scholarly journals A Data Fusion Method in Wireless Sensor Network Based on Belief Structure

2020 ◽  
Author(s):  
Chenfeng Long ◽  
Xinxing Liu ◽  
Yakun Yang ◽  
Tao Zhang ◽  
Siqiao Tan ◽  
...  
Keyword(s):  
Data Fusion ◽  
Attribute Reduction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fusion Method ◽  
Processing Efficiency ◽  
Belief Structure ◽  
High Data ◽  
Positive Region ◽  
Different Levels

Abstract Considering the issue with respect to the high data redundancy and high cost of information collection in wireless sensor nodes, this paper proposes a data fusion method based on belief structure to reduce attribution in multi-granulation rough set. By introducing belief structure, attribute reduction is carried out for multi-granulation rough sets. From the view of granular computing, this paper studies the evidential characteristics of incomplete multi-granulation ordered information systems. On this basis, the positive region reduction, belief reduction and plausibility reduction are put forward in incomplete multi-granulation order information system, and analyze the consistency in the same level and transitivity in different levels. The positive region reduction and belief reduction are equivalent, and the positive region reduction and belief reduction is unnecessary and sufficient conditional plausibility reduction in the same level; if the cover structure order of different levels are the same, the corresponding equivalent positive region reduction. The algorithm proposed in this paper not only performs three reductions, but also reduces the time complexity largely. The above study fuses the node data which reduces the amount of data that needs to be transmitted and effectively improves the information processing efficiency.

scholarly journals A data fusion method in wireless sensor network based on belief structure

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chengfeng Long ◽  
Xingxin Liu ◽  
Yakun Yang ◽  
Tao Zhang ◽  
Siqiao Tan ◽  
...  
Keyword(s):  
Data Fusion ◽  
Attribute Reduction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fusion Method ◽  
Processing Efficiency ◽  
Belief Structure ◽  
High Data ◽  
Positive Region ◽  
Different Levels

AbstractConsidering the issue with respect to the high data redundancy and high cost of information collection in wireless sensor nodes, this paper proposes a data fusion method based on belief structure to reduce attribution in multi-granulation rough set. By introducing belief structure, attribute reduction is carried out for multi-granulation rough sets. From the view of granular computing, this paper studies the evidential characteristics of incomplete multi-granulation ordered information systems. On this basis, the positive region reduction, belief reduction and plausibility reduction are put forward in incomplete multi-granulation ordered information system and analyze the consistency in the same level and transitivity in different levels. The positive region reduction and belief reduction are equivalent, and the positive region reduction and belief reduction are unnecessary and sufficient conditional plausibility reduction in the same level, if the cover structure order of different levels are the same the corresponding equivalent positive region reduction. The algorithm proposed in this paper not only performs three reductions, but also reduces the time complexity largely. The above study fuses the node data which reduces the amount of data that needs to be transmitted and effectively improves the information processing efficiency.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

Study of Data Fusion Mechanism Based on the WSN

2013 ◽  
Vol 321-324 ◽  
pp. 600-603
Author(s):  
Wei Liu ◽  
Qin Sheng Du ◽  
Le Le Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Wireless Sensor ◽  
Network Technology ◽  
Fusion Method ◽  
Simulation Test ◽  
Embedded Computing ◽  
New Type

Wireless sensor networks integrated four technologies including sensor, embedded computing, network technology and wireless communication. It is a new type of non-infrastructure wireless network. In this paper, a data fusion method has been brought forward based on wireless sensor networks, and through an algorithm simulation test, It is proved that the algorithm is effective to reduce the energy consumption of the network, and extend the lifetime of the network.

scholarly journals Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881130 ◽  
Author(s):  
Jaanus Kaugerand ◽  
Johannes Ehala ◽  
Leo Mõtus ◽  
Jürgo-Sören Preden
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Data Streams ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Temporal Consistency ◽  
Variable Delays

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

A Review of Multi-Channel Medium Access Control Protocols for Wireless Sensor Networks

