Improved BEENISH Protocol for Wireless Sensor Networks Based Upon Fuzzy Inference System
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Improved BEENISH Protocol for Wireless Sensor Networks Based Upon Fuzzy Inference System

Authors: Rishabh Sharma, Renu Vig, Neeraj Sharma

Abstract:

The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: Wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system.

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[1] M. Benaddy, B. El Habil, M. El Ouali, O. El Meslouhi, S. Krit, “A mutlipath routing algorithm for wireless sensor networks under distance and energy consumption constraints for reliable data transmission”, 2017, International Conference on Engineering & MIS (ICEMIS), https://doi.org/10.1109/ICEMIS.2017.8273076
[2] Đ. Banđur, B. Jakšić, M. Banđur, S. Jović, “An Analysis of Energy Efficiency in Wireless Sensor Networks (WSNs) Applied in Smart Agriculture”, 2019, Computers and Electronics in Agriculture, Vol. 3, No. 26, pp. 564-573, https://doi.org/10.1016/j.compag.2018.12.016
[3] N. F. Ali, A. Md Said, K. Nisar, I. A. Aziz, “A Survey on Software Defined Network Approaches for Achieving Energy Efficiency in Wireless Sensor Network”, 2017, IEEE Conference on Wireless Sensors, Vol. 21, No. 17, pp. 674-682, https://doi.org/10.1109/ICWISE.2017.8267157
[4] Peyman Neamatollahi & Mahmoud Naghibzadeh, “Distributed unequal clustering algorithm in large-scale wireless sensor networks using fuzzy logic”, 2018, The Journal for Supercomputing, https://doi.org/10.1007/s11227-018-2261-5
[5] Trong-The Nguyen, Chin-Shiuh Shieh, Thi-Kien Dao, Jaw-Shyang Wu, Wu-Chih Hu, “Prolonging of the Network Lifetime of WSN Using Fuzzy Clustering Topology”, 2013, Second International Conference on Robot, Vision and Signal Processing, https://doi.org/10.1109/RVSP.2013.10
[6] D.V. Pushpalatha, Padmalaya Nayak, “A Clustering Algorithm for WSN to Optimize the Network Lifetime Using Type-2 Fuzzy Logic Model”, 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS), https://doi.org/10.1109/AIMS.2015.19
[7] Qi Wang, Elis Kulla, Gjergji Mino, Leonard Barolli, “Prediction of Sensor Lifetime in Wireless Sensor Networks Using Fuzzy Logic”, 2014, IEEE 28th International Conference on Advanced Information Networking and Applications, https://doi.org/10.1109/AINA.2014.137
[8] Gaurav Srikar, Reshmi TR, “A Fuzzy-Logic Based Clustering Algorithm in WSN to Extend NetworkLifetime”, International Journal of Applied Engineering Research, Volume 13, Number 10 (2018) pp. 7711-7718, https://doi.org/10.1109/JSEN.2015.2472970
[9] Hassan El Alami, AbdellahNajid, “Fuzzy Logic Based Clustering Algorithmfor Wireless Sensor Networks”, 2017, International Journal of Fuzzy System Applications, Volume 6, Issue 4, 10.4018/978-1-7998-2454-1.ch018
[10] Pankaj Kumar Mishra, and Shashi Kant Verma, “FFMCP: Feed-Forward Multi-Clustering Protocol Using FuzzyLogic for Wireless Sensor Networks (WSNs)”, 2021, Energies, https://doi.org/10.3390/en14102866
[11] Md. Abdul Alim, Yucheng Wu, Wei Wang, “A Fuzzy Based Clustering Protocol for Energy-efficient Wireless Sensor Networks”, 2013, Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering, https://doi.org/10.4028/www.scientific.net/AMR.760-762.685
[12] Abdulmughni Hamzah, Mohammad Shurman, Omar Al-JarrahandEyadTaqieddin, “Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks”, 2019, Sensors, https://doi.org/10.3390/s19030561
