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Title Vehicle Assisted Computing Offloading for Unmanned Aerial Vehicles in Smart City
ID_Doc 36449
Authors Dai, MH; Su, Z; Xu, QC; Zhang, N
Title Vehicle Assisted Computing Offloading for Unmanned Aerial Vehicles in Smart City
Year 2021
Published Ieee Transactions On Intelligent Transportation Systems, 22, 3
DOI 10.1109/TITS.2021.3052979
Abstract Smart city emerges a promising paradigm for improving operational efficiency of city and comfort of people. With embedded multi-sensors, Unmanned Aerial Vehicles (UAVs) hold great potential for collecting sensing data and providing social services in smart city. However, due to the limited battery lifetime and processing capacities of UAVs, the efficient offloading scheme of UAVs is urgently needed in smart city. Therefore, in this article, a vehicle-assisted computing offloading architecture for UAVs is proposed to improve offloading efficiency by harnessing the moving vehicles in smart city. We first develop an offloading model for UAVs to determine the offloading strategy. Next, to select the optimal vehicles for offloading, we formulate a matching scheme based on the preference lists of UAVs and vehicles to derive the optimal matching between UAVs and vehicles. After that, to improve the offloading efficiency and maximize the utilities of UAVs and vehicles, the transaction process of computing data between UAVs and vehicles is modeled as a bargaining game. Moreover, an offloading algorithm for UAVs and vehicles is proposed to obtain the optimal strategy. Finally, simulations are performed to validate the efficiency of the proposed offloading scheme. The results demonstrate that the proposed offloading scheme can significantly save resource and improve the utilities of UAVs and vehicles.
Author Keywords Smart cities; Task analysis; Computational modeling; Games; Unmanned aerial vehicles; Interference; Computer architecture; Smart city; unmanned aerial vehicles (UAVs); computing offloading; matching scheme; bargaining game
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000626338600050
WoS Category Engineering, Civil; Engineering, Electrical & Electronic; Transportation Science & Technology
Research Area Engineering; Transportation
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