Abstract
In Wireless sensor networks, energy efficiency is the significant attribute to be improved. Clustering is the major technique to enhance energy efficiency. Using this technique, sensor nodes in the network region are grouped as several clusters and cluster head (CH) is chosen for each and every cluster. This CH gathers data packet from the non-CH members inside the cluster and forwards the collected data packet to the base station. However, the CH may drain its energy after a number of transmissions. So, we present the Energy efficient Gravitational search algorithm (GSA) and Fuzzy based clustering with Hop count based routing for WSN in this paper. Initially, CH is selected using Gravitational Search Algorithm (GSA), based on its weight sensor nodes are joined to the CH and thus cluster is formed. Among the selected CHs in the network, supercluster head (SCH) is selected using a fuzzy inference system (FIS). This selected SCH gathers the data packet from all CHs and forwards it to the sink or base station. For transmission, the efficient route is established based on the hop count of the sensor nodes. Simulation results show that the performance of our proposed approach is superior to the existing work in terms of delivery ratio and energy efficiency.
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References
Afsar M, Mohammad H, Tayarani N, Aziz M (2015) An Adaptive Competition-Based Clustering Approach For Wireless Sensor Networks. Telecommun Syst 61(1):181–204
Arebi L, Gu F, Ball A (2012) A Comparative Study Of Misalignment Detection Using A Novel Wireless Sensor With Conventional Wired Sensors. J Phys Conf Ser 364:012049
Azharuddin, Md, and Jana PK (2016) PSO-Based Approach For Energy-Efficient And Energy-Balanced Routing And Clustering In Wireless Sensor Networks. Soft Computing. n. pag
Chowdhury C, Aslam N, Ahmed G, Chattapadhyay S, Neogy S, Zhang L (2017) Novel Algorithms for Reliability Evaluation of Remotely Deployed Wireless Sensor Networks. Wirel Pers Commun 98(1):1331–1360
Ding H (2013) Application Of Wireless Sensor Network In Target Detection And Localization. TELKOMNIKA Indonesian Journal of Electrical Engineering 11.10: n. pag
Ghosh K, Neogy S, Das P, Mehta M (2017) Intrusion Detection at International Borders and Large Military Barracks with Multi-sink Wireless Sensor Networks: An Energy Efficient Solution. Wirel Pers Commun 98(1):1083–1101
Gupta SK, Jana PK (2015) Energy Efficient Clustering And Routing Algorithms For Wireless Sensor Networks: GA Based Approach. Wirel Pers Commun 83(3):2403–2423
Han G, Zhang L (2017) WPO-EECRP: Energy-Efficient Clustering Routing Protocol Based on Weighting and Parameter Optimization in WSN. Wirel Pers Commun 98(1):1171–1205
K M, K C, C S (2018) An energy efficient clustering scheme using multilevel routing for wireless sensor network. Comput Electr Eng 69:642–652
Karaboga D, Okdem S, Ozturk C (2012) Cluster Based Wireless Sensor Network Routing Using Artificial Bee Colony Algorithm. Wirel Netw 18(7):847–860
Kulau U, Rottmann S, Schildt S, Balen J, Wolf L (2016) Undervolting in Real World WSN Applications: A Long-Term Study, 2016 International Conference on Distributed Computing in Sensor Systems (DCOSS)
Lalwani P et al. (2016) CRHS: Clustering And Routing In Wireless Sensor Networks Using Harmony Search Algorithm. Neural Computing and Applications: n. pag
Logambigai R, Kannan A (2015) Fuzzy Logic Based Unequal Clustering For Wireless Sensor Networks. Wirel Netw 22(3):945–957
"Micro Climate Monitoring-Web Application Using Wireless Sensor Network". International Journal of Science and Research (IJSR) 5.4 (2016): 104-106.
Mittal N, Singh U, Sohi BS (2017) A Novel Energy Efficient Stable Clustering Approach For Wireless Sensor Networks. Wireless Personal Communications: n. pag
Mottaghi S, Zahabi MR (2015) Optimizing LEACH Clustering Algorithm With Mobile Sink And Rendezvous Nodes. AEU - Int J Electron Commun 69(2):507–514
Qu MZ (2014) Research On The Applications And Characteristics Of The Wireless Sensor Network. Appl Mech Mater 538:498–501
Rabiya H, Rai Y (2016) Wireless Sensor Network. International Journal of Engineering and Computer Science: n. pag.
Sahoo RR et al (2015) A Bio Inspired And Trust Based Approach For Clustering In WSN. Nat Comput 15(3):423–434
Tawalbeh L, Hashish S, Tawalbeh H (2017) Quality of Service requirements and Challenges in Generic WSN Infrastructures. Proc Comput Sci 109:1116–1121
Wang T, Zhang G, Yang X, Vajdi A (2018) Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks. J Syst Softw 146:196–214
Yan C et al (2018) A Fast Uyghur Text Detector for Complex Background Images. IEEE Trans Multimedia 20(12):3389–3398
Yan C, Li L, Zhang C, Liu B, Zhang Y, Dai Q (2019) Cross-modality Bridging and Knowledge Transferring for Image Understanding, IEEE Transactions on Multimedia, pp. 1-1
Zheng J, Bhuiyan M, Liang S, Xing X, Wang G (2014) Auction-based adaptive sensor activation algorithm for target tracking in wireless sensor networks. Futur Gener Comput Syst 39:88–99
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Tomar, M.S., Shukla, P.K. Energy Efficient Gravitational Search Algorithm and Fuzzy Based Clustering With Hop Count Based Routing For Wireless Sensor Network. Multimed Tools Appl 78, 27849–27870 (2019). https://doi.org/10.1007/s11042-019-07844-2
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DOI: https://doi.org/10.1007/s11042-019-07844-2