scholarly journals A Novel Fault Diagnosis Strategy for Heterogeneous Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Li Cao ◽  
Yinggao Yue ◽  
Yong Zhang

Fault diagnosis is a guarantee for the reliable operation of heterogeneous wireless sensor networks, and accurate fault prediction can effectively improve the reliability of wireless sensor networks. First, it summarizes the node fault classification and common fault diagnosis methods of heterogeneous wireless sensor networks. After that, taking advantage of the short learning time, fewer parameter settings, and good generalization ability of kernel extreme learning machine (KELM), the collected sample data of the sensor node hardware failure is introduced into the trained kernel extreme learning machine and realizes the fault identification of various hardware modules of the sensor node. Regarding the regularization coefficient C and the kernel parameter s in KELM as the model parameters, it will affect the accuracy of the fault diagnosis model of the kernel extreme learning machine. A method for the sensor nodes fault diagnosis of heterogeneous wireless sensor networks based on kernel extreme learning machine optimized by the improved artificial bee colony algorithm (IABC-KELM) is proposed. The proposed algorithm has stronger ability to solve regression fault diagnosis problems, better generalization performance, and faster calculation speed. The experimental results show that the proposed algorithm improves the accuracy of the hardware fault diagnosis of the sensor nodes and can be better applied to the node hardware fault diagnosis of heterogeneous wireless sensor networks.

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982631 ◽  
Author(s):  
Zhangquan Wang ◽  
Yourong Chen ◽  
Banteng Liu ◽  
Haibo Yang ◽  
Ziyi Su ◽  
...  

To improve the regional coverage rate and network lifetime of heterogeneous wireless sensor networks, a sensor node scheduling algorithm for heterogeneous wireless sensor networks is proposed. In sensor node scheduling algorithm, heterogeneous perception radius of sensor node is considered. Incomplete coverage constraint and arc coverage interval are analyzed. Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. Multi-objective scheduling model is established using weight factors and integrated function. Furthermore, the heuristic method is proposed to solve the multi-objective optimization model, and scheduling scheme of heterogeneous sensor nodes is obtained. When the network is in operation for a period of time, some sensor nodes are invalid and relevant regions are uncovered. The repair method is proposed to wake up sleep sensor nodes and repair the coverage blind area. The simulation results show that if keeping the same regional coverage rate, sensor node scheduling algorithm improves network lifetime, increases number of living sensor nodes, and keeps average node energy consumption at a low level. Under certain conditions, sensor node scheduling algorithm outperforms DGREEDY, two-tiered scheduling, and minimum connected cover.


2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.


Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3663 ◽  
Author(s):  
Seyed Aghili ◽  
Hamid Mala ◽  
Pedro Peris-Lopez

Heterogeneous wireless sensor networks (HWSNs) are employed in many real-time applications, such as Internet of sensors (IoS), Internet of vehicles (IoV), healthcare monitoring, and so on. As wireless sensor nodes have constrained computing, storage and communication capabilities, designing energy-efficient authentication protocols is a very important issue in wireless sensor network security. Recently, Amin et al. presented an untraceable and anonymous three-factor authentication (3FA) scheme for HWSNs and argued that their protocol is efficient and can withstand the common security threats in this sort of networks. In this article, we show how their protocol is not immune to user impersonation, de-synchronization and traceability attacks. In addition, an adversary can disclose session key under the typical assumption that sensors are not tamper-resistant. To overcome these drawbacks, we improve the Amin et al.’s protocol. First, we informally show that our improved scheme is secure against the most common attacks in HWSNs in which the attacks against Amin et al.’s protocol are part of them. Moreover, we verify formally our proposed protocol using the BAN logic. Compared with the Amin et al.’s scheme, the proposed protocol is both more efficient and more secure to be employed which renders the proposal suitable for HWSN networks.


Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].


2021 ◽  
Author(s):  
Ramdas Vankdothu ◽  
Hameed Mohd Abdul ◽  
Fatima Husnah ◽  
Subbarao Akkala

Abstract Heterogeneous wireless sensor networks (HWSNs) satisfy researchers' requirements for developing real-world solutions that handle unattended challenges. However, the primary constraint of researchers is the privacy of the sensor nodes. It safeguards the sensor nodes and extensions in the HWSNs. Therefore, it is necessary to develop secure operational systems. Multicast scaling with security and time efficiency is described in heterogeneous wireless sensor networks to maximize network performance while also successfully protecting network privacy. This study evaluates the initial security and time efficiency measures, such as execution time, transmission delay, processing delay, congestion level, and trust measure. Subsequently, the optimal location of the heterogeneous nodes is determined using sigmoid-based fuzzy c-means clustering. Finally, successful cluster routing was achieved via support-value-based particle swarm optimization. The experimental results indicate that the proposed strategy surpasses existing strategies in terms of network delivery ratio, end-to-end delay, throughput, packet delivery, and node remaining energy level.


Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.


Author(s):  
C. R. Bharathi ◽  
Alapati Naresh ◽  
Arepalli Peda Gopi ◽  
Lakshman Narayana Vejendla

In wireless sensor networks (WSN), the majority of the inquiries are issued at the base station. WSN applications frequently require collaboration among countless sensor nodes in a network. One precedent is to persistently screen a region and report occasions. A sensor node in a WSN is initially allocated with an energy level, and based on the tasks of that sensor node, energy will be reduced. In this chapter, two proposed methods for secure network cluster formation and authentication are discussed. When a network is established then all the nodes in it must register with cluster head and then authentication is performed. The selection of cluster head is done using a novel selection algorithm and for authenticating the nodes. Also, a novel algorithm for authentication is used in this chapter. The validation and authorization of nodes are carried over by managing the keys in WSN. The results have been analyzed using NS2 simulator with an aid of list of relevant parameters.


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