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International Journal of Sensor Networks, 24
Xiaorong Zhu, Lianfeng Shen, T. Yum (2007)
Hausdorff Clustering and Minimum Energy Routing for Wireless Sensor NetworksIEEE Transactions on Vehicular Technology, 58
Senthil Nagarajan, V. Muthukumaran, R. Murugesan, Rose Joseph, Meram Munirathanam (2021)
Feature selection model for healthcare analysis and classification using classifier ensemble techniqueInternational Journal of Systems Assurance Engineering and Management
Gao Yi, Sun Guiling, Liang Weixiang, Pan Yong (2009)
Recluster-LEACH: A recluster control algorithm based on density for wireless sensor network2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS), 3
G. Venkataraman, S. Emmanuel, S. Thambipillai (2005)
DASCA: A Degree and Size based Clustering Approach for Wireless Sensor Networks2005 2nd International Symposium on Wireless Communication Systems
Haixia Tan, Weilin Zeng, L. Bao (2005)
PATM: Priority-Based Adaptive Topology Management for Efficient Routing in Ad Hoc Networks
Q. Tang, Kun Yang, Ping Li, Jianming Zhang, Yuan-sheng Luo, Bing Xiong (2012)
An energy efficient MCDS construction algorithm for wireless sensor networksEURASIP Journal on Wireless Communications and Networking, 2012
Donghyun Kim, Yiwei Wu, Yingshu Li, Feng Zou, D. Du (2009)
Constructing Minimum Connected Dominating Sets with Bounded Diameters in Wireless NetworksIEEE Transactions on Parallel and Distributed Systems, 20
P. Wan, K. Alzoubi, O. Frieder (2002)
Distributed Construction of Connected Dominating Set in Wireless Ad Hoc NetworksMobile Networks and Applications, 9
M. Faheem, A. Ngadi, Saqib Ali, M. Shahid, L. Sakar (2013)
Energy based Efficiency Evaluation of Cluster-Based Routing Protocols for Wireless Sensor Networks (WSNs)International Journal of Software Engineering and its Applications, 7
M. Watfa, O. Mirza, J. Kawtharani (2009)
BARC: A Battery Aware Reliable Clustering algorithm for sensor networksJ. Netw. Comput. Appl., 32
N. Aslam, W. Phillips, W. Robertson, S. Sivakumar (2011)
A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networksInf. Fusion, 12
B. Lakshmi, M. Neelima (2012)
Maximising Wireless sensor Network life time through cluster head selection using Hit sets
Rui Wang, Guozhi Liu, C. Zheng (2007)
A Clustering Algorithm based on Virtual Area Partition for Heterogeneous Wireless Sensor Networks2007 International Conference on Mechatronics and Automation
S. Guha, S. Khuller (1996)
Approximation Algorithms for Connected Dominating SetsAlgorithmica, 49
Fereshteh Khorasani, H. Naji (2017)
Energy efficient data aggregation in wireless sensor networks using neural networksInt. J. Sens. Networks, 24
Li-Qing Guo, Yi Xie, Chenhui Yang, Zheng-Wei Jing (2010)
Improvement on LEACH by combining Adaptive Cluster Head Election and Two-hop transmission2010 International Conference on Machine Learning and Cybernetics, 4
(2021)
Design and evaluation of Wi-Fi offloading mechanism in heterogeneous network
Yuanyuan Zeng, X. Jia, Yanxiang He (2006)
Energy efficient distributed connected dominating sets construction in wireless sensor networks
IEEE Computer Society, 1
In wireless sensor networks, improving the network lifetime is considered as the prime objective that needs to be significantly addressed during data aggregation. Among the traditional data aggregation techniques, cluster-based dominating set algorithms are identified as more effective in aggregating data through cluster heads. But, the existing cluster-based dominating set algorithms suffer from a major drawback of energy deficiency when a large number of communicating nodes need to collaborate for transferring the aggregated data. Further, due to this reason, the energy of each communicating node is gradually decreased and the network lifetime is also decreased. To increase the lifetime of the network, the proposed algorithm uses two sets: Dominating set and hit set.Design/methodology/approachThe proposed algorithm uses two sets: Dominating set and hit set. The dominating set constructs an unequal clustering, and the hit set minimizes the number of communicating nodes by selecting the optimized cluster head for transferring the aggregated data to the base station. The simulation results also infer that the proposed optimized unequal clustering algorithm (OUCA) is greater in improving the network lifetime to a maximum amount of 22% than the existing cluster head selection approach considered for examination.FindingsIn this paper, lifetime of the network is prolonged by constructing an unequal cluster using the dominating set and electing an optimized cluster head using hit set. The dominator set chooses the dominator based on the remaining energy and its node degree of each node. The optimized cluster head is chosen by the hit set to minimize the number of communicating nodes in the network. The proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit set. The simulation result confirms that the proposed algorithm prolonging the lifetime of the network efficiently when compared with the existing algorithms.Originality/valueThe proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit sets. The simulation result confirms that the proposed algorithm is prolonging the lifetime of the network efficiently when compared with the existing algorithms.
International Journal of Intelligent Computing and Cybernetics – Emerald Publishing
Published: Sep 22, 2022
Keywords: Unequal clustering; Hit set; Dominating set; Network lifetime
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