Extending lifetime of wireless sensor networks using multi-sensor data fusion

Das, Soumitra; Barani, S.; Wagh, Sanjeev J.; Sonavane, S. S.

doi:10.1007/s12046-017-0669-x

Cited by 14 publications

(13 citation statements)

References 16 publications

(12 reference statements)

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“…8 The data fusion can be accomplished on the data collected by sensor nodes in two customs. 9 In a first way, physical models are employed. In a second way, the techniques of artificial intelligence and automatic classification are used.…”

Section: Of 14mentioning

confidence: 99%

“…KUMAR AND CHAURASIYA Layer 3: The nodes in this layers perform the normalization process of the firing strength from the previous layer. The output of this layer can be computed as 9 , i = 1, 2 … 9.…”

Section: Of 14mentioning

confidence: 99%

“…In each iteration, the velocity along each dimension is adjusted according to Equation (9), and a new position of the node is determined using that velocity as shown by Equation (10).…”

Section: Quantum-behaved Particle Swarm Optimizationmentioning

confidence: 99%

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A multisensor data fusion strategy for path selection in Internet‐of‐Things oriented wireless sensor network (WSN)

Kumar

Chaurasiya

2018

Concurrency and Computation

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To give the complete description of an environment or to take a robust decision, a number of observations are collected and combined from multiple sensor nodes. The process of combining and analyzing the observations is called multisensor data fusion. The fusion is used to produce more consistent, accurate, and useful information rather than provided by any individual sensor node. Data fusion finds wide application in many areas of such as object recognition, wireless sensor network, image processing, environment mapping, and localization. Nowadays, the Internet of Things (IoT) utilizes wireless sensor network (WSN) as a necessary platform for data sensing and communication. For efficiency, data fusion is performed on the sensed sample collected by the sensor nodes. However, fusion of the network parameters is also essential to select an appropriate sensor node for the forwarding of data. Therefore, in this paper, we propose a multisensor data fusion (MDF) strategy that performs fusion of the collected network parameters like bandwidth and centrality for the selection of an appropriate path. Extensive simulations were made, and related results showed that our proposed scheme has a better performance compared with other schemes in our simulated scenarios. KEYWORDS data fusion, Internet-of-Things, performance analysis, wireless sensor network INTRODUCTIONA wireless sensor network (WSN) is a type of network that contains large number of nodes having sensing capability such that they can easily detect any changes in the surrounding real-world environment. The nodes in WSN are used to carry sensed information from one to another desired location for further processing. 1,2 Technological advances are being developed daily, and a WSN plays a rapid contribution for providing smart communication with the use of smart devices. These smart devices perform communication at the different locations by providing a level of transparency among users and maintained an interconnected smart network. A number of sensor nodes are constituted by the smart network, which is used to send sensed information and termed as the Internet of Things (IoT). 3 In this paper, we called this network as an IoT oriented WSN. In this network, the users communicate with each other by exchanging of sensed data, monitoring of events, and surrounding and reacting autonomously. 4 The difference between the WSN and IoT oriented WSN is only the few sensors are deployed in WSN rather than along with smart devices for applications.However, the IoT oriented WSN consists of devices having sensors with full network connectivity. The network of IoT oriented WSN is concerned with the loss of packets and performance of the links for achieving high throughput in less delay.The services of IoT oriented WSN are provided by using a standard interface such that users can create a query, retrieve information, and change their states accordingly. An Internet link is used to provide the standard interface between users and IoT devices. The hardware components of a sensor no...

