Hybrid Bird Swarm Optimized Quasi Affine Algorithm Based Node Location in Wireless Sensor Networks

Malathy, E. M.; Mythili, A.; Dheeraj, Alagu; Kannan, A.

doi:10.1007/s11277-021-08934-x

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…WSN with IoT manages all network protocols, topology, deployment of nodes, location technology, and network security. This article used the Bird Swarm Optimized Quasi-Affine Evolutionary Algorithm (BSOQAEA) to tackle the node placement problem in sensor networks [29]. Health support systems confront considerable obstacles include a lack of proper medical information, avoidable mistakes, data security risks, incorrect diagnoses, and delayed communication.…”

Section: Related Workmentioning

confidence: 99%

Analysis of the Security of Internet of Multimedia Things in Wireless Environment

Haddad,

Mustafa,

Salih

et al. 2023

JCSANDM

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The Internet of Things (IoT) and real-time flexibility improve people’s lives, and IoT applications rely heavily on multimedia sensors and devices. An interconnected network of IoT multimedia devices has made the Internet of Medical Things (IoMT). It creates massive data distinct from what the Internet of Things (IoT) produced. Smart traffic monitoring and smart hospitals are only a few examples of real-time deployment applications. IoMT data and decision-making must be made quickly since it directly impacts human life. The security heterogeneity of optimization issues is a significant challenge for enabling multimedia applications on the IoT. The IoMT has difficulty achieving low-cost data collecting while maintaining data security. An Internet of Multimedia Things in a wireless environment (IoMT-WE) system decreases the bandwidth and privacy risk caused by the revocation list, ensures the integrity of batch verification information, and corresponds with Vehicular ad hoc network (VANET) security performance. The proposed method uses random subsampling and chaotic convolution to collect numerous images. The sampling method is safe since the measurement matrix is controlled by chaos. As part of the IoMT architecture, wireless multimedia sensor nodes can be more easily deployed over the long term for real-time multimedia. The Wireless Multimedia Sensor Network (WMSN) comprises nodes that can capture both multimedia and non-multimedia data. The ioMT-WE system has been tested and found to be secure and effective.

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Section: Related Workmentioning

confidence: 99%

Analysis of the Security of Internet of Multimedia Things in Wireless Environment

Haddad,

Mustafa,

Salih

et al. 2023

JCSANDM

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“…Bird swarm optimization was hybridized with quasi-affine evolutionary algorithm in [ 70 ] to localize the nodes with more accuracy in WSN. RSS was used to discover the location of sensor nodes, and the bird swarm optimization had more node connectivity and less localization error.…”

Section: Literature Reviewmentioning

confidence: 99%

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

2022

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Wireless sensor networks (WSNs) contain sensor nodes in enormous amount to accumulate the information about the nearby surroundings, and this information is insignificant until the exact position from where data have been collected is revealed. Localization of sensor nodes in WSNs plays a significant role in several applications such as detecting the enemy movement in military applications. The major aim of localization problem is to find the coordinates of all target nodes with the help of anchor nodes. In this paper, two variants of bat optimization algorithm (BOA) are proposed to localize the sensor nodes in a more efficient way and to overcome the drawbacks of original BOA, i.e. being trapped in local optimum solution. The exploration and exploitation features of original BOA are modified in the proposed BOA variants 1 and 2 using improved global and local search strategies. To validate the efficiency of the proposed BOA variants 1 and 2, several simulations have been performed for various numbers of target nodes and anchor nodes, and the results are compared with original BOA and other existing optimization algorithms applied to node localization problem. The proposed BOA variants 1 and 2 outperform the other algorithms in terms of mean localization error, number of localized nodes and computing time. Further, the proposed BOA variants 1 and 2 and original BOA are also compared in terms of various errors and localization efficiency for several values of target and anchor nodes. The simulations results signify that the proposed BOA variant 2 is superior to the proposed BOA variant 1 and existing BOA in terms of several errors. The node localization based on the proposed BOA variant 2 is more effective as it takes less time to perform computations and has less mean localization error than the proposed BOA variant 1, BOA and other existing optimization algorithms.

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Hybrid algorithm optimization for coverage problem in wireless sensor networks

Jia

Chu

et al. 2022

Telecommun Syst

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Hybrid Bird Swarm Optimized Quasi Affine Algorithm Based Node Location in Wireless Sensor Networks

Cited by 8 publications

References 26 publications

Analysis of the Security of Internet of Multimedia Things in Wireless Environment

Analysis of the Security of Internet of Multimedia Things in Wireless Environment

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

Hybrid algorithm optimization for coverage problem in wireless sensor networks

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