A Novel Approach for Reducing Energy Consumption using Binary Tree Structure in WSN
DOI:
https://doi.org/10.18486/ijcsnt/5.3.071Keywords:
Wsn, Data Aggregation, Cluster, Tree Based ApproachAbstract
Data aggregation is very vital method in wireless sensor networks. As the data aggregation decreases the energy utilization and efficiency increases. We are discussing about data aggregation and its various energy-efficient techniques used for data collection in WSN as well as representing diverse sorts of architectures, its requirements and classification. In our propose work we apply binary based approach for getting better result.
References
Zhao C. Treelet-based clustered compressive data aggregation for wireless sensor networks. IEEE; 10.1109/TVT.2014.2361250.
Rezaei Z and Mobininejad S. Energy saving in wireless sensor networks. International Journal of Computer Science & Engineering Survey; 10.5121/ijcses.2012.3103.
Tripathi A, Gupta S and Chourasiya B. Survey on data aggregation techniques for wireless sensor networks. International Journal of Advanced Research in Computer and Communication Engineering 2014; 3(7).
Dagar M and Mahajan S. Data aggregation in wireless sensor network: A survey. International Journal of Information and Computation Technology 2013; .
Baranidharan B and Shanthi B. A survey on energy efficient protocols for wireless sensor networks. International Journal of Computer Applications 2010; 11(10). 0975–8887. DOI: https://doi.org/10.5120/1616-2173
Le TN, Pegatoquet A, Huy TL et al. Improving energy efficiency of mobile WSN using reconfigurable directional antennas. IEEE; 10.1109/LCOMM.2016.2554544.
ZhiHui H. Research on WSN routing algorithm based on energy efficiency. In IEEE. 978-1-4673-9393-5/15, DOI 10.1109/ISDEA.2015.178.
Ahmed RZ and Biradar RC. Data aggregation for pest identification in coffee plantations using WSN: A hybrid model. In IEEE. 978-1-4673-7309-8/15.
Kumar S and Sah P. A survey on energy efficient protocols for wireless sensor network. International Journal of Computer Applications 2015; 120(2). 0975–8887. DOI: https://doi.org/10.5120/21197-3863
Sasidhar K, Sreeresmi R and Rekha P. A WSN lifetime improvement algorithm reaping benefits of data aggregation and state transitions. In IEEE. 978-1-4799-4097-4/14.
Marques BF and Ricardo MP. Improving the energy efficiency of WSN by using application-layer topologies to constrain RPL-defined routing trees. In IEEE. 978-1-4799-5258-8/14.
Shrivastava L, Tomar GS and Bhadoria S. Performance evaluation of reactive routing in mobile grid environment. International Journal of Grid and High Performance, IGI-Global Publishers 2011; 3(3): 45–53. DOI: https://doi.org/10.4018/jghpc.2011070104
Shrivastava L and Tomar G. A critical analysis of congestion adaptive routing protocols for mobile ad hoc networks. International Journal of Future Generation Communication and Networking 2016; 9(6): 9–16. DOI: https://doi.org/10.14257/ijfgcn.2016.9.6.02
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