Article
Data Aggregation Based on Overlapping Rate of
Sensing Area in Wireless Sensor Networks
Xiaolan Tang
1
, Hua Xie
1
, Wenlong Chen
1,
*, Jianwei Niu
2,3
and Shuhang Wang
4
1
College of Information Engineering, Capital Normal University, Beijing 100048, China;
tangxl@cnu.edu.cn (X.T.); 2151002064@cnu.edu.cn (H.X.)
2
State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and
Engineering, Beihang University, Beijing 100191, China; niujianwei@buaa.edu.cn
3
Research Institute of Beihang University in Shenzhen, Shenzhen 518057, China
4
Schepens Eye Research Institute, Harvard Medical School, Boston, MA 02114, USA;
shuhang_wang@meei.harvard.edu
* Correspondence: chenwenlong@cnu.edu.cn; Tel.: +86-10-6890-1370 (ext. 232)
Received: 26 April 2017; Accepted: 20 June 2017; Published: 29 June 2017
Abstract:
Wireless sensor networks are required in smart applications to provide accurate control, where
the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste
of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However,
most of aggregation schemes reduce information accuracy and prolong end-to-end delay when
eliminating transmission overhead. In this paper, we propose a data aggregation scheme based
on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in
wireless sensor networks with high information accuracy. According to aggregation rules, gathering
nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset
threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are
highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps
the original entropy by only deleting the duplicated data. Experiment results show that compared with
others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.
Keywords:
wireless sensor networks; data aggregation; overlapping rate of sensing area; data accuracy
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 forwarded
Sensors 2017, 17, 1527; doi:10.3390/s17071527 www.mdpi.com/journal/sensors
