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Decoding probability analysis of network-coded data collection and delivery by relay drones

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Decoding probability analysis of network-coded data collection and delivery by relay drones. / Chatzigeorgiou, Ioannis; Manole, Elena.
2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2020.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Chatzigeorgiou, I & Manole, E 2020, Decoding probability analysis of network-coded data collection and delivery by relay drones. in 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 31st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, London, United Kingdom, 31/08/20. https://doi.org/10.1109/PIMRC48278.2020.9217325

APA

Chatzigeorgiou, I., & Manole, E. (2020). Decoding probability analysis of network-coded data collection and delivery by relay drones. In 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) IEEE. https://doi.org/10.1109/PIMRC48278.2020.9217325

Vancouver

Chatzigeorgiou I, Manole E. Decoding probability analysis of network-coded data collection and delivery by relay drones. In 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE. 2020 doi: 10.1109/PIMRC48278.2020.9217325

Author

Chatzigeorgiou, Ioannis ; Manole, Elena. / Decoding probability analysis of network-coded data collection and delivery by relay drones. 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2020.

Bibtex

@inproceedings{41282b0b6964464495afee61a771519d,
title = "Decoding probability analysis of network-coded data collection and delivery by relay drones",
abstract = "Relay drones in delay-tolerant applications are dispatched to remote locations in order to gather data transmitted by a source node. Collected data are stored on the drones and delivered to one or multiple bases. This paper considers two schemes for broadcasting data to drones when feedback channels are not available: a data carousel and systematic random linear network coding (RLNC). We propose a theoretical framework for the calculation of the probability that a base will fully or partially recover the transmitted data and the probability that all involved bases will successfully obtain the data, when the bases are either isolated or interconnected. Theoretical results are validated through simulations. Design considerations are also discussed, including the relationship among the field size used by RLNC, the number of relay drones and the requirement for full data recovery or the retrieval of at least part of the data.",
author = "Ioannis Chatzigeorgiou and Elena Manole",
year = "2020",
month = oct,
day = "8",
doi = "10.1109/PIMRC48278.2020.9217325",
language = "English",
isbn = "9781728144917",
booktitle = "2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)",
publisher = "IEEE",
note = "31st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC ; Conference date: 31-08-2020 Through 03-09-2020",
url = "https://pimrc2020.ieee-pimrc.org",

}

RIS

TY - GEN

T1 - Decoding probability analysis of network-coded data collection and delivery by relay drones

AU - Chatzigeorgiou, Ioannis

AU - Manole, Elena

PY - 2020/10/8

Y1 - 2020/10/8

N2 - Relay drones in delay-tolerant applications are dispatched to remote locations in order to gather data transmitted by a source node. Collected data are stored on the drones and delivered to one or multiple bases. This paper considers two schemes for broadcasting data to drones when feedback channels are not available: a data carousel and systematic random linear network coding (RLNC). We propose a theoretical framework for the calculation of the probability that a base will fully or partially recover the transmitted data and the probability that all involved bases will successfully obtain the data, when the bases are either isolated or interconnected. Theoretical results are validated through simulations. Design considerations are also discussed, including the relationship among the field size used by RLNC, the number of relay drones and the requirement for full data recovery or the retrieval of at least part of the data.

AB - Relay drones in delay-tolerant applications are dispatched to remote locations in order to gather data transmitted by a source node. Collected data are stored on the drones and delivered to one or multiple bases. This paper considers two schemes for broadcasting data to drones when feedback channels are not available: a data carousel and systematic random linear network coding (RLNC). We propose a theoretical framework for the calculation of the probability that a base will fully or partially recover the transmitted data and the probability that all involved bases will successfully obtain the data, when the bases are either isolated or interconnected. Theoretical results are validated through simulations. Design considerations are also discussed, including the relationship among the field size used by RLNC, the number of relay drones and the requirement for full data recovery or the retrieval of at least part of the data.

U2 - 10.1109/PIMRC48278.2020.9217325

DO - 10.1109/PIMRC48278.2020.9217325

M3 - Conference contribution/Paper

SN - 9781728144917

BT - 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

PB - IEEE

T2 - 31st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

Y2 - 31 August 2020 through 3 September 2020

ER -