal 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/5063261.

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Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.
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Saadi, Amnah A., and Osama A. Awad. "LIFETIME MAXIMIZATION OF A MOBILE WSN USING ZRP-FUZZY CLUSTERING PROTOCOL BASED ON ANT-LION OPTIMIZER." Iraqi Journal of Information and Communications Technology 1, no. 1 (2021): 70–82. http://dx.doi.org/10.31987/ijict.1.1.171.

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Wireless Sensor Networks require energy-efficient protocols for communication and data fusion to integrate data and extend the lifetime of the network. An efficient clustering algorithm for sensor nodes will optimize the energy efficiency of WSNs. However, the clustering process requires additional overhead, such as selection of cluster head, cluster creation, and deployment. This paper prepared a modified ZRP for mobile WSN clustering scheme and optimization using ant-lion optimization algorithm and so far named as mobility cluster head fuzzy logic based on the zone routing protocol (ZRP-FMC-ALO). Which proposed fuzzy logic approach based on three descriptors node for the selection of the CH nodes such as, residual energy, the concentration, and the centrality of the node and also exploited the concept of the mobility of the Base Station (BS) to prolong the life span of a WSN. The performance of the proposed protocol compared with the famous protocol such as LEACH. Using the MATLAB simulator and the result shows that it outperforms in terms of the WSN network lifetime, the average remaining-consuming energy, and the number of a live node.
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Samara, Ghassan, Mohammad Hassan, and Yahya Zayed. "An Intelligent Vice Cluster Head Election Protocol in WSN." International Journal of Advances in Soft Computing and its Applications 13, no. 3 (2021): 202–22. http://dx.doi.org/10.15849/ijasca.211128.14.

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Wireless sensor networks (WSNs) has a practical ability to link a set of sensors to build a wireless network that can be accessed remotely; this technology has become increasingly popular in recent years. Wi-Fi-enabled sensor networks (WSNs) are used to gather information from the environment in which the network operates. Many obstacles prevent wireless sensor networks from being used in a wide range of fields. This includes maintaining network stability and extending network life. In a wireless network, sensors are the most essential component. Sensors are powered by a battery that has a finite amount of power. The battery is prone to power loss, and the sensor is therefore rendered inoperative as a result. In addition, the growing number of sensor nodes off-site affects the network's stability. The transmission and reception of information between the sensors and the base consumes the most energy in the sensor. An Intelligent Vice Cluster Head Selection Protocol is proposed in this study (IVC LEACH). In order to achieve the best performance with the least amount of energy consumption, the proposed hierarchical protocol relies on a fuzzy logic algorithm using four parameters to calculate the value of each node in the network and divides them into three hierarchical levels based on their value. This improves network efficiency and reliability while extending network life by 50 percent more than the original Low Energy Adaptive Clustering Hierarchy protocol. Keywords: Wireless Sensor Networks, Sensors, Communication Protocol, Fuzzy logic, Leach protocol.
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Book chapters on the topic "Heterogeneous WSN; cluster head; fuzzy logic"

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Ghosh, Ramkrishna, Suneeta Mohanty, Prasant Kumar Pattnaik, and Sabyasachi Pramanik. "A Novel Approach Towards Selection of Role Model Cluster Head for Power Management in WSN." In Machine Learning Applications in Non-Conventional Machining Processes. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3624-7.ch015.

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In this chapter, the authors present an innovative, smart controller to sustain mobility in wireless sensor networks (WSNs). Principally, the focal point is dependent on the arrangement of fuzzy input variables (i.e., remaining battery power [RBP], mobility, and centrality solution) to crucial usages, similar to personnel safety in an industrialized atmosphere. A mobility controller dependent upon type-1 fuzzy logic (T1FL) is planned to support sensor mobile nodes (MN). Here, a role model cluster head (RMCH) is picked out among the cluster heads (CHs) that may simply convey the message to the mobile base station (BS) by determining the appropriate type-1 fuzzy (T1F) descriptors such as RBP, mobility of the sink, and the centrality of the clusters. Type-1 fuzzy inference system (Mamdani's rule) is utilized to opt for the possibility to be RMCH. The validity of the introduced model is carried out by means of multiple linear regressions.
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Elmazi, Donald, Evjola Spaho, Keita Matsuo, Tetsuya Oda, Makoto Ikeda, and Leonard Barolli. "F3N." In Mobile Computing and Wireless Networks. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8751-6.ch044.

