Data fusion on a distributed heterogeneous sensor network

2006 ◽  
Author(s):  
Peter Lamborn ◽  
Pamela J. Williams
Keyword(s):  
Data Fusion ◽  
Sensor Network ◽  
Heterogeneous Sensor Network

scholarly journals EZ-SEP: Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1021
Author(s):  
Zhanserik Nurlan ◽  
Tamara Zhukabayeva ◽  
Mohamed Othman
Keyword(s):  
Sensor Network ◽  
Hierarchical Clustering ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Cluster Head ◽  
Average Power ◽  
Base Station ◽  
Average Power Consumption ◽  
Clustering Approach ◽  
Heterogeneous Sensor Network

Wireless sensor networks (WSN) are networks of thousands of nodes installed in a defined physical environment to sense and monitor its state condition. The viability of such a network is directly dependent and limited by the power of batteries supplying the nodes of these networks, which represents a disadvantage of such a network. To improve and extend the life of WSNs, scientists around the world regularly develop various routing protocols that minimize and optimize the energy consumption of sensor network nodes. This article, introduces a new heterogeneous-aware routing protocol well known as Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network or EZ-SEP, where the connection of nodes to a base station (BS) is done via a hybrid method, i.e., a certain amount of nodes communicate with the base station directly, while the remaining ones form a cluster to transfer data. Parameters of the field are unknown, and the field is partitioned into zones depending on the node energy. We reviewed the Z-SEP protocol concerning the election of the cluster head (CH) and its communication with BS and presented a novel extended mechanism for the selection of the CH based on remaining residual energy. In addition, EZ-SEP is weighted up using various estimation schemes such as base station repositioning, altering the field density, and variable nodes energy for comparison with the previous parent algorithm. EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. Simulation results show that our proposed extended version performs better than Z-SEP in the stability period due to an increase in the number of active nodes by 48%, in efficiency of network by the high packet delivery coefficient by 16% and optimizes the average power consumption compared to by 34.

scholarly journals An efficient intelligent data fusion algorithm for wireless sensor network

2021 ◽  
Vol 183 ◽  
pp. 418-424
Author(s):  
Haitao Wang ◽  
Lihua Song ◽  
Jue Liu ◽  
Tingting Xiang
Keyword(s):  
Wireless Sensor Network ◽  
Data Fusion ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Fusion Algorithm

System Design and Data Fusion in Body Sensor Networks

2012 ◽  
pp. 1-25 ◽  
Author(s):  
Kai Lin ◽  
Min Chen ◽  
Joel J. P. C. Rodrigues ◽  
Hongwei Ge
Keyword(s):  
Sensor Networks ◽  
Data Fusion ◽  
System Design ◽  
Sensor Network ◽  
Evaluation Method ◽  
Data Evaluation ◽  
Body Sensor Networks ◽  
Sensory Data ◽  
Redundant Data ◽  
Healthcare Monitoring

Body Sensor Networks (BSNs) are formed by the equipped or transplanted sensors in the human body, which can sense the physiology and environment parameters. As a novel e-health technology, BSNs promote the deployment of innovative healthcare monitoring applications. In the past few years, most of the related research works have focused on sensor design, signal processing, and communication protocol. This chapter addresses the problem of system design and data fusion technology over a bandwidth and energy constrained body sensor network. Compared with the traditional sensor network, miniaturization and low-power are more important to meet the requirements to facilitate wearing and long-running operation. As there are strong correlations between sensory data collected from different sensors, data fusion is employed to reduce the redundant data and the load in body sensor networks. To accomplish the complex task, more than one kind of node must be equipped or transplanted to monitor multi-targets, which makes the fusion process become sophisticated. In this chapter, a new BSNs system is designed to complete online diagnosis function. Based on the principle of data fusion in BSNs, we measure and investigate its performance in the efficiency of saving energy. Furthermore, the authors discuss the detection and rectification of errors in sensory data. Then a data evaluation method based on Bayesian estimation is proposed. Finally, the authors verify the performance of the designed system and the validity of the proposed data evaluation method. The chapter is concluded by identifying some open research issues on this topic.

Wireless Sensor Network based Data Fusion and Control Model for an Oil Production Platform

2010 ◽  
pp. 113-137
Author(s):  
Mitun Bhattacharyya ◽  
Ashok Kumar ◽  
Magdy Bayoumi
Keyword(s):  
Control System ◽  
Data Fusion ◽  
Sensor Network ◽  
Hierarchical Control ◽  
Oil Production ◽  
Fusion Model ◽  
Production Platform ◽  
Network Manager ◽  
Association Data ◽  
And Control

In this chapter the authors propose methodologies for improving the efficiency of a control system in an industrial environment, specifically an oil production platform. They propose a data fusion model that consists of four steps – preprocessing, classification and association, data association and correlation association, and composite decision. The first two steps are executed at the sensor network level and the last two steps are done at the network manager or controller level. Their second proposal is a distributed hierarchical control system and network management system. Here the central idea is that the network manager and controller coordinate in order to make delays in feedback loops as well as for increasing the lifetime of the sensor network. The authors finally conclude the control system proposal by giving a controlling model using sensor networks to control the flow of hydrocarbons in an oil production platform.

Sign in / Sign up

Export Citation Format

Share Document