Application based Study on Wireless Sensor Network

Maraiya, Kiran; Kant, Kamal; Gupta, Nitin

doi:10.5120/2534-3459

Cited by 63 publications

(43 citation statements)

References 8 publications

(3 reference statements)

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“…2 WSN has a wide range of application areas in health, military, environmental monitoring, tracking, controlling security, household, and other commercial areas. [3][4][5][6] The majority of the applications require that the measured value is tagged with time and location information. Hence, the measured data are meaningless without knowing the location from where the data are obtained.…”

Section: Introductionmentioning

confidence: 99%

On precise path planning algorithm in wireless sensor network

Javed

Khan

et al. 2018

International Journal of Distributed Sensor Networks

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Wireless sensor network is a collection of small devices called sensors nodes, which are deployed in the sensing field to monitor physical and environmental information. Location information of sensor node is a critical issue for many applications in wireless sensor network. The main problem is to design a path for a mobile landmark to maximize the location accuracy as well as to reduce energy consumption. Different path planning schemes have been proposed for localization.Here, this study focused only on static path planning scheme. In this article, the performance of five static path planning schemes is evaluated, namely, random way point, Scan, D-Scan, Hilbert, and Circles based on three parameters such as location error ratio, energy consumption, and number of references. Network simulator-2 is used as a simulation tool. Simulation scenarios with three node densities are used in this research study such as sparse node density, medium node density, and dense node density. The analysis of simulation results concludes that random way point has higher performance efficiency compared to rest of the static path planning algorithms concerning location error ratio (accuracy), energy consumption, and number of references in medium and dense node density scenarios. Hilbert performance was found good only in sparse node density scenario.

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Section: Introductionmentioning

confidence: 99%

On precise path planning algorithm in wireless sensor network

Javed

Khan

et al. 2018

International Journal of Distributed Sensor Networks

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“…The XLP protocol with respect to the Code Division Multiple Access Ad-hoc networks is concerned, the energy optimization can be done more efficiently if the route request messages could be stored during the process of route establishment when packets have been transmitted more in number due to which the number of hops also increased [35]. Corresponding to this issue, a modified XLP protocol is been combined with AODV protocol to provide more ease in extracting the shortest path towards the destinations [32][33].…”

Section: Related Workmentioning

confidence: 99%

An Optimum Energy Consumption Hybrid Algorithm for XLN Strategic Design in WSN’S

Mohiddin¹,

Dutt²

2019

IJCNC

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In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15.4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.

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“…Deployed applications are tele-monitoring physiological data, tracking patient locations and patient drug management [12]. WSN will allow the patient to be under constant supervision without hospital admission.…”

Section: Health Applicationsmentioning

confidence: 99%

Computational Intelligence for Wireless Sensor Networks: Applications and Clustering Algorithms

Solaiman¹,

Sheta²

2013

IJCA

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WSN has been directed from military applications to various civil applications. However, many applications are not ready for real world deployment. Most challenging issues are still unresolved. The main challenge facing the operation of WSN is saving energy to prolong the network lifetime. Clustering is an efficient technique used for managing energy consumption. However, clustering is an NP hard optimization problem that can't be solved effectively by traditional methods. Computational Intelligence (CI) paradigms are suitable to adapt for WSN dynamic nature. This paper explores the advantages of CI techniques and how they may be used to solve varies problems associated to WSN. Finally, a short conclusion and future recommendation is being provided.

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Application based Study on Wireless Sensor Network

Cited by 63 publications

References 8 publications

On precise path planning algorithm in wireless sensor network

On precise path planning algorithm in wireless sensor network

An Optimum Energy Consumption Hybrid Algorithm for XLN Strategic Design in WSN’S

Computational Intelligence for Wireless Sensor Networks: Applications and Clustering Algorithms

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