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JCR Impact Factor: 0.700
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2016 - 7

 HIGH-IMPACT PAPER 

MAC Protocol for Data Gathering in Wireless Sensor Networks with the Aid of Unmanned Aerial Vehicles

VLADUTA, A.-V. See more information about VLADUTA, A.-V. on SCOPUS See more information about VLADUTA, A.-V. on IEEExplore See more information about VLADUTA, A.-V. on Web of Science, PURA, M. L. See more information about  PURA, M. L. on SCOPUS See more information about  PURA, M. L. on SCOPUS See more information about PURA, M. L. on Web of Science, BICA, I. See more information about BICA, I. on SCOPUS See more information about BICA, I. on SCOPUS See more information about BICA, I. on Web of Science
 
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Download PDF pdficon (1,329 KB) | Citation | Downloads: 1,174 | Views: 4,449

Author keywords
data acquisition, wireless sensor networks, unmanned aerial vehicles, wireless application protocol, algorithm

References keywords
sensor(16), networks(14), communications(10), survey(5), network(5), protocol(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-05-31
Volume 16, Issue 2, Year 2016, On page(s): 51 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.02007
Web of Science Accession Number: 000376996100007
SCOPUS ID: 84974777710

Abstract
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Data gathering in wireless sensor networks by employing unmanned aerial vehicles has been a subject of real interest in the recent years. While drones are seen as an efficient method of data gathering in almost any environment, wireless sensor networks are the key elements for generating data because they have low dimensions, improved flexibility, decreased power consumption and costs. This paper addresses the communication at the Medium Access Control (MAC) layer between static deployed sensors and a moving drone whose unique role is to collect data from all sensors on its path. The most important part of the proposed protocol consists of prioritizing the sensors in such a manner that each of them has a fair chance to communicate with the drone. Simulations are performed in NS-2 and results demonstrate the capabilities of the proposed protocol.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 18
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Cited-By CrossRef

[1] Design of an Integrated Remote and Ground Sensing Monitor System for Assessing Farmland Quality, Zhang, Feiyang, Wang, Guangxing, Hu, Yueming, Chen, Liancheng, Zhu, A-xing, Sensors, ISSN 1424-8220, Issue 2, Volume 20, 2020.
Digital Object Identifier: 10.3390/s20020336
[CrossRef]

[2] An Outage-Probability-Aware MAC Protocol for UAV-Assisted Networks, Cheng, Pan, Yang, Xin, Wang, Dawei, Gong, Yanyun, Wang, Ling, IEEE Sensors Journal, ISSN 1530-437X, Issue 11, Volume 23, 2023.
Digital Object Identifier: 10.1109/JSEN.2023.3267513
[CrossRef]

[3] DCDS-MAC: A Dual-Channel Dual-Slot MAC Protocol for Delay Sensitive Wireless Sensor Network Applications, Azad, Abul K., Alam, Mohammad S. , Shawkat, Shamim A., Journal of Communications, ISSN 2374-4367, 2019.
Digital Object Identifier: 10.12720/jcm.14.11.1049-1058
[CrossRef]

[4] Ubiquity of Wi-Fi: Crowdsensing Properties for Urban Fingerprint Positioning, LECA, C. L., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.04016
[CrossRef] [Full text]

[5] Performance Analysis and Optimization for the MAC Protocol in UAV-Based IoT Network, Li, Bin, Guo, Xianzhen, Zhang, Ruonan, Du, Xiaojiang, Guizani, Mohsen, IEEE Transactions on Vehicular Technology, ISSN 0018-9545, Issue 8, Volume 69, 2020.
Digital Object Identifier: 10.1109/TVT.2020.2997782
[CrossRef]

[6] QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications, Thomas, Diya, Shankaran, Rajan, Sheng, Quan Z., Orgun, Mehmet A., Hitchens, Michael, Masud, Mehedi, Ni, Wei, Mukhopadhyay, Subhas Chandra, Piran, Md. Jalil, IEEE Access, ISSN 2169-3536, Issue , 2021.
Digital Object Identifier: 10.1109/ACCESS.2020.3046619
[CrossRef]

[7] Medium Access Control Protocols for Unmanned Aerial Vehicle-Aided Wireless Sensor Networks: A Survey, Poudel, Sabitri, Moh, Sangman, IEEE Access, ISSN 2169-3536, Issue , 2019.
Digital Object Identifier: 10.1109/ACCESS.2019.2917948
[CrossRef]

[8] A survey of UAV-based data collection: Challenges, solutions and future perspectives, Messaoudi, Kaddour, Oubbati, Omar Sami, Rachedi, Abderrezak, Lakas, Abderrahmane, Bendouma, Tahar, Chaib, Noureddine, Journal of Network and Computer Applications, ISSN 1084-8045, Issue , 2023.
Digital Object Identifier: 10.1016/j.jnca.2023.103670
[CrossRef]

[9] A Proposed Solution for Analyzing the Behavior of a WSN using a Secured Neural Network Approach, Vladuta, Valentin-Alexandru, Ghimes, Ana-Maria, Patriciu, Victor Valeriu, 2018 International Symposium on Electronics and Telecommunications (ISETC), ISBN 978-1-5386-5925-0, 2018.
Digital Object Identifier: 10.1109/ISETC.2018.8583859
[CrossRef]

[10] Neural network models in big data analytics and cyber security, Ghimes, Ana-Maria, Patriciu, Victor-Valeriu, 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), ISBN 978-1-5090-6457-1, 2017.
Digital Object Identifier: 10.1109/ECAI.2017.8166441
[CrossRef]

[11] Data Gathering Optimization in Wireless Sensor Networks Using Unmanned Aerial Vehicles, Vladuta, Valentin-Alexandru, Matei, Ioana, Bica, Ion, 2019 22nd International Conference on Control Systems and Computer Science (CSCS), ISBN 978-1-7281-2331-8, 2019.
Digital Object Identifier: 10.1109/CSCS.2019.00029
[CrossRef]

[12] Trajectory influence on data collection in Wireless Sensor Networks using an Unmanned Aerial Vehicle, Vladuta, Valentin-Alexandru, Ghimes, Ana-Maria, Grumazescu, Constantin, Patriciu, Victor-Valeriu, 2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), ISBN 978-1-5386-4901-5, 2018.
Digital Object Identifier: 10.1109/ECAI.2018.8679047
[CrossRef]

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