Green Fault Tolerant AIoT-Enabled Mobile Sink Data Collection Scheme in Sensor Networks
In the current era, the Internet of Things (IoT) is an emerging technology that finds its application in the smart agriculture, smart cities, healthcare, etc. The backbone of these IoT-based applications is Wireless Sensor Networks (WSNs). The sensors in the WSNs face various challenges such as hard...
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Published in | IEEE transactions on vehicular technology Vol. 73; no. 10; pp. 15385 - 15394 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.10.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | In the current era, the Internet of Things (IoT) is an emerging technology that finds its application in the smart agriculture, smart cities, healthcare, etc. The backbone of these IoT-based applications is Wireless Sensor Networks (WSNs). The sensors in the WSNs face various challenges such as hardware failure and limited battery power. This causes network partitioning problems. Also, limited battery power causes energy-hole issues. In this paper, an Artificial Intelligence (AI)-based rendezvous points selection and rotation mechanism is proposed that provides green and fault-tolerant data collection in sensor networks. Also, an intelligent mobile sink-based data collection scheduling scheme is proposed that resolves energy holes and network partitioning issues. The simulations and testbed results demonstrate the efficiency of the proposed scheme. |
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ISSN: | 0018-9545 1939-9359 |
DOI: | 10.1109/TVT.2024.3400880 |