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Assuring Autonomy of UAVs in Mission-critical Scenarios by Performability Modeling and Analysis

Authors:

Ermeson Andrade,

Fumio MachidaAuthors Info & Claims

ACM Transactions on Cyber-Physical Systems, Volume 8, Issue 3

Article No.: 30, Pages 1 - 24

https://doi.org/10.1145/3624572

Published: 13 July 2024 Publication History

Abstract

Uncrewed Aerial Vehicles (UAVs) have been used in mission-critical scenarios such as Search and Rescue (SAR) missions. In such a mission-critical scenario, flight autonomy is a key performance metric that quantifies how long the UAV can continue the flight with a given battery charge. In a UAV running multiple software applications, flight autonomy can also be impacted by faulty application processes that excessively consume energy. In this article, we propose Flight Autonomy Assurance as a framework to assure the autonomy of a UAV considering faulty application processes through performability modeling and analysis. The framework employs hierarchically configured stochastic Petri nets, evaluates the performability-related metrics, and guides the design of mitigation strategies to improve autonomy. We consider a SAR mission as a case study and evaluate the feasibility of the framework through extensive numerical experiments. The numerical results quantitatively show how autonomy is enhanced by offloading and restarting faulty application processes.

References

[1]

Marco Ajmone Marsan, Gianni Conte, and Gianfranco Balbo. 1984. A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems. ACM Trans. Comput. Syst. 2, 2 (1984), 93–122.

Digital Library

[2]

Ermeson Andrade, Fumio Machida, Roberto Pietrantuono, and Domenico Cotroneo. 2020. Software aging in image classification systems on cloud and edge. In Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW’20). IEEE, 342–348.

[3]

João Bachiega Jr., Breno Costa, and Aleteia P. F. Araujo. 2022. Computational perspective of the fog node. Retrieved from https://arXiv:2203.07425

[4]

Flavio Bonomi, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. 2012. Fog computing and its role in the internet of things. In Proceedings of the 1st Edition of the MCC Workshop on Mobile Cloud Computing. 13–16.

[5]

Hwei-Ming Chung, Sabita Maharjan, Yan Zhang, Frank Eliassen, and Kai Strunz. 2020. Placement and routing optimization for automated inspection with unmanned aerial vehicles: A study in offshore wind farm. IEEE Trans. Industr. Inform. 17, 5 (2020), 3032–3043.

[6]

Gianfranco Ciardo, Jogesh K. Muppala, Kishor S. Trivedi et al. 1989. SPNP: Stochastic Petri net package. In Proceedings of the 3rd International Workshop on Petri Nets and Performance Models (PNPM’89). Citeseer, 142–151.

[7]

Domenico Cotroneo, Francesco Fucci, Antonio Ken Iannillo, Roberto Natella, and Roberto Pietrantuono. 2016. Software aging analysis of the android mobile os. In Proceedings of the IEEE 27th International Symposium on Software Reliability Engineering (ISSRE’16). IEEE, 478–489.

[8]

Graham R. Drozeski. 2005. A Fault-tolerant Control Architecture for Unmanned Aerial Vehicles. Georgia Institute of Technology.

[9]

Emad Ebeid, Martin Skriver, Kristian Husum Terkildsen, Kjeld Jensen, and Ulrik Pagh Schultz. 2018. A survey of Open-Source UAV flight controllers and flight simulators. Microprocess. Microsyst. 61 (2018), 11–20. DOI:

[10]

Michael A. Goodrich, Bryan S. Morse, Damon Gerhardt, Joseph L. Cooper, Morgan Quigley, Julie A. Adams, and Curtis Humphrey. 2008. Supporting wilderness search and rescue using a camera-equipped mini UAV. J. Field Robot. 25, 1-2 (2008), 89–110.

[11]

Michael Grottke, Rivalino Matias, and Kishor S. Trivedi. 2008. The fundamentals of software aging. In Proceedings of the IEEE International Conference on Software Reliability Engineering Workshops (ISSRE’08). IEEE, 1–6.

[12]

Lav Gupta, Raj Jain, and Gabor Vaszkun. 2015. Survey of important issues in UAV communication networks. IEEE Commun. Surveys Tutor. 18, 2 (2015), 1123–1152.

Digital Library

[13]

Christophe Hirel, Bruno Tuffin, and Kishor S. Trivedi. 2000. SPNP: Stochastic Petri nets. version 6.0. In Proceedings of the 11th International Conference on Computer Performance Evaluation, Modelling Techniques, and Tools (TOOLS’00). Springer, 354–357.

