Computation offloading game for an UAV network in mobile edge computing

Mohamed-Ayoub Messous 1, * Hichem Sedjelmaci 1, * Houari Noureddin 2 Sidi Mohammed Senouci 1, *
* Auteur correspondant
1 DRIVE - Département de Recherche en Ingénierie des Véhicules pour l'Environnement [Nevers]
2 USTHB - Université des Sciences et de la Technologie Houari Boumediene [Alger]
Abstract : Due to the limitations of mobile devices in terms of processing power and battery lifetime, cloud based solutions offer an attractive approach to answer these shortcomings. Since offloading intensive computation tasks to an edge/cloud server would achieve impressive performances, computation offloading paradigm has attracted the focus of many research groups in the last few years. This paper considers the problem of computation offloading while achieving a tradeoff between execution time and energy consumption. The proposed solution is intended for a fleet of small drones that are required to achieve highly intensive computation tasks. Drones need to detect, identify and classify objects or situations. Thus, they are brought to deal with intensive tasks such as pattern recognition and video preprocessing. The latter implement very complex calculations and typically require dedicated and powerful processors, which would definitely accentuate the dilemma between energy and delay. We adopted a game theory model where the players are all the drones in the network with three possible strategies. We defined the cost function to be minimized as a combination of energy overhead and delay. The simulation results are very promising and the achieved performances outperformed their counterparts in terms of average system wide cost and scalability.
Keywords : Mobile communication Wireless communication autonomous aerial vehicles cloud computing computerised control energy consumption mobile computing mobility management (mobile radio) synchronisation telecommunication power management energy overhead game theory model video preprocessing pattern recognition edge-cloud server offloading intensive computation cloud based solutions battery lifetime processing power mobile devices UAV network unmanned aerial vehicles computation offloading game Computation Offloading Mobile Edge Computing Game Theory UAV (Unmanned Areal Vehicles)
Type de document :
Communication dans un congrès
2017 IEEE International Conference on Communications (ICC), May 2017, Paris, France. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, Communications (ICC), 2017 IEEE International Conference on, pp.1-6, 2017, 2017 IEEE International Conference on Communications (ICC) 〈http://ieeexplore.ieee.org/document/7996483/〉. 〈10.1109/ICC.2017.7996483〉
Liste complète des métadonnées
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01588200
Contributeur : Ub_drive Université de Bourgogne <>
Soumis le : vendredi 15 septembre 2017 - 12:02:12
Dernière modification le : vendredi 23 février 2018 - 12:18:08

Identifiants

Collections

Citation

Mohamed-Ayoub Messous, Hichem Sedjelmaci, Houari Noureddin, Sidi Mohammed Senouci. Computation offloading game for an UAV network in mobile edge computing. 2017 IEEE International Conference on Communications (ICC), May 2017, Paris, France. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, Communications (ICC), 2017 IEEE International Conference on, pp.1-6, 2017, 2017 IEEE International Conference on Communications (ICC) 〈http://ieeexplore.ieee.org/document/7996483/〉. 〈10.1109/ICC.2017.7996483〉. 〈hal-01588200〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

12

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD