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NA Pantazis (2013)
10.1109/SURV.2012.062612.00084IEEE Commun Surveys Tuts, 15
P. Rao, P. Jana, H. Banka (2017)
A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networksWireless Networks, 23
A. Nayyar, Dac-Nhuong Le, Nhu Nguyen (2018)
Advances in Swarm Intelligence for Optimizing Problems in Computer Science
Ruonan Zhang, Jianping Pan, Di Xie, Fubao Wang (2016)
NDCMC: A Hybrid Data Collection Approach for Large-Scale WSNs Using Mobile Element and Hierarchical ClusteringIEEE Internet of Things Journal, 3
S. Mirjalili, A. Gandomi, S. Mirjalili, Shahrzad Saremi, Hossam Faris, S. Mirjalili (2017)
Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problemsAdv. Eng. Softw., 114
Y. Rani, E. Reddy (2021)
An optimal communication in WSN enabled by fuzzy clustering and improved meta-heuristic modelInt. J. Pervasive Comput. Commun., 19
Jenq-Shiou Leu, Tung-Hung Chiang, Min-Chieh Yu, Kuan-Wu Su (2015)
Energy Efficient Clustering Scheme for Prolonging the Lifetime of Wireless Sensor Network With Isolated NodesIEEE Communications Letters, 19
Jagdish Bansal, Harish Sharma, S. Jadon, M. Clerc (2014)
Spider Monkey Optimization algorithm for numerical optimizationMemetic Computing, 6
A. Nayyar, Rajeshwar Singh (2015)
A Comprehensive Review of Simulation Tools for Wireless Sensor Networks (WSNs), 5
Femi Aderohunmu, Jeremiah Deng, M. Purvis (2011)
A deterministic energy-efficient clustering protocol for wireless sensor networks2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing
Tarunpreet Kaur, Dilip Kumar (2018)
Particle Swarm Optimization-Based Unequal and Fault Tolerant Clustering Protocol for Wireless Sensor NetworksIEEE Sensors Journal, 18
P. Nayak, Bhavani Vathasavai (2017)
Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy LogicIEEE Sensors Journal, 17
J. Bezdek, R. Ehrlich, W. Full (1984)
FCM: The fuzzy c-means clustering algorithmComputers & Geosciences, 10
A. Nayyar, Nhu Nguyen (2018)
Introduction to Swarm IntelligenceAdvances in Swarm Intelligence for Optimizing Problems in Computer Science
Li Qing, Qingxin Zhu, Mingwen Wang (2006)
Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networksComput. Commun., 29
Gengzhong Zheng, Sanyang Liu, Xiaogang Qi (2012)
Clustering routing algorithm of wireless sensor networks based on Bayesian gameJournal of Systems Engineering and Electronics, 23
O. Younis, S. Fahmy (2004)
HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networksIEEE Transactions on Mobile Computing, 3
W. Heinzelman, A. Chandrakasan, H. Balakrishnan (2002)
An application-specific protocol architecture for wireless microsensor networksIEEE Trans. Wirel. Commun., 1
Jin-Shyan Lee, Wei Cheng (2012)
Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy PredicationIEEE Sensors Journal, 12
G. Anastasi, M. Conti, M. Francesco, A. Passarella (2009)
Energy conservation in wireless sensor networks: A surveyAd Hoc Networks, 7
Sadanand Yadav, Vinay Kumar (2017)
Optimal Clustering in Underwater Wireless Sensor Networks: Acoustic, EM and FSO Communication Compliant TechniqueIEEE Access, 5
N. Mittal, Urvinder Singh, Rohit Salgotra, B. Sohi (2018)
A boolean spider monkey optimization based energy efficient clustering approach for WSNsWireless Networks, 24
Z. Aliouat, S. Harous (2012)
An efficient clustering protocol increasing wireless sensor networks life time2012 International Conference on Innovations in Information Technology (IIT)
Jennifer Yick, B. Mukherjee, D. Ghosal (2008)
Wireless sensor network surveyComput. Networks, 52
S. Daneshvar, Pardis Mohajer, S. Mazinani (2019)
Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf OptimizerIEEE Access, 7
M. Abdullah-Al-Wadud, Md. Hamid (2014)
A fault-tolerant structural health monitoring protocol using wireless sensor networksannals of telecommunications - annales des télécommunications, 69
Sathyapriya Loganathan, Jawahar Arumugam (2020)
Energy centroid clustering algorithm to enhance the network lifetime of wireless sensor networksMultidimensional Systems and Signal Processing, 31
Priyanshu Gupta, Pallav Raj, Shwetanshu Tiwari, P. Kumari, P. Mehra (2020)
