Projects per year
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.
|Title of host publication||2019 IEEE Wireless Communications and Networking Conference, WCNC 2019|
|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
|Name||IEEE Wireless Communications and Networking Conference|
|Conference||IEEE Wireless Communications and Networking Conference|
|Period||15/04/2019 → 19/04/2019|
Bagaa, M., El Marai, O., Maiouak, M., Bekkouche, O., Yang, B., Hellaoui, H., Taleb, T., Addad, R., Afolabi, I., Mada, B., Naas, S., Yu, H., Boudi, A., Maity, I., Kerfah, I., Benzaid, C., Amor, A. & Sehad, N.
01/09/2017 → 31/08/2021
Project: Academy of Finland: Other research funding