# Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks
## 1 Introduction  
Wireless sensor networks (WSNs) consist of a large quantity of sensor nodes to offer a variety of services, such as environmental monitoring and security surveillance [1, 2]. Nowadays, WSNs are considered as one of the most promising technologies for cyber manufacturing systems in Industrial Internet of Things (IIoT) [3]. In smart factories, WSNs serve for intelligent industrial control applications in harsh environments [4, 5]. In order to provide highly reliable and realtime transmission, sensor nodes are often densely distributed in monitoring areas. However, the high density of node deployment causes lots of redundant data, and hence their forwarding brings in a large waste of the limited power and bandwidth, resulting in low energy efficiency and short network lifetime.  
In order to avoid the transmissions of redundant information, data aggregation is required in WSNs. In most of aggregation schemes, the whole network is separated into several areas like grids according to the geographical coordinates, and then the data collected by sensors in each area are aggregated by a particular node [6]. Because of the possible random distribution of nodes as well as the fixed size and shape of the aggregation area, the similarity of data collected by different sensors in one area is not close, which affects the performance of aggregation. Additionally, since there may be multiple hops from an ordinary node to an aggregation node, the redundant data might be forwardedfor several hops and hence lead to a high energy cost. Besides, an aggregation node has to wait for collecting all sensor data in its area before aggregation, which results in a long end-to-end delay [7; 8].  
In this paper, we propose a novel data aggregation scheme based on overlapping rate of sensing area in WSNs, named AggOR, to achieve energy-efficient data collection and keep high data accuracy. With respect to the sensing ranges, several nodes construct a gathering area if their overlapping rates of sensing area are no less than a preset threshold. In this way, the data in a gathering area have relatively high correlation and hence would be aggregated efficiently to eliminate redundancy. Moreover, there are only one or two levels of nodes in a gathering area. Usually a lower-level node transfers its sensing data to an upper-level node which aggregates and then delivers data to the sink. Therefore, redundant data are removed immediately after one-hop forwarding, which prohibits more energy consumption of redundancy relay. For further energy saving, an appropriate neighbor node at the same level could also be selected as the aggregation node if subject to particular conditions in the aggregation rules.  
The main advantages of our scheme are listed below. (1) Construct gathering areas according to the overlapping rate of sensing area. It helps to remove a large quantity of duplicated data and keep almost all entropy of the original information; (2) Three aggregation rules take full advantage of data aggregation by selecting aggregating nodes from candidate parent nodes or appropriate neighbor nodes. They limit the hops of redundancy forwarding and decrease the transmission overhead as much as possible; (3) A large quantity of experiments show that AggOR scheme keeps a high accuracy of data, improves energy efficiency and achieves a quick data collection.  
The rest of this paper is organized as follows. In Section 2, some related work on data aggregation in WSNs is discussed. Definitions and aggregation rules used in AggOR are introduced in Section 3, and Section 4 details the implementation of AggOR. Experimental results are analyzed in Section 5, and Section 6 concludes this paper.