Wireless sensor networks afford the possibility to control remote monitoring of many environments (such as military ones) by hundreds of tiny sensor nodes. Restriction of energy consumption is a major challenge in these networks, which will affect the lifetime of the network. One of the key solutions to solving the challenge is data aggregation and avoiding of repeated data sending. The most popular communication protocols are clustering and tree based data aggregation. Clustering in data aggregation issue leads to energy balance, but energy consumption is high due to long distances between cluster heads and base station. In the tree structure, due to short distances between nodes, energy consumption is low but, the depth of the tree is usually high. In this paper, a hybrid analytical hierarchical process named CTDA is proposed in which energy consumption is reduced by clustering and minimum spanning tree for data aggregation in wireless sensor networks. The simulation of the proposed method illustrates reduction in energy consumption compared to two aformentioned protocols.
Saadati, Z., & Sajedi, H. (2019). Data Aggregation in Wireless Sensor Networks Based on Clustering and Minimum Spanning Tree. Journal of Advanced Defense Science & Technology, 4(4), 293-300.
MLA
Z. Saadati; H. Sajedi. "Data Aggregation in Wireless Sensor Networks Based on Clustering and Minimum Spanning Tree", Journal of Advanced Defense Science & Technology, 4, 4, 2019, 293-300.
HARVARD
Saadati, Z., Sajedi, H. (2019). 'Data Aggregation in Wireless Sensor Networks Based on Clustering and Minimum Spanning Tree', Journal of Advanced Defense Science & Technology, 4(4), pp. 293-300.
VANCOUVER
Saadati, Z., Sajedi, H. Data Aggregation in Wireless Sensor Networks Based on Clustering and Minimum Spanning Tree. Journal of Advanced Defense Science & Technology, 2019; 4(4): 293-300.
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