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Section: Of 14mentioning

confidence: 99%

Section: Of 14mentioning

confidence: 99%

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A multisensor data fusion strategy for path selection in Internet‐of‐Things oriented wireless sensor network (WSN)

Kumar

Chaurasiya

2018

Concurrency and Computation

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“…On the other hand, the non-probabilistic method [26][27][28][29] uses multiple factors for the selection of cluster heads. Although, the non-probabilistic methods give an improved performance as compared to traditional probabilistic methods, however, because of dynamic nature of sensor nodes [30][31][32][33][34], improving energy conservation and routing robustness are still open challenges for IoT based on WSN.…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient and Secure Routing Protocol for Intrusion Avoidance in IoT-Based WSN

et al. 2019

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Due to the advancement of information and communication technologies, the use of Internet of Things (IoT) devices has increased exponentially. In the development of IoT, wireless sensor networks (WSNs) perform a vital part and comprises of low-cost smart devices for information gathering. However, such smart devices have constraints in terms of computation, processing, memory and energy resources. Along with such constraints, one of the fundamental challenges for WSN is to achieve reliability with the security of transmitted data in a vulnerable environment against malicious nodes. This paper aims to develop an energy-efficient and secure routing protocol (ESR) for intrusion avoidance in IoT based on WSN to increase the network period and data trustworthiness. Firstly, the proposed protocol creates different energy-efficient clusters based on the intrinsic qualities of nodes. Secondly, based on the (k,n) threshold-based Shamir secret sharing scheme, the reliability and security of the sensory information among the base station (BS) and cluster head are achieved. The proposed security scheme presents a light-weight solution to cope with intrusions generated by malicious nodes. The experimental results using the network simulator (NS-2) demonstrate that the proposed routing protocol achieved improvement in terms of network lifetime as 37%, average end-to-end delay as 24%, packet delivery ratio as 30%, average communication cost as 29%, network overhead as 28% and the frequency of route re-discoveries as 38% when compared with the existing work under dynamic network topologies.

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“…The current technological revolution and the appearance of low-cost and highperformance electronic components have allowed the design and manufacture of embedded devices for the fulfillment of specific tasks. In the health sciences case, there is an increasing number of technological platforms that enable the clinically objective diagnosis of patients [1,2] and host another kind of applications [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Wireless Data Transmission over Wi-Fi in a Biomechanical Information Processing System

2019

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This paper presents a characterization of the wireless transmission of biomechanical signals in an embedded system, where a TCP protocol is used in an IEEE 802.11 communications network (Wi-Fi). The embedded system under study, called Imocap, allows the collection, analysis and transmission of biomechanical signals in real-time for various applications, among which the analysis of the movement of the lower and upper extremities and the operation of various control systems stand out. To accomplish this, Imocap is equipped with a Wi-Fi transceiver module (ESP8266) and various input and output peripherals. The wireless communication performance of Imocap, exposed in this paper, was analyzed through different tests in miscellaneous conditions like indoors, outdoors and in the presence of interference, noise and other wireless networks. The different test protocols conducted result in the Imocap system: 1) has a maximum effective range of 45.6 m when in Access Point mode; 2) has a maximum effective range of 44.3 m when in Station mode. In indoors and under the same conditions, the Imocap system: 3) has a maximum effective range of 81.25 m2, either Access Point or Station mode. The results showed that the transmission of biomechanical information through Wi-Fi using the TCP protocol is efficient and robust, both indoors and outdoors, even in environments of radio frequency interference. The use of this protocol is emphasized since its use allows the transmission of packages to be carried out in a controlled manner, allowing the error handling and recovery. In this way, it is possible to carry out efficient and robust wireless communication through embedded and portable devices, focusing mainly on areas such as medicine, telemedicine and telerehabilitation.

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Extending lifetime of wireless sensor networks using multi-sensor data fusion

Cited by 14 publications

References 16 publications

A multisensor data fusion strategy for path selection in Internet‐of‐Things oriented wireless sensor network (WSN)

A multisensor data fusion strategy for path selection in Internet‐of‐Things oriented wireless sensor network (WSN)

An Energy-Efficient and Secure Routing Protocol for Intrusion Avoidance in IoT-Based WSN

Characterization of Wireless Data Transmission over Wi-Fi in a Biomechanical Information Processing System

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