<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The integration of Wireless Sensor Networks (WSN) and cloud computing brings several advantages. However, one of the main problems with the existing cloud solutions is the latency involved in accessing, storing, and processing data. This limits the use of cloud computing for various types of applications (for instance, patient health monitoring) that require real-time access and processing of data. To address the latency problem, we proposed a fog-assisted Link Aware and Energy E cient Protocol for Wireless Body Area Networks (Fog-LAEEBA). The proposed solution is based on the already developed state-of-the-art protocol called LAEEBA. We implement, test, evaluate and compare the results of Fog-LAEEBA in terms of stability period, end-to-end delay, throughput, residual energy, and path-loss. For the stability period all nodes in the LAEEBA protocol die after 7445 rounds, while in our case the last node dies after 9000 rounds. For the same number of rounds, the end-to-end delay is 2 seconds for LAEEBA and 1.25 seconds for Fog-LAEEBA. In terms of throughput, our proposed solution increases the number of packets received by the sink node from 1.5 packets to 1.8 packets. The residual energy of the nodes in Fog-LAEEBA is also less than the LAEEBA protocol. Finally, our proposed solution improves the path loss by 24 percent.</p>
</abstract>

The integration of Wireless Sensor Networks (WSN) and cloud computing brings several advantages. However, one of the main problems with the existing cloud solutions is the latency involved in accessing, storing, and processing data. This limits the use of cloud computing for various types of applications (for instance, patient health monitoring) that require real-time access and processing of data. To address the latency problem, we proposed a fog-assisted Link Aware and Energy E cient Protocol for Wireless Body Area Networks (Fog-LAEEBA). The proposed solution is based on the already developed state-of-the-art protocol called LAEEBA. We implement, test, evaluate and compare the results of Fog-LAEEBA in terms of stability period, end-to-end delay, throughput, residual energy, and path-loss. For the stability period all nodes in the LAEEBA protocol die after 7445 rounds, while in our case the last node dies after 9000 rounds. For the same number of rounds, the end-to-end delay is 2 seconds for LAEEBA and 1.25 seconds for Fog-LAEEBA. In terms of throughput, our proposed solution increases the number of packets received by the sink node from 1.5 packets to 1.8 packets. The residual energy of the nodes in Fog-LAEEBA is also less than the LAEEBA protocol. Finally, our proposed solution improves the path loss by 24 percent.

Fog-LAEEBA: Fog-assisted Link aware and energy efficient protocol for wireless body area network

CECOS University of IT and Emerging Sciences

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution 4.0 International License.

The integration of Wireless Sensor Networks (WSN) and cloud computing brings several advantages. However, one of the main problems with the existing cloud...

Fog-LAEEBA: Fog-assisted Link aware and energy efficient protocol for wireless body area network

Published Online: Jul 08, 2021

Page range: 180 - 194

Received: Apr 24, 2021

Accepted: Jun 01, 2021

DOI: https://doi.org/10.2478/ausi-2021-0008

Keywords
wireless sensor network, wireless body area network, fog computing, fog-laeeba, energy efficiency

© 2021 Kifayat Ullah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fog-LAEEBA: Fog-assisted Link aware and energy efficient protocol for wireless body area network

Published Online: Jul 08, 2021

Page range: 180 - 194

Received: Apr 24, 2021

Accepted: Jun 01, 2021

DOI: https://doi.org/10.2478/ausi-2021-0008

Keywordswireless sensor network, wireless body area network, fog computing, fog-laeeba, energy efficiency

© 2021 Kifayat Ullah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
wireless sensor network, wireless body area network, fog computing, fog-laeeba, energy efficiency