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Web Based Cross Layer Optimization Technique for Energy Efficient WSN.

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Title: Web Based Cross Layer Optimization Technique for Energy Efficient WSN.
Authors: Chandravathi, C.1 (AUTHOR) saijay2007.c@gmail.com, Mahadevan, K.2 (AUTHOR)
Source: Wireless Personal Communications. Apr2021, Vol. 117 Issue 4, p2781-2792. 12p.
Subjects: Cross layer optimization, End-to-end delay, Mathematical optimization, Wireless sensor networks, Military surveillance, Psychological feedback
Abstract: In recent days, wireless sensor networks (WSN) plays a major role in the real time applications like military battlefield surveillance, industrial process monitoring, machine health monitoring and so on. In WSN, selecting the cluster head (CH) is the challenging task. CH selection is done by considering parameters of single layer only. In cross layer protocol more than one layers are considered for inter related parameters such as integration of MAC/physical layer and integration routing/MAC/physical layers. The main drawback of layer-based approach is not considering the effect on improvement of particular layer parameter to other layer parameters. In this paper, new cross layer technique for energy efficient module is designed to address the energy efficiency issues, which is common to all layers and used to optimize the energy from one layer parameter by others. Nowadays everything is possible with the help of Internet, so sharing the information between WSN and TCP through the energy efficient cross layer can be done. It is done with transport layer to enhance the application filed to be reliably connected to the web. In this paper, dynamically adapted sleep scheduling mechanism is used with residual energy of each node. Virtual end-to-end packet rate selection and congestion control feedback mechanism are considered for end to end delay. This reduces the packet loss with the support of data-rate adaptation technique. [ABSTRACT FROM AUTHOR]
Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Web Based Cross Layer Optimization Technique for Energy Efficient WSN.
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  Data: In recent days, wireless sensor networks (WSN) plays a major role in the real time applications like military battlefield surveillance, industrial process monitoring, machine health monitoring and so on. In WSN, selecting the cluster head (CH) is the challenging task. CH selection is done by considering parameters of single layer only. In cross layer protocol more than one layers are considered for inter related parameters such as integration of MAC/physical layer and integration routing/MAC/physical layers. The main drawback of layer-based approach is not considering the effect on improvement of particular layer parameter to other layer parameters. In this paper, new cross layer technique for energy efficient module is designed to address the energy efficiency issues, which is common to all layers and used to optimize the energy from one layer parameter by others. Nowadays everything is possible with the help of Internet, so sharing the information between WSN and TCP through the energy efficient cross layer can be done. It is done with transport layer to enhance the application filed to be reliably connected to the web. In this paper, dynamically adapted sleep scheduling mechanism is used with residual energy of each node. Virtual end-to-end packet rate selection and congestion control feedback mechanism are considered for end to end delay. This reduces the packet loss with the support of data-rate adaptation technique. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr2021
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