[13] Abhishek Rai, Kanika Sharma, “A Fuzzy Based Techniques for Energy Efficient Cluster Head Selection for Wireless Sensor Network”, 2019, International Journal of Engineering and Advanced Technology (IJEAT), Volume8, Issue6, 10.35940/ijeat.F8560.088619
[14] Vinod K, Kanika Sharma, “Routing Algorithm using Fuzzy Logic BasedClustering with Mobile Sink for Wireless SensorNetwork”, 2019, International Journal of Recent Technology and Engineering (IJRTE), Volume-8 Issue-4, November 2019, 10.35940/ijrte.D8629.118419
[15] Baranidharan Balakrishnan and Santhi Balachandran, “FLECH: Fuzzy Logic Based Energy Efficient Clustering Hierarchyfor Nonuniform Wireless Sensor Networks”, 2017, Hindawi, https://doi.org/10.1155/2017/1214720
[16] Mohd Adnan, Liu Yang, Tazeem Ahmad, Yang Tao, “An Unequally Clustered Multi-hop Routing Protocol Based on Fuzzy Logic for Wireless Sensor Networks”, 2021, IEEE Access, https://doi.org/10.1109/ACCESS.2021.3063097
[17] Marwa Fattoum, ZakiaJellali, Leïla Najjar Atallah, “Fuzzy Logic-based Two-Level Clustering for Data Aggregation in WSN”, 2020, 17th International Multi-Conference on Systems, Signals & Devices (SSD), https://doi.org/10.1109/SSD49366.2020.9364181
[18] Asmaa Mohamed, WalaaSaber, Ibrahim Elnahry, Aboul Ella Hassanien, “Coyote Optimization Based on a Fuzzy Logic Algorithm for Energy-Efficiency in Wireless Sensor Networks”, 2020, IEEE Access, https://doi.org/10.1109/ACCESS.2020.3029683
[19] Devendra Choudhary, Iti Sharma, “Using fuzzy logic for clustering in wireless sensor networks”, 2017, International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), https://doi.org/10.1109/ICICICT1.2017.8342678
[20] Swapna Ch, Vijayashree R Budyal, “Expectation Maximization and Fuzzy Logic Based Energy Efficient Data Collection in Wireless Sensor Networks with Mobile Elements”, 2020, 7th International Conference on Signal Processing and Integrated Networks (SPIN), http://dx.doi.org/10.1109/SPIN48934.2020.9071055
[21] Payam Rahimi, ChrysostomosChrysostomou, “Improving the Network Lifetime and Performance of Wireless Sensor Networks for IoT Applications Based on Fuzzy Logic”, 2019, 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), https://doi.org/10.1109/DCOSS.2019.00120
[22] Xin Zhao, Zhiqiang Wei, Yanping Cong, Bo Yin, “A Balances Energy Consumption Clustering Routing Protocol for a Wireless Sensor Network”, 2018, IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), https://doi.org/10.1109/ITOEC.2018.8740385
[23] Wenqi Zhang, Jingjing Yu, Xingchun Liu, Ying Tao, Shubo Ren, “Low-Energy Dynamic Clustering Scheme for Wireless Sensor Networks”, 2019, 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), https://doi.org/10.1109/PDCAT46702.2019.00031
[24] Sonam Lata, Shabana Mehfuz, Shabana Urooj, FadwaAlrowais, “Fuzzy Clustering Algorithm for Enhancing Reliability and Network Lifetime of Wireless Sensor Networks”, 2020, IEEE Access, https://doi.org/10.1109/ACCESS.2020.2985495
[25] ChaowananJamroen, PreechaKomkum, ChanonFongkerd, WipaKrongpha, “An Intelligent Irrigation Scheduling System Using Low-Cost Wireless Sensor Network Toward Sustainable and Precision Agriculture”, 2020, IEEE Access, https://doi.org/10.1109/ACCESS.2020.3025590
[26] Safana H. Abbas, Israa M. Khanjar, “Managing Data Transmission to Improve Lifetime of Wireless Sensor Network”, 2019, First International Conference of Computer and Applied Sciences (CAS), https://doi.org/10.1109/CAS47993.2019.9075466
[27] Amir Abbas Baradaran a, Keivan Navi b, “HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks “, 2019, Article in Press, Elsevier, https://doi.org/10.1016/j.fss.2019.11.015