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Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that Wireless Sensor Networks (WSNs) research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in WSN applications and can drastically affect the net- work's communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, the authors propose a power reduction algorithm for WSNs based on Fuzzy Logic (FL) and Number of Neighbour Nodes (3N). They call this system F3N. The authors evaluate F3N and LEACH by many simulation results. The performance of F3N system is evaluated for tree different parameters: Remaining Battery Power of Sensor (RPS); Degree of Number of Neighbour Nodes (D3N); and Distance from Cluster Centroid (DCC). From the simulation results, they found that the probability of a sensor node to be a cluster head is increased with increase of number of neighbour nodes and remained battery power and is decreased with the increase of distance from the cluster centroid.
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Conference papers on the topic "Heterogeneous WSN; cluster head; fuzzy logic"

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Jagadeesh, S., P. Suresh Pandiarajan, Jayaraman Kumarappan, Karthika, P. N. Karthikayan, and Rajesh Devaraj. "Enhancing Energy Efficiency in WSN Through Multiple Cluster Head Selection and Fuzzy Logic." In 2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE). IEEE, 2024. http://dx.doi.org/10.1109/amathe61652.2024.10582197.

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Batra, Payal Khurana, and Rashmi Kushwah. "Fuzzy Logic based Cluster Head Selection method for Heterogeneous Wireless Sensor Networks." In 2019 Fifth International Conference on Image Information Processing (ICIIP). IEEE, 2019. http://dx.doi.org/10.1109/iciip47207.2019.8985903.

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Tripathi, Ankit, Saima Khan, and Shivendra Singh. "Secure and Success Rate of Packet for WSN using Leach Cluster Head Fuzzy Logic." In 2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS). IEEE, 2020. http://dx.doi.org/10.1109/sceecs48394.2020.199.

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Ben Alla, Said, Abdellah Ezzati, and Ahmed Mohsen. "Gateway and Cluster Head Election using Fuzzy Logic in heterogeneous wireless sensor networks." In 2012 International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2012. http://dx.doi.org/10.1109/icmcs.2012.6320203.

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Manikandan, V., Dinesh Mavaluru, K. Gobinathan, S. Rajanarayanan, M. Jenifer, and R. Rohini. "Virtual Cluster Head Based PSO and Fuzzy Logic Approach for WSN to Extend Network Lifetime." In 2020 International Conference on Computing and Information Technology (ICCIT-1441). IEEE, 2020. http://dx.doi.org/10.1109/iccit-144147971.2020.9213823.

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Ranjith, Rinu Sara, and H. N. Vishwas. "Analysis study of data buffer policies in a fuzzy logic based WSN using cluster head." In 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon). IEEE, 2017. http://dx.doi.org/10.1109/smarttechcon.2017.8358492.

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Ranjith, Rinu Sara, and H. N. Vishwas. "Evaluation study of secondary cluster head selection using fuzzy logic in WSN for conservation of battery energy." In 2017 International Conference on Inventive Communication and Computational Technologies (ICICCT). IEEE, 2017. http://dx.doi.org/10.1109/icicct.2017.7975157.

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Ali Adem, Mohammed. "Energy Optimization of Wireless Sensor Network Using Neuro-Fuzzy Algorithms." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai2019120814.

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Wireless sensor network (WSN) is one of the recent technologies in communication and engineering world to assist various civilian and military applications. They are deployed remotely in sever environment which doesn’t have an infrastructure. Energy is a limited resource that needs efficient management to work without any failure. Energy efficient clustering of WSN is the ultimate mechanism to conserve energy for longtime. The major objective of this research is to efficiently consume energy based on the Neuro-Fuzzy approach particularly adaptive Neuro fuzzy inference system (ANFIS). The significance of this study is to examine the challenges of energy efficient algorithms and the network lifetime on WSN so that they can assist several applications. Clustering is one of the hierarchical based routing protocols, which manage the communication between sensor nodes and sink via Cluster Head (CH), CH is responsible to send and receive information from multiple sensor nodes and multiple base stations (BS). There are various algorithms that can efficiently select appropriate CH and localize the membership of cluster with fuzzy logic classification parameters to minimize periodic clustering which consumes more energy and we have applied neural network learning algorithm to learn various patterns based on the fuzzy rules and measured how much energy has saved from random clustering. Finally, we have compared to our Neuro-Fuzzy logic and consequently demonstrated that our Neuro-Fuzzy model outperforms than random model.
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