Stackelberg Game Approach for Service Selection in UAV Networks

Nowadays, mobile devices are expected to perform a growing number of tasks, whose complexity is also increasing significantly. However, despite great technological improvements in the last decade, such devices still have limitations in terms of processing power and battery lifetime. In this context,...

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Bibliographic Details
Main Authors: Calafate, C.T (Author), Hadjkouider, A.M (Author), Kerrache, C.A (Author), Korichi, A. (Author), Sahraoui, Y. (Author)
Format: Article
Language:English
Published: MDPI 2023
Subjects:
Online Access:View Fulltext in Publisher
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LEADER 03145nam a2200445Ia 4500
001 10.3390-s23094220
008 230529s2023 CNT 000 0 und d
020 |a 14248220 (ISSN) 
245 1 0 |a Stackelberg Game Approach for Service Selection in UAV Networks 
260 0 |b MDPI  |c 2023 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/s23094220 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159196092&doi=10.3390%2fs23094220&partnerID=40&md5=f04230806b43b7e5d9235b543a0ef074 
520 3 |a Nowadays, mobile devices are expected to perform a growing number of tasks, whose complexity is also increasing significantly. However, despite great technological improvements in the last decade, such devices still have limitations in terms of processing power and battery lifetime. In this context, mobile edge computing (MEC) emerges as a possible solution to address such limitations, being able to provide on-demand services to the customer, and bringing closer several services published in the cloud with a reduced cost and fewer security concerns. On the other hand, Unmanned Aerial Vehicle (UAV) networking emerged as a paradigm offering flexible services, new ephemeral applications such as safety and disaster management, mobile crowd-sensing, and fast delivery, to name a few. However, to efficiently use these services, discovery and selection strategies must be taken into account. In this context, discovering the services made available by a UAV-MEC network, and selecting the best services among those available in a timely and efficient manner, can become a challenging task. To face these issues, game theory methods have been proposed in the literature that perfectly suit the case of UAV-MEC services by modeling this challenge as a Stackelberg game, and using existing approaches to find the solution for such a game aiming at an efficient services’ discovery and service selection. Hence, the goal of this paper is to propose Stackelberg-game-based solutions for service discovery and selection in the context of UAV-based mobile edge computing. Simulations results conducted using the NS-3 simulator highlight the efficiency of our proposed game in terms of price and QoS metrics. © 2023 by the authors. 
650 0 4 |a Aerial vehicle 
650 0 4 |a Antennas 
650 0 4 |a Battery lifetime 
650 0 4 |a Computer games 
650 0 4 |a Disaster prevention 
650 0 4 |a Disasters 
650 0 4 |a Game approach 
650 0 4 |a game theory 
650 0 4 |a Game theory 
650 0 4 |a mobile edge computing 
650 0 4 |a Mobile edge computing 
650 0 4 |a Processing power 
650 0 4 |a Service discovery 
650 0 4 |a Service selection 
650 0 4 |a services selection 
650 0 4 |a Stackelberg 
650 0 4 |a Stackelberg Games 
650 0 4 |a Technological improvements 
650 0 4 |a UAVs 
650 0 4 |a Unmanned aerial vehicles (UAV) 
650 0 4 |a Vehicle network 
700 1 0 |a Calafate, C.T.  |e author 
700 1 0 |a Hadjkouider, A.M.  |e author 
700 1 0 |a Kerrache, C.A.  |e author 
700 1 0 |a Korichi, A.  |e author 
700 1 0 |a Sahraoui, Y.  |e author 
773 |t Sensors