scholarly journals A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
ZiQi Hao ◽  
ZhenJiang Zhang ◽  
Han-Chieh Chao
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Data Fusion ◽  
Event Detection ◽  
Base Station ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Local Decision ◽  
Fuzzy Logic Method

As limited energy is one of the tough challenges in wireless sensor networks (WSN), energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We usek-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

scholarly journals A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 784 ◽  
Author(s):  
Jiayao Wang ◽  
Olamide Tawose ◽  
Linhua Jiang ◽  
Dongfang Zhao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Base Station ◽  
Fuzzy Entropy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Time Performance

The wireless sensor network (WSN) is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and energy consumption in the network, extend the network life cycle, improve the utilization of bandwidth, and thus overcome the bottleneck on energy and bandwidth consumption. This paper proposes a new data fusion algorithm based on Hesitant Fuzzy Entropy (DFHFE). The new algorithm aims to reduce the collection of repeated data on sensor nodes from the source, and strives to utilize the information provided by redundant data to improve the data reliability. Hesitant fuzzy entropy is exploited to fuse the original data from sensor nodes in the cluster at the sink node to obtain higher quality data and make local decisions on the events of interest. The sink nodes periodically send local decisions to the base station that aggregates the local decisions and makes the final judgment, in which process the burden for the base station to process all the data is significantly released. According to our experiments, the proposed data fusion algorithm greatly improves the robustness, accuracy, and real-time performance of the entire network. The simulation results demonstrate that the new algorithm is more efficient than the state-of-the-art in terms of both energy consumption and real-time performance.

scholarly journals A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (11) ◽  
pp. 2555 ◽  
Author(s):  
Tengyue Zou ◽  
Yuanxia Wang ◽  
Mengyi Wang ◽  
Shouying Lin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Real Time ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Weighted Data

scholarly journals Increasing Network Lifetime In Cluster Based Wireless Sensor Networks Via Fuzzy Logic

2021 ◽  
Author(s):  
Rouzbeh Behrouz
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Large Scale ◽  
Fuzzy Inference ◽  
Critical Issue ◽  
Base Station ◽  
Wireless Sensor ◽  
Inference System ◽  
Efficient Operation

Energy efficient operation is a critical issue that has to be addressed with large-scale wireless sensor networks deployments. Cluster-based protocols are developed to tackle this problem and Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the best-known protocols of this type. However, certain aspects of LEACH offer room for improvement. One such aspect is the arrangement of wireless sensor network with the fixed base station location. In this thesis we purpose Fuzzy Logic for Mobile Base Station (FLMBS) protocol that is based on LEACH but uses a Fuzzy Inference System driven approach to adjust the location of the base station. FLMBS produces reasonable improvement over LEACH in a network area greater than 1000 x 1000 m

scholarly journals A Fuzzy Data Fusion Solution to Enhance the QoS and the Energy Consumption in Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Mario Collotta ◽  
Giovanni Pau ◽  
Alexander V. Bobovich
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Quality Data ◽  
Suggested Approach ◽  
True Value

Wireless Sensor Networks (WSNs) are formed of various nodes that gather parameters in a monitored environment. These nodes interact with each other or can be arranged into clusters controlled by a cluster head that has the task of rerouting the acquired data to a base station. Both the Quality of Service (QoS) and low data quality are common issues in WSNs, mainly prompted by the data fusion mechanism, where a certain amount of low-quality data may affect the overall fusion result negatively. In this paper, a fuzzy-based solution for data fusion in WSNs is presented to provide a better QoS and to reduce the energy consumption. The suggested approach can aggregate only true value rather than process the full data. This purpose is accomplished thanks to a Fuzzy Logic Controller (FLC) implemented within nodes. Besides, the data, which have been separated, are aggregated by a cluster head which also has the responsibility of determining the probability that an event has happened in the monitored environment. Finally, the base station estimates whether an event has occurred and, eventually, raises an appropriate alarm. The results of a real testbed scenario reveal that the proposed method achieves encouraging performance.

Using fuzzy logic for robust event detection in wireless sensor networks

2012 ◽  
Vol 10 (4) ◽  
pp. 709-722 ◽  
Author(s):  
Krasimira Kapitanova ◽  
Sang H. Son ◽  
Kyoung-Don Kang
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Event Detection ◽  
Wireless Sensor
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