A survey on data aggregation techniques in IoT sensor networks

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Journal Article
Wireless Networks, 2020, 26, (2), pp. 1243-1263
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. There is a growing interest in using wireless sensor technologies in various Internet of things scenarios. Considering the huge growth of smart objects and their applications, the need to collect and analyze their product data are becoming one of the main challenges. Sensor nodes are powered by batteries, efficient operations in term of energy are critical. Toward that end, it is desirable for a sensor node to eliminate redundancies in the received data from the neighboring nodes before transferring the final data to the central station. Data aggregation is one of the influential techniques in elimination of data redundancy and improvement of energy efficiency; also it increases the lifespan of Wireless Sensor Networks. In addition, the efficient data aggregation protocol can reduce network traffic. When a specific objective takes place in a specific area, it might be detected by more than one sensor. Considering the main challenges and aspects of data aggregation in wireless sensor networks, a review on different types of data aggregation techniques and protocols are presented in this paper. The ultimate objective of this study is to make the basic foundations to develop new advanced designs based on data integration techniques and clustering that have been proposed so far. Major techniques of data integration in wireless sensor networks covering ground, underground and underwater sensor networks are presented in this paper and the applications, advantages and disadvantages of using each technique are described.
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