2021 ◽  
Vol 6 (6) ◽  
pp. 39-53
Author(s):  
Hanan Alahmadi ◽  
Fatma Boabdullah
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mac Protocols ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Medium Access Control Protocols ◽  
Medium Access ◽  
Momentum Spread ◽  
High Data ◽  
Multichannel Mac

Wireless Sensor Networks (WSNs) are witnessing a momentum spread especially with the growth of the Internet of Things (IoT) paradigm. Indeed, WSNs are considered as the main enabling infrastructure for IoT networks. Nowadays, the emerging WSNs applications require not only long network lifespan but also considerably high data rate. Consequently, conceiving Multichannel MAC protocols that save the scarceenergy budget of sensor nodes while providing high network throughput is crucial for the emerging WSNs applications. In this paper, a thorough review of recent multichannel MAC protocols is provided along with a classification framework to deeply understand the design aspects for each protocol.

Wireless Sensor Network

2012 ◽  
pp. 339-347
Author(s):  
Noor Zaman ◽  
Azween Abdullah ◽  
Khalid Ragab
Keyword(s):  
Wireless Sensor Networks ◽  
Resource Constraints ◽  
Data Transfer ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Future Directions ◽  
Maximum Benefit ◽  
Routing Techniques ◽  
Different Levels

Wireless Sensor Networks (WSNs) are becoming common in use, with a vast diversity of applications. Due to its resource constraints, it is hard to maintain Quality of Service (QoS) with WSNs. Though they contain a vast variety of applications, at the same time they are also required to provide different levels of QoS, for various types of applications. A number of different issues and challenges still persist ahead to maintain the QoS of WSN, especially in critical applications where the accuracy of timely, guaranteed data transfer is required, such as chemical, defense, and healthcare. Hence, QoS is required to ensure the best use of sensor nodes at any time. Researchers are trying to focus on QoS issues and challenges to get maximum benefit from their applications. With this chapter, the authors focus on operational and architectural challenges of handling QoS, requirements of QoS in WSNs, and they discuss a selected survey of QoS aware routing techniques by comparing them in WSNs. Finally, the authors highlight a few open issues and future directions of research for providing QoS in WSNs.

scholarly journals Optimized Clustering Algorithms for Large Wireless Sensor Networks: A Review

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 322 ◽  
Author(s):  
Damien Wohwe Sambo ◽  
Blaise Yenke ◽  
Anna Förster ◽  
Paul Dayang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Smart Cities ◽  
Clustering Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Environmental Behaviors ◽  
High Data ◽  
High Scalability

During the past few years, Wireless Sensor Networks (WSNs) have become widely used due to their large amount of applications. The use of WSNs is an imperative necessity for future revolutionary areas like ecological fields or smart cities in which more than hundreds or thousands of sensor nodes are deployed. In those large scale WSNs, hierarchical approaches improve the performance of the network and increase its lifetime. Hierarchy inside a WSN consists in cutting the whole network into sub-networks called clusters which are led by Cluster Heads. In spite of the advantages of the clustering on large WSNs, it remains a non-deterministic polynomial hard problem which is not solved efficiently by traditional clustering. The recent researches conducted on Machine Learning, Computational Intelligence, and WSNs bring out the optimized clustering algorithms for WSNs. These kinds of clustering are based on environmental behaviors and outperform the traditional clustering algorithms. However, due to the diversity of WSN applications, the choice of an appropriate paradigm for a clustering solution remains a problem. In this paper, we conduct a wide review of proposed optimized clustering solutions nowadays. In order to evaluate them, we consider 10 parameters. Based on these parameters, we propose a comparison of these optimized clustering approaches. From the analysis, we observe that centralized clustering solutions based on the Swarm Intelligence paradigm are more adapted for applications with low energy consumption, high data delivery rate, or high scalability than algorithms based on the other presented paradigms. Moreover, when an application does not need a large amount of nodes within a field, the Fuzzy Logic based solution are suitable.

Sign in / Sign up

Export Citation Format

Share Document