Wireless sensor network (WSN) associated with a set of wireless sensor nodes by using high speed network connectivity. All deployed sensor nodes are used to sense and process of data effectively over the network. This leads to increase the communication overhead and affects the performance of the network lifetime. The main objective of the data aggregation is to eliminate the redundant data that increase the network lifetime otherwise prolongs or conserves the energy of the sensor nodes for data aggregation in WSN. Hence, it is needed to aggregate the sensed data into high quality information and this is accomplished through data aggregation. In this paper, reviews the data aggregation approaches named as centralized, tree, cluster, and in-network approaches in WSNs. Also discuss the comparison of various data aggregation approaches with respect to latency, data accuracy, computation overhead, scalability, redundancy, and energy consumption.

Wireless Sensor Network (WSN), Data Aggregation, Centralized, Tree, Cluster, and In-Network Approaches

[1] L. B., Bhajantri, H. C., Pavithra. M. Patil, “Context Aware Topology Control in Wireless Sensor Networks”, In the Proceedings of IEEE 2nd International Conference on Applied and Theoretical Computing and Communication Technology, pp.825-830, 2016.
[2] S. R., JinoRamson, D. J., Moni, “Applications of Wireless Sensor Networks: A Survey”, In the Proceedings of International Conference on Innovations in Electrical, Electronics, Instrumentation, and Media Technology, pp.325-329, 2017.
[3] S. Sharma, R. K., Bansal, S. Bansal, “Issues and Challenges in Wireless Sensor Networks”, In the Proceedings of International conference on Machine Intelligence and Research Advancement”, pp.58-62, 2013.
[4] H. Suo, J. Wan, L. Huang, C. Zou, “Issues and Challenges of Wireless Sensor Networks Localization in Emerging Applications”, In the Proceedings of International Conference on Computer Science and Electronics Engineering, vol.3, pp.447-451, 2012.
[5] A. Ihsan, K. Rahim, H. Mehdi, A. Mustaq, “Energy Aware Routing and Data Aggregation in Wireless Sensor Networks”, In the Proceedings of 2nd International Conference on Machine Learning and Computer Science, pp.27 - 30, 2013.
[6] K. Bhaskar, E. Deborah, W. Stephen,“The Impact of Data Aggregation in Wireless Sensor Networks”, In the Proceedings of International conference on Distributed Computing Systems, pp.575-578, 2002.
[7] C. Ramar, K. Rubasoundar, “A Survey on Data Aggregation Techniques in Wireless Sensor Networks”, International Journal of Mobile Network Design and Innovation, vol.6, no.2, pp.81-91, 2015.
[8] T. Dua, S.Qua, K. Liua, J.Xub, Y.Caob, “An Efficient Data Aggregation Algorithm for WSNs based on Dynamic Message List”, In the Proceedings of the 7th International Conference on Ambient Systems, Networks and Technologies, vol.83, pp.98-106, 2016.
[9] K. Haseeb, K.A., Bakar, A. H., Abdullah, T. Darwish, “Adaptive Energy Aware Cluster Based Routing Protocol for Wireless Sensor Networks, Journal on Wireless Networks, vol.23, no.6, pp.1953-1966, 2017.
[10] S. Sirsikar, S. Anavatti, “Issues of Data Aggregation Methods in Wireless Sensor Networks: A Survey”, In the Proceedings of the 4th International Conference on Advances in Computing, Communication and Control, vol.49, pp.194-201, 2015.
[11] A. Razaque, S. S., Rizvi, “Secure Data Aggregation using Access Control and Authentication for Wireless Sensor Networks”, Journal on Computers and Security, vol.70, pp.532-545,2017.
[12] S. S., Ranjani, S. Radhakrishnan, C.Thangaraj, “Secure Cluster Based Data Aggregation in Wireless Sensor Networks”, In the Proceedings of International Conference on Science Engineering and Management Research, pp.1-6, 2014.
[13] S. Nalini, A. Valarmathi, “Fuzzy Association Rule Based Cluster Head Selection in Wireless Sensor Networks”, In the Proceedings of 2nd International Conference on Green High Performance Computing”, pp.1-5, 2016.
[14] H. Harb, A. Makhoul, S. Tawbi, R. Couturier, “Comparison of Different Data Aggregation Techniques in Distributed Sensor Networks”, Journal of IEEE Access, vol.5, pp.4250-4263, 2017.
[15] L. B., Bhajantri, N. Nalini, “Context Aware Data Aggregation in Distributed Sensor Networks”, International Journal of Computer Networks and Wireless Communications, vol.6, no.6, pp.46-51, 2016.
[16] S. Roy, M. Conti, S. Setia, S. Jajodia, “Secure Data Aggregation in Wireless Sensor Networks”, IEEE Transaction on Information Forensics and Security, vol.7, no.3, pp.1040-1052, 2012.
[17] V. Kumar, S. Madria, “Secure Data Aggregation in Wireless Sensor Networks”, Springer Book Chapter on Wireless Technologies for the Information Explosion Era, pp.77-107, 2010.
[18] D. H., Rajesh, B. Paramasivan, “Fuzzy Logic Based Performance Optimization with Data Aggregation in Wireless Sensor Networks”, In the Proceedings of International Conference on Modeling Optimization and Computing, vol.38, pp.3331-3336, 2012.
[19] D. H., Rajesh, B. Paramasivan, “Survey of Data Aggregation Techniques Using Soft Computing in Wireless Sensor Networks”, IET International Journal on Security, vol.7, no.4, pp.336-342, 2013.
[20] N, A., Babamir, F, Orman, “A Tree Based Data Aggregation Scheme for Wireless Sensor Networks using Genetic Algorithm”, Journal on Wireless Sensor Network, vol.4, pp.191-196, 2012.
[21] F. Khorasani, H. R., Naji, “Energy Efficient Data Aggregation in Wireless Sensor Networks Using Neural Networks”, International Journal of Sensor Networks, vol.24, no.2, pp.26-42, 2017.