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6. Other applications

This section covers the other identified applications.

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6.1. Live Streaming Application

Ref: Li, D. C., Chen, B. H., Tseng, C. W., & Chou, L. D. (2020). A Novel Genetic Service Function Deployment Management Platform for Edge Computing. Mobile Information Systems, 2020.

6.2. Face recognizer application

6.2.1. Example 1

• Ref_1: Basic, F., Aral, A., & Brandic, I. (2019, June). Fuzzy handoff control in edge offloading. In 2019 IEEE International Conference on Fog Computing (ICFC) (pp. 87-96). IEEE.

• Ref_2: De Maio, V., & Brandic, I. (2018). First hop mobile offloading of dag computations. IEEE/ACM CCGRID (pp. 83-92). Source code

6.2.2. Example 2

Ref: Kuang, L., Gong, T., OuYang, S., Gao, H., & Deng, S. (2020). Offloading decision methods for multiple users with structured tasks in edge computing for smart cities. Future Generation Computer Systems, 105, 717-729.

6.2.3. Example 3

Ref: Perala, S. S. N., Galanis, I., & Anagnostopoulos, I. (2018). Fog computing and efficient resource management in the era of Internet-of-video things (IoVT). In IEEE ISCAS. pp. 1-5.

6.3. Navigator application

• Ref_1: Basic, F., Aral, A., & Brandic, I. (2019, June). Fuzzy handoff control in edge offloading. IEEE ICFC. (pp. 87-96). IEEE.

• Ref_2: De Maio, V., & Brandic, I. (2018). First hop mobile offloading of dag computations. IEEE/ACM CCGRID (pp. 83-92). Source code

6.4. Sock shop demo application

Ref: Guerrero, C., Lera, I., & Juiz, C. (2019). A lightweight decentralized service placement policy for performance optimization in fog computing. Journal of Ambient Intelligence and Humanized Computing, 10(6), 2435-2452.

6.5. Antivirus application

Ref: De Maio, V., & Brandic, I. (2018). First hop mobile offloading of dag computations. IEEE/ACM CCGRID (pp. 83-92). Source code

6.6. Chess application

Ref: De Maio, V., & Brandic, I. (2018). First hop mobile offloading of dag computations. IEEE/ACM CCGRID (pp. 83-92). Source code

6.7. Montage application for assembling multiple independent astronomical images

Ref: De Maio, V., & Kimovski, D. (2020). Multi-objective scheduling of extreme data scientific workflows in Fog. Future Generation Computer Systems, 106, 171-184.

6.8. MeteoAG scientific application for conduction meteorological simulations

Ref: De Maio, V., & Kimovski, D. (2020). Multi-objective scheduling of extreme data scientific workflows in Fog. Future Generation Computer Systems, 106, 171-184.

6.9. Epigenomics workflow pipeline that executes various genome sequencing operations

Ref: De Maio, V., & Kimovski, D. (2020). Multi-objective scheduling of extreme data scientific workflows in Fog. Future Generation Computer Systems, 106, 171-184.

6.10. Burrows-Wheeler aligner workflow for performing low-divergent sequencing against a large reference genome

Ref: De Maio, V., & Kimovski, D. (2020). Multi-objective scheduling of extreme data scientific workflows in Fog. Future Generation Computer Systems, 106, 171-184.

6.11. Earthquake application

Ref: Mouradian, C., Kianpisheh, S., Abu-Lebdeh, M., Ebrahimnezhad, F., Jahromi, N. T., & Glitho, R. H. (2019). Application component placement in NFV-based hybrid cloud/fog systems with mobile fog nodes. IEEE Journal on Selected Areas in Communications, 37(5), 1130-1143.

6.12. A smart agriculture application.

Ref: A. Brogi, S. Forti and A. Ibrahim (2017). How to Best Deploy Your Fog Applications, Probably. IEEE ICFEC. pp. 105-114.

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5. Smart home/ Smart cities applications