Improving the energy efficiency in mobile ad-hoc network using learning-based routing

被引：10

作者：

Aroulanandam V.V. ^{[1
]}

Latchoumi T.P. ^{[2
]}

Balamurugan K. ^{[3
]}

Yookesh T.L. ^{[4
]}

机构：

[1] Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai

[2] Department of Computer Science and Engineering, VFSTR (Deemed to be University), 522213, AP

[3] Department of Mechanical Engineering, VFSTR (Deemed to be University), 522213, AP

[4] Division of Mathematics, Department of Science and Humanities, VFSTR (Deemed to be University), 522213, AP

来源：

Revue d'Intelligence Artificielle | 2020年 / 34卷 / 03期

关键词：

Learning-based routing; Neural networks; Node range adjustment; Sequential learning; Weighted clustering;

D O I：

10.18280/ria.340312

中图分类号：

学科分类号：

摘要：

Improving Mobile Ad-Hoc Network (MANET) performance is a tedious task because of the dynamic and uncertain characteristics of the nodes. MANET nodes connected to multiple applications that involve a high exchange of data. To add reliability to the application services, MANETs optimized through dedicated load balancing schemes. The Dynamic Range Clustering (DRC) algorithm associated with Learning-based Routing (LR) used in the present work to improve the energy efficiency and the nature of the network's data handling. DRC design focuses on selecting the head of the cluster and maintaining stability over the cluster. LR selects unique neighbors that assist in ensuring the efficient, non-congested communication of data exchange. An effort has made to combine the two incompatible methods to increase the performance of the network over differential network traffic. The proposed approach tested using simulations and measures output by comparative analysis. © 2020 Lavoisier. All rights reserved.

引用

页码：337 / 343

页数：6

共 25 条

[1]

Shyam D., Kot A., Athalye C., Abandoned object detection using a pixel-based finite state machine and single shot multibox detector, IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, (2018)

[2]

Latchoumi T.P., Jayakumar L., Latha P., Janakiraman S., OFS method for selecting active features using clustering techniques, Proceedings of the International Conference on Informatics and Analytics, pp. 1-4, (2016)

[3]

Li J., Si Y., Lang L., Liu L., Xu T., A spatial pyramid pooling-based deep convolutional neural network for the classification of electrocardiogram beats, Applied Sciences, 8, 9, (2018)

[4]

Nazila M., Raziyeh H., A survey on existing mechanisms in energy-aware routing in MANET, International Journal of Computer Applications Technology and Research, 4, 9, pp. 673-679, (2015)

[5]

Ezhilarasi T.P., Dilip G., Latchoumi T.P., Balamurugan K., UIP-A smart web application to manage network environments, Proceedings of the Third International Conference on Computational Intelligence and Informatics, pp. 97-108, (2020)

[6]

Sundaranarayan D., Venkatachalapathy K., An effectual load distribution approach based on transmission power and topology controlled clustered environment in mobile Adhoc network, International Journal of Computer Applications, 179, 25, pp. 34-38, (2018)

[7]

Khatoon N., Mobility aware energy efficient clustering for MANET: A bio-inspired approach with particle swarm optimization, Wireless Communications and Mobile Computing, 2017, pp. 1-12, (2017)

[8]

Linyang S., Jingbo S., Jinfeng D., A novel energy-efficient approach to DSR based routing protocol for Ad Hoc Network, IEEE International Conference on Electrical and Control Engineering, pp. 2618-2620, (2010)

[9]

Mandhare V.V., Thool R.C., Improving QoS of mobile ad-hoc network using cache update scheme in dynamic source routing protocol, Procedia Computer Science, 79, pp. 692-699, (2016)

[10]

Barati M., Atefi K., Khosravi F., Daftari Y.A., Performance Evaluation of energy efficiency for MANET using AODV routing protocol, IEEE 3rd International Conference on Computational Intelligence and Communication Technology, pp. 636-642, (2017)

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