[14]

Shahrear Iqbal. 2021. A study on UAV operating system security and future research challenges. In Proceedings of the IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC’21). 0759–0765.

[15]

Hao Jiang, Hongli Yang, Shengchao Qin, Zhendong Su, Jian Zhang, and Jun Yan. 2017. Detecting energy bugs in android apps using static analysis. In Proceedings of the International Conference on Formal Engineering Methods. Springer, 192–208.

[16]

Anamta Khan, Naghmeh Ivaki, and Henrique Madeira. 2022. Are UAVs’ flight controller software reliable? In Proceedings of the IEEE 27th Pacific Rim International Symposium on Dependable Computing (PRDC’22). IEEE, 194–204.

[17]

Fumio Machida and Ermeson Andrade. 2021. Availability modeling for drone image processing systems with adaptive offloading. In Proceedings of the IEEE 26th Pacific Rim International Symposium on Dependable Computing (PRDC’21). IEEE, 93–103.

[18]

Fumio Machida and Ermeson Andrade. 2021. PA-offload: Performability-aware adaptive fog offloading for drone image processing. In Proceedings of the IEEE 5th International Conference on Fog and Edge Computing (ICFEC’21). IEEE, 66–73.

[19]

Fumio Machida, Qingyang Zhang, and Ermeson Andrade. 2023. Performability analysis of adaptive drone computation offloading with fog computing. Future Gen. Comput. Syst. 145 (2023), 121–135. DOI:

Digital Library

[20]

Paulo Maciel, Rubens Matos, Bruno Silva, Jair Figueiredo, Danilo Oliveira, Iure Fé, Ronierison Maciel, and Jamilson Dantas. 2017. Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In Proceedings of the IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC’17). IEEE, 50–57.

[21]

Rubens Matos, Jean Araujo, Danilo Oliveira, Paulo Maciel, and Kishor Trivedi. 2015. Sensitivity analysis of a hierarchical model of mobile cloud computing. Simul. Model. Pract. Theory 50 (2015), 151–164.

[22]

Arvind Merwaday and Ismail Guvenc. 2015. UAV assisted heterogeneous networks for public safety communications. In Proceedings of the IEEE Wireless Communications and Networking Conference Workshops (WCNCW’15). IEEE, 329–334.

[23]

Mohamed-Ayoub Messous, Sidi-Mohammed Senouci, Hichem Sedjelmaci, and Soumaya Cherkaoui. 2019. A game theory-based efficient computation offloading in an UAV network. IEEE Trans. Vehic. Technol. 68, 5 (2019), 4964–4974.

[24]

Michael K. Molloy. 1982. Performance analysis using stochastic Petri nets. IEEE Trans. Comput. 31, 09 (1982), 913–917.

Digital Library

[25]

Tuan Anh Nguyen, Kwonsu Jeon, Jae-Woo Lee, Iure Fe, and Francisco Airton Silva. 2022. Model-driven mission dependability design of unmanned aerial systems. In Proceedings of the AIAA AVIATION Forum. 4091.

[26]

Pijush Kanti Dutta Pramanik, Nilanjan Sinhababu, Bulbul Mukherjee, Sanjeevikumar Padmanaban, Aranyak Maity, Bijoy Kumar Upadhyaya, Jens Bo Holm-Nielsen, and Prasenjit Choudhury. 2019. Power consumption analysis, measurement, management, and issues: A state-of-the-art review of smartphone battery and energy usage. IEEE Access 7 (2019), 182113–182172.

[27]

Supravat Samanta, Subhajit Pramanick, and Partha Sarathi Mandal. 2021. Fault-tolerant covering points by UAVs. In Proceedings of the 8th International Conference on Networking, Systems and Security. 60–64.

Digital Library

[28]

David C. Schedl, Indrajit Kurmi, and Oliver Bimber. 2021. An autonomous drone for search and rescue in forests using airborne optical sectioning. Sci. Robot. 6, 55 (2021), eabg1188.

[29]

Tabea Schmidt and Alexander Pretschner. 2022. StellaUAV: A tool for testing the safe behavior of UAVs with scenario-based testing. In Proceedings of the IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE’22). IEEE, 37–47.

