Abstract
The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches.
Highlights
Wireless sensor networks (WSNs) have been used in various domains such as military applications and civil applications.Generally, a large number of sensor nodes, capable of collecting data, processing and communicating among themselves as well as with a base station (BS) are deployed in the sensing field to collect data according to a specific application
(d) We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption
Fuzzy logic-based approaches that utilise a fuzzy logic controller embedded in the sensor nodes have been used for cluster-head election [16], for reducing the deadline miss ratio associated with the real-time data transmission from the source node to the actuator maintained at a pre-determined desired level [17] and online routing algorithms to address the maximum lifetime routing problem in wireless sensor networks [18]
Summary
Wireless sensor networks (WSNs) have been used in various domains such as military applications (e.g., military surveillance) and civil applications (e.g., industrial control and wildlife monitoring). There are many data fusion mechanisms with the purpose of reducing the energy consumption for WSNs [1,2,3] These mechanisms use different techniques such as probability theory [4], fuzzy set theory [5], a combination of fuzzy sets and neural network [6] and Dempster-Shafer evidence theory (DSET) [7]. Most of these approaches are able to eliminate duplicate data in the fusion process. A fuzzy-based data fusion approach for WSNs that increases the QoS whilst maximizing the network lifetime by minimizing the energy consumption is presented.
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