Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles

Oussama Bekkouche; Tarik Taleb; Miloud Bagaa; Konstantinos Samdanis

doi:10.1109/WCNC.2019.8886000

Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles

Oussama Bekkouche, Tarik Taleb, Miloud Bagaa, Konstantinos Samdanis

Mobile Network Softwarization and Service Customization

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

10 Citations (Scopus)

135 Downloads (Pure)

Abstract

Unmanned Aerial Vehicles (UAVs) can offer a plethora of applications, provided that the appropriate ground control and complementary computing and storage services are available in close proximity. To accomplish this, edge cloud platforms, deployed at or close to the base stations, are essential. However, current UAV travel planning does not take into account the resource constraints of such edge cloud platforms. This paper introduces an aligned process for UAV flight planning and networking resource allocation, minimizing the total traveled distance. It proposes two solutions, namely (i) a Multi-access Edge Computing (MEC)-Aware UAVs' Path planning (MAUP) based on integer linear programming and (ii) an Accelerated MAUP (AMAUP), i.e., a heuristic and scalable approach that adopts the shortest weighted path algorithm considering directed graphs. The performance of the two solutions are evaluated using computer-based simulations and the obtained results demonstrate the effectiveness of the two solutions in achieving their design goals.

Original language	English
Title of host publication	2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Publisher	IEEE
ISBN (Electronic)	9781538676462
DOIs	https://doi.org/10.1109/WCNC.2019.8886000
Publication status	Published - 1 Apr 2019
MoE publication type	A4 Article in a conference publication
Event	IEEE Wireless Communications and Networking Conference - Marrakech, Morocco Duration: 15 Apr 2019 → 19 Apr 2019

Publication series

Name	IEEE Wireless Communications and Networking Conference
ISSN (Print)	1525-3511
ISSN (Electronic)	1558-2612

Conference

Conference	IEEE Wireless Communications and Networking Conference
Abbreviated title	WCNC
Country/Territory	Morocco
City	Marrakech
Period	15/04/2019 → 19/04/2019

Access to Document

10.1109/WCNC.2019.8886000

ELEC_Bekkouche_Edge_Cloud_WCNCAccepted author manuscript, 624 KB

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Full text

Cite this

@inproceedings{17b070516024424590ecd57ebd8b1e66,

title = "Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles",

abstract = "Unmanned Aerial Vehicles (UAVs) can offer a plethora of applications, provided that the appropriate ground control and complementary computing and storage services are available in close proximity. To accomplish this, edge cloud platforms, deployed at or close to the base stations, are essential. However, current UAV travel planning does not take into account the resource constraints of such edge cloud platforms. This paper introduces an aligned process for UAV flight planning and networking resource allocation, minimizing the total traveled distance. It proposes two solutions, namely (i) a Multi-access Edge Computing (MEC)-Aware UAVs' Path planning (MAUP) based on integer linear programming and (ii) an Accelerated MAUP (AMAUP), i.e., a heuristic and scalable approach that adopts the shortest weighted path algorithm considering directed graphs. The performance of the two solutions are evaluated using computer-based simulations and the obtained results demonstrate the effectiveness of the two solutions in achieving their design goals.",

author = "Oussama Bekkouche and Tarik Taleb and Miloud Bagaa and Konstantinos Samdanis",

note = "| openaire: EC/H2020/815191/EU//PriMO-5G; IEEE Wireless Communications and Networking Conference, WCNC ; Conference date: 15-04-2019 Through 19-04-2019",

year = "2019",

month = apr,

day = "1",

doi = "10.1109/WCNC.2019.8886000",

language = "English",

series = "IEEE Wireless Communications and Networking Conference",

publisher = "IEEE",

booktitle = "2019 IEEE Wireless Communications and Networking Conference, WCNC 2019",

address = "United States",

}

Bekkouche, O, Taleb, T, Bagaa, M & Samdanis, K 2019, Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles. in 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019., 8886000, IEEE Wireless Communications and Networking Conference, IEEE, IEEE Wireless Communications and Networking Conference, Marrakech, Morocco, 15/04/2019. https://doi.org/10.1109/WCNC.2019.8886000

Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles. / Bekkouche, Oussama; Taleb, Tarik; Bagaa, Miloud et al.
2019 IEEE Wireless Communications and Networking Conference, WCNC 2019. IEEE, 2019. 8886000 (IEEE Wireless Communications and Networking Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles

AU - Bekkouche, Oussama

AU - Taleb, Tarik

AU - Bagaa, Miloud

AU - Samdanis, Konstantinos

N1 - | openaire: EC/H2020/815191/EU//PriMO-5G

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Unmanned Aerial Vehicles (UAVs) can offer a plethora of applications, provided that the appropriate ground control and complementary computing and storage services are available in close proximity. To accomplish this, edge cloud platforms, deployed at or close to the base stations, are essential. However, current UAV travel planning does not take into account the resource constraints of such edge cloud platforms. This paper introduces an aligned process for UAV flight planning and networking resource allocation, minimizing the total traveled distance. It proposes two solutions, namely (i) a Multi-access Edge Computing (MEC)-Aware UAVs' Path planning (MAUP) based on integer linear programming and (ii) an Accelerated MAUP (AMAUP), i.e., a heuristic and scalable approach that adopts the shortest weighted path algorithm considering directed graphs. The performance of the two solutions are evaluated using computer-based simulations and the obtained results demonstrate the effectiveness of the two solutions in achieving their design goals.

AB - Unmanned Aerial Vehicles (UAVs) can offer a plethora of applications, provided that the appropriate ground control and complementary computing and storage services are available in close proximity. To accomplish this, edge cloud platforms, deployed at or close to the base stations, are essential. However, current UAV travel planning does not take into account the resource constraints of such edge cloud platforms. This paper introduces an aligned process for UAV flight planning and networking resource allocation, minimizing the total traveled distance. It proposes two solutions, namely (i) a Multi-access Edge Computing (MEC)-Aware UAVs' Path planning (MAUP) based on integer linear programming and (ii) an Accelerated MAUP (AMAUP), i.e., a heuristic and scalable approach that adopts the shortest weighted path algorithm considering directed graphs. The performance of the two solutions are evaluated using computer-based simulations and the obtained results demonstrate the effectiveness of the two solutions in achieving their design goals.

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Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles

Abstract

Publication series

Conference

Access to Document

OpenUrl availability

Other files and links

Fingerprint

PriMO-5G: Virtual Presence in Moving Objects through 5G

CSN: Customized Software Networking across Multiple Administrative Domains

Cite this

Edge Cloud Resource-aware Flight Planning for Unmanned Aerial Vehicles

Abstract

Publication series

Conference

Access to Document

OpenUrl availability

Other files and links

Fingerprint

Projects

PriMO-5G: Virtual Presence in Moving Objects through 5G

CSN: Customized Software Networking across Multiple Administrative Domains

Cite this