Energy Efficient Diagonal Based Clustering Protocol in Wireless Sensor NetworkSSRN Electronic Journal
Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks
Xiu-wu Yu, Liu Qin, Liu Yong, Mufang Hu, Zhang Ke, Renrong Xiao (2019)
Uneven clustering routing algorithm based on glowworm swarm optimizationAd Hoc Networks, 93
Y. Rani, E. Reddy (2021)
Stability-aware Energy Efficient Clustering Protocol in WSN using Opposition-based Elephant Herding OptimisationJournal of Control and Decision
A. Shahraki, Amirhosein Taherkordi, Øystein Haugen, F. Eliassen (2021)
A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking ParadigmsIEEE Transactions on Network and Service Management, 18
Deyu Lin, Quan Wang (2019)
An Energy-Efficient Clustering Algorithm Combined Game Theory and Dual-Cluster-Head Mechanism for WSNsIEEE Access, 7
Jin Liu, Juan Li, Xiaoguang Niu, Xiaohui Cui, Yunchuan Sun (2015)
GreenOCR: An Energy-Efficient Optimal Clustering Routing ProtocolComput. J., 58
Sudhir Kumar (2018)
Compartmental Modeling of Opportunistic Signals for Energy Efficient Optimal Clustering in WSNIEEE Communications Letters, 22
Shahrzad Saremi, S. Mirjalili, A. Lewis (2017)
Grasshopper Optimisation Algorithm: Theory and applicationAdv. Eng. Softw., 105
S. Swamy, B. Rajakumar, I. Valarmathi (2013)
Design of hybrid wind and photovoltaic power system using opposition-based genetic algorithm with Cauchy mutation
Nhat-Tien Nguyen, T. Le, Huy Nguyen, M. Voznák (2021)
Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSNSensors (Basel, Switzerland), 21
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Energy efficiency is one of the major challenges in the growing WSNs. Since communication offers a vast place in the consumption of energy, effective routing is the best solution to handle this problem. The lifetime improvement is an important problem since the majority of the WSNs function in an unattended environment, in which monitoring, as well as human access, is not possible in a practical manner. Clustering is one of the powerful approaches, which arranges the system operation for the enhanced lifetime of the network, improves energy efficiency, reduces the consumption of energy, and also attend the scalability of the network. To handle this issue, the present researchers have considered the usage of various clustering algorithms. Yet, the cluster head is burdened by the majority of the suggested algorithms in the process of cluster formation. To handle this problem, this paper plans to develop the energy-efficient clustering for WSN using the improved LEACH protocol. Here, the concept of a hybrid meta-heuristic algorithm is used for the optimal cluster head selection through energy-efficient clustering. The optimal solutions are rated based on the multi-objective function considering the objective constraints like energy, distance, delay, quality of service (QoS), load, and time of death. Communication between the sink node and cluster head uses the distance of separation as a parameter for reducing energy consumption. Two well-performing algorithms, like salp swarm algorithm (SSA) and grasshopper optimization algorithm (GOA) are merged to develop the proposed hybrid algorithm called salp-swarm grasshopper optimization (SS-GO). From the results, for 200 nodes, the normalized energy of SS-GO at 1400th round is 5.41%, 11.43%, 14.71%, and 25.81%, superior to GOA, SSO, O-EHO, and FU-CSA, respectively. Here, the performance of the proposed SS-GO is also higher in the other distance, delay, time of death node, and QOS. The performance of the introduced hybrid algorithm-based LEACH is evaluated in several different scenarios, and it is shown that the proposed protocol improves network lifetime in comparison to a number of the recent similar protocol.
Journal of Reliable Intelligent Environments – Springer Journals
Published: Dec 1, 2022
Keywords: Energy-efficient clustering protocol; Wireless sensor network; Multi-objective analysis; Salp-swarm grasshopper optimization
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