An overview of wireless sensor network and its applications

<span>The wireless sensor network (WSN) is a decentralized network that allows sensor nodes to freely join and quit the network, making it a unique network type that varies from centralized systems in which the fusion center decides on entry and exit. However, one of the key drawbacks of these networks is that the sensor nodes are small and located in remote areas. As a result, energy usage must be efficiently managed. In order to limit energy consumption, an efficient clustering protocol approach is necessary, which may be performed by dividing the networks into clusters and selecting cluster heads depending on the remaining energy and sensor distance. The energy hole problem has an impact on the performance of an energy-efficient technique. As a result, this work aims to extend the lifespan of WSNs, the goal of this research is to make the cluster to normal ratio (CTNR) Protocol better. Data forwarding nodes are added to the CTNR protocol hierarchy to enable hopping and avoid consuming nodes in order to solve the energy hole problem (sink). The proposed method is implemented in Matlab, and the results are compared to literature on energy usage and the amount of dead and living nodes. In terms of the performance indicators given, the results reveal that our proposed scheme beat others.</span>

Section: Introductionmentioning

confidence: 99%

Improved cluster to normal ratio protocol for increasing the lifetime of wireless sensor networks

Martey

Esenogho

2022

“…Also, they help human to have access and manage marine information in hostile environments. A group of autonomous underwater vehicles form a mobile underwater sensor network [4]. Unlike static underwater sensor network, autonomously operated underwater vehicles have long deployment time also they can sense large regions of the ocean because they can move in all directions [5].…”

Section: Introductionmentioning

confidence: 99%

Decentralised optimal deployment of mobile underwater sensors for covering layers of the ocean

Nazarzehi

Damani

2022

This paper presents the problem of sensing coverage of layers of the ocean in three dimensional underwater environments. We propose distributed control laws to drive mobile underwater sensors to optimally cover a given confined layer of the ocean. By applying this algorithm at first the mobile underwater sensors adjust their depth to the specified depth. Then, they make a triangular grid across a given area. Afterwards, they randomly move to spread across the given grid. These control laws only rely on local information also they are easily implemented and computationally effective as they use some easy consensus rules. The feature of exchanging information just among neighbouring mobile sensors keeps the information exchange minimum in the whole networks and makes this algorithm practicable option for undersea. The efficiency of the presented control laws is confirmed via mathematical proof and numerical simulations.

“…The popularity and increased usage of wireless sensor network (WSN) for various remote applications makes the wireless sensor network as one of the emerging technologies of recent days [1]. The wireless sensor network comprised of sensor nodes connected via wireless technologies, and each sensor node is comprised of microcontroller, sensing unit, radio transceiver and limited power supply unit.…”

Section: Introductionmentioning

confidence: 99%

“…The gateway node collects the successive sensor reading (Xi>1) and compares with the predetermined cluster head CH1 of primary cluster C1. If the successive readings (Xi>1) distance measure Dist(Xi , Xi+1)=|(Xi -Xi+1)| is lesser than the predefined application based custom threshold of ε then the successive reading under consideration would be put into the first cluster as represented in (1).…”

mentioning

confidence: 99%

Outlier tolerant adaptive sampling rate approach for wireless sensor node

Selvaraj

Bhat²

2022

Nowadays the wireless sensor network (WSN) has been used for variety of applications and still lot of research in progress around the corner for the betterment of the wireless sensor network technology. In this paper, one such issues related to energy consumption in sensor node due to fixed sampling interval of sensing unit and its impact on redundant data is discussed with a possible solution. The association of sampling interval and its impact on energy dissipation in sensor node enforces the need for study on energy efficient adaptive sampling interval approach. The lack of serious consideration of outlier in sensor data degrades the performance of the existing adaptive sampling interval approach. The result of the proposed approach of in-network clustering algorithm shows the better efficiency towards detecting the outlier in real time. The results also showcase the better efficiency of proposed approach in terms of rapid optimization of sampling interval compared to simple variance based approach.