Sistema de monitoramento de métricas para Ambiente integrado UAV-FOG / Metric monitoring system for Integrated UAV-FOG environment

João Lucas Ribeiro Barbosa, Isaac Barros da Costa Moreira, Wendel Barros Serra, Warley Muricy Valente Junior, Hugo Kuribayashi, João Victor Costa Carmona

Abstract


Apesar dos avanços recentes que tornaram o uso de UAVs (Unmanned Air Vehicles) em diversos cenários uma realidade, há vários desafios a serem enfrentados para explorar todo o seu potencial. O uso de Fog Computing se torna uma saída para auxiliar estes dispositivos móveis com energia e hardware limitados a terceirizar toda a capacidade de processamento para um recurso remoto na borda da rede. Este trabalho apresenta o de desenvolvimento e implementação de um sistema de levantamento de métricas para avaliação de desempenho da técnica de offloading com uso de drone e servidor Cloudlet em ambiente de Fog Computing para a transmissão e processamento de imagens através de algoritmo tradicional de detecção e reconhecimento facial em tempo real, em diferentes cenários, visando a análise do consumo energético do drone, ao longo do processo, a intensidade de sinal entre o drone e o orquestrador, e o tempo de processamento gasto em cada entidade, drone e maquinas virtuais.


Keywords


UAV, Fog Computing, Offloading e Cloulets.

References


BAHTOVSKI, A.; GUSEV, M. Cloudlet challenges. Procedia Engineering, Elsevier, v. 69, p. 704–711, 2014.

BARBOSA, J. et al. Análise de desempenho da técnica de offloading de imagens com drone em ambiente de computacão em névoa. In: SBC. Anais do XVIII Workshop em Desempenho de Sistemas Computacionais e de Comunicação.

BONOMI, F. et al. Fog Computing and its role in the internet of things. In: ACM. Proceedings of the first edition of the MCC workshop on Mobile Cloud computing. [S.l.], 2012. p. 13–16.

HAYAT, S.; YANMAZ, E.; MUZAFFAR, R. Survey on unmanned aerial vehicle networks for civil applications: A communications viewpoint. IEEE Communications Surveys & Tutorials, IEEE, v. 18, n. 4, p. 2624–2661, 2016.

HU, P. et al. Survey on Fog Computing: architecture, key technologies, applications and open issues. Journal of network and computer applications, Elsevier, v. 98, p. 27–42, 2017.

JUNIOR, W.; SILVA, B.; DIAS, K. A systematic mapping study on mobility mechanisms for cloud service provisioning in mobile cloud ecosystems. Computers & Electrical Engineering, Elsevier Ltd, v. 0, p. 1–18, feb 2018. ISSN 00457906.

LIMA, C. M. d. A.; SILVA, E. A. da; VELLOSO, P. B. Avaliação de desempenho do ieee 802.11 para coleta de grande volume de dados em florestas com auxílio de drones. In: SBC. 17º Workshop em Desempenho de Sistemas Computacionais e de Comunicação (WPerformance 2018). [S.l.], 2018. v. 17, n. 1/2018.

LUO, C. et al. A uav-cloud system for disaster sensing applications. In: IEEE. 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). [S.l.], 2015. p. 1–5.

MACH, P.; BECVAR, Z. Mobile Edge Computing: A survey on architecture and computation offloading. IEEE Communications Surveys & Tutorials, IEEE, v. 19, n. 3, p. 1628– 1656, 2017.

MOHAMED, N. et al. Uavfog: A uav-based Fog Computing for internet of things. In: IEEE. 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). [S.l.], 2017. p. 1–8.

MOHAMED, N. et al. Unmanned aerial vehicles applications in future smart cities. Technological Forecasting and Social Change, Elsevier, 2018.

MOTLAGH, N. H.; BAGAA, M.; TALEB, T. Uav-based iot platform: A crowd surveillance use case. IEEE Communications Magazine, IEEE, v. 55, n. 2, p. 128–134, 2017.

OPENFOGCONSORTIUM. Openfog reference architecture for Fog Computing. 2017

PAN, J.; MCELHANNON, J. Future edge cloud and Edge computing for internet of things applications. IEEE Internet of Things Journal, IEEE, v. 5, n. 1, p. 439–449, 2017.

ROMAN, R.; LOPEZ, J.; MAMBO, M. Mobile Edge Computing, fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems, Elsevier, v. 78, p. 680–698, 2018.

SARA, M.; JAWHAR, I.; NADER, M. A softwarization architecture for uavs and wsns as part of the cloud environment. In: IEEE. 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW). [S.l.], 2016. p. 13–18

SHAKHATREH, H. et al. Unmanned aerial vehicles (uavs): A survey on civil applications and key research challenges. IEEE Access, IEEE, v. 7, p. 48572–48634, 2019.

VALENTINO, R.; JUNG, W.-S.; KO, Y.-B. Opportunistic computational offloading system for clusters of drones. In: IEEE. 2018 20th International Conference on Advanced Communication Technology (ICACT). [S.l.], 2018. p. 303–306.

YI, S.; LI, C.; LI, Q. A survey of Fog Computing: concepts, applications and issues. In: ACM. Proceedings of the 2015 workshop on mobile big data. [S.l.], 2015. p. 37–42.

YOUSEFPOUR, A. et al. All one needs to know about Fog Computing and related Edge computing paradigms: A complete survey. Journal of Systems Architecture, Elsevier B.V., n. February, 2019.

YU, W. et al. A survey on the Edge computing for the internet of things. IEEE access, IEEE, v. 6, p. 6900–6919, 2017.




DOI: https://doi.org/10.34117/bjdv6n6-411

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