Aerial computing: Enhancing mobile cloud computing with unmanned aerial vehicles as data bridges—A Markov chain based dependability quantification
Francisco Airton Silva,
Iure Fe,
Carlos Brito,
Gabriel Araujo,
Leonel Feitosa,
Tuan Anh Nguyen,
Kwonsu Jeon,
Jae-Woo Lee,
Dugki Min,
Eunmi Choi
Affiliations
Francisco Airton Silva
Laboratory of Applied Research to Distributed Systems (PASID), Federal University of Piaui (UFPI), R. Cicero Duarte, No. 905 - Junco, 64607-670, Picos, Piaui, Brazil
Iure Fe
Laboratory of Applied Research to Distributed Systems (PASID), Federal University of Piaui (UFPI), R. Cicero Duarte, No. 905 - Junco, 64607-670, Picos, Piaui, Brazil
Carlos Brito
Laboratory of Applied Research to Distributed Systems (PASID), Federal University of Piaui (UFPI), R. Cicero Duarte, No. 905 - Junco, 64607-670, Picos, Piaui, Brazil
Gabriel Araujo
Laboratory of Applied Research to Distributed Systems (PASID), Federal University of Piaui (UFPI), R. Cicero Duarte, No. 905 - Junco, 64607-670, Picos, Piaui, Brazil
Leonel Feitosa
Laboratory of Applied Research to Distributed Systems (PASID), Federal University of Piaui (UFPI), R. Cicero Duarte, No. 905 - Junco, 64607-670, Picos, Piaui, Brazil
Tuan Anh Nguyen
Konkuk Aerospace Design-Airworthiness Institute (KADA), Konkuk University, Seoul 05029, South Korea; Department of Computer Science and Engineering, College of Engineering, Konkuk University, Seoul 05029, South Korea; Corresponding authors.
Kwonsu Jeon
Konkuk Aerospace Design-Airworthiness Institute (KADA), Konkuk University, Seoul 05029, South Korea
Jae-Woo Lee
Department of Aerospace Engineering, Konkuk University, Seoul 05029, South Korea; Corresponding authors.
Dugki Min
Department of Computer Science and Engineering, College of Engineering, Konkuk University, Seoul 05029, South Korea; Department of Artificial Intelligence, Graduate School, Konkuk University, Seoul 05029, South Korea; Corresponding authors.
Eunmi Choi
School of Software, College of Computer Science, Kookmin University, Seoul 02707, South Korea
Aerial Computing, utilizing unmanned aerial vehicles (UAVs), has emerged as a promising solution to enhance mobile cloud computing (MCC) infrastructure for the Internet of Things (IoT). The continuous generation of vast amounts of data by IoT devices requires efficient processing and monitoring for timely decision-making. However, wireless connections between IoT devices and remote servers can be unreliable, resulting in data loss. UAVs, with their increasing processing power and autonomy, can act as bridges between IoT devices and remote servers such as edge or cloud computing. In that context, this paper proposes a continuous time Markov chain (CTMC) models for an aerial computing system to evaluate system dependability metrics including availability and reliability. Sensitivity analysis is conducted to provide extended CTMC models with improved system availability. The proposed advanced model reduces downtime by 62 h compared to the baseline model, showcasing the potential of UAVs in enhancing the availability and reliability of MCC infrastructures. The use of UAVs and MCC in aerial computing is believed to be a win–win solution for cost-effective and energy-saving communication and computation services in various environments.