[30]

Mahmood Shafiee, Zeyu Zhou, Luyao Mei, Fateme Dinmohammadi, Jackson Karama, and David Flynn. 2021. Unmanned aerial drones for inspection of offshore wind turbines: A mission-critical failure analysis. Robotics 10, 1 (2021), 26.

[31]

Hazim Shakhatreh, Ahmad H. Sawalmeh, Ala Al-Fuqaha, Zuochao Dou, Eyad Almaita, Issa Khalil, Noor Shamsiah Othman, Abdallah Khreishah, and Mohsen Guizani. 2019. Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges. IEEE Access 7 (2019), 48572–48634.

[32]

Mario Silvagni, Andrea Tonoli, Enrico Zenerino, and Marcello Chiaberge. 2017. Multipurpose UAV for search and rescue operations in mountain avalanche events. Geomat., Nat. Hazards Risk 8, 1 (2017), 18–33.

[33]

Tullio Joseph Tanzi, Madhu Chandra, Jean Isnard, Daniel Camara, Olivier Sébastien, and Fanilo Harivelo. 2016. Towards “drone-borne” disaster management: Future application scenarios. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Vol. III-8). Copernicus GmbH, 181–189.

[34]

Max Taylor, Jayson Boubin, Haicheng Chen, Christopher Stewart, and Feng Qin. 2021. A study on software bugs in unmanned aircraft systems. In Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS’21). 1439–1448. DOI:

[35]

Panagiotis Vekris, Ranjit Jhala, Sorin Lerner, and Yuvraj Agarwal. 2012. Towards verifying android apps for the absence of no-sleep energy bugs. In Proceedings of the Workshop on Power-Aware Computing and Systems.

[36]

Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, and Yulei Sui. 2021. An exploratory study of autopilot software bugs in unmanned aerial vehicles. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 20–31.

Digital Library

[37]

Kengo Watanabe, Fumio Machida, Ermeson Andrade, Roberto Pietrantuono, and Domenico Cotroneo. 2023. Software aging in real-time object detection systems on edge servers. In Proceedings of the 38th Annual ACM Symposium on Applied Computing. 671–678.

Digital Library

[38]

Mingyuan Xia, Wenbo He, Xue Liu, and Jie Liu. 2013. Why application errors drain battery easily? A study of memory leaks in smartphone apps. In Proceedings of the Workshop on Power-Aware Computing and Systems. 1–5.

Digital Library

[39]

Connie Zeng, Jacob Knickerbocker, Razia Shaik, and Kevin Marx. 2020. Routing of hitchhiking drones with respect to autonomous and connected vehicles. U.S. Patent App. 16/756,582.

[40]

Juan Zhang, James F. Campbell, Donald C. Sweeney II, and Andrea C. Hupman. 2021. Energy consumption models for delivery drones: A comparison and assessment. Transport. Res. D: Transport Environ. 90 (2021), 102668.

Cited By

Byun SLee D(2024)Performability Evaluation of Autonomous Underwater Vehicles Using Phased Fault Tree AnalysisJournal of Marine Science and Engineering10.3390/jmse1204056412:4(564)Online publication date: 27-Mar-2024
https://doi.org/10.3390/jmse12040564
Hiroi IMachida FAndrade E(2024)Energy Bugs in Object Detection Software on Battery-Powered Devices2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW63542.2024.00097(313-320)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSREW63542.2024.00097

Index Terms

Assuring Autonomy of UAVs in Mission-critical Scenarios by Performability Modeling and Analysis
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks

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Information & Contributors

Information

Published In

cover image ACM Transactions on Cyber-Physical Systems

ACM Transactions on Cyber-Physical Systems Volume 8, Issue 3

July 2024

308 pages

EISSN:2378-9638

DOI:10.1145/3613667

Editor:
Chenyang Lu
Washington University in St. Louis, USA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 13 July 2024

Online AM: 16 September 2023

Accepted: 03 September 2023

Revised: 28 August 2023

Received: 11 April 2023

Published in TCPS Volume 8, Issue 3

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Cited By

Byun SLee D(2024)Performability Evaluation of Autonomous Underwater Vehicles Using Phased Fault Tree AnalysisJournal of Marine Science and Engineering10.3390/jmse1204056412:4(564)Online publication date: 27-Mar-2024
https://doi.org/10.3390/jmse12040564
Hiroi IMachida FAndrade E(2024)Energy Bugs in Object Detection Software on Battery-Powered Devices2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW63542.2024.00097(313-320)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSREW63542.2024.00097

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