Abstract
The fog computing approach has come up as a distributed mechanism for capturing of data, its further processing, and allocation of resources associated with the Internet of things (IoT). The IoT services require several quality of service (QoS) parameters such as bandwidth utilization, resource provisioning, energy consumption, service delay. A new architecture for fog computing based on QoS parameters has been designed. A distributed solution for cloud-IoT has been presented where data is distributed optimally among several fog nodes/mini-clouds. The virtual machines (VMs) located in the edge devices are facilitated by these distributed fog nodes/mini-clouds to take care of IoT traffic. However, very little research has been done on designing any QoS-aware architecture for fog computing. The mathematical formulation for the presented model has also been proposed, and hence, the performance analysis of the system is shown in terms of the QoS metrics.
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References
Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pp. 13–16, ACM, Helsinki, Finland (2012). https://doi.org/10.1145/2342509.2342513
Aazam, M., Huh, E.N.: Fog computing and smart gateway based communication for cloud of things. In: IEEE International Conference on Future Internet of Things and Cloud, pp. 464–470, IEEE, Barcelona (2014). https://doi.org/10.1109/FiCloud.2014.83
Gia, T.N., Jiang, M., Rahmani, A.M., Westerlund, T., Liljeberg, P., Tenhunen, H.: Fog computing in health-care internet of things: a case study on ECG feature extraction. In: IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, pp. 356–363, IEEE, Liverpool (2015). https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.51
Aazam, M., Huh, E.N.: Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. In: IEEE 29th International Conference on Advanced Information Networking and Applications, pp. 687–694 , IEEE, Gwangiu (2015). https://doi.org/10.1109/AINA.2015.254
Abdullahi, I., Arif, S., Hassan, S.: Ubiquitous shift with information centric network caching using fog computing. In: Computational Intelligence in Information Systems. Advances in Intelligent Systems and Computing, vol. 331, pp. 327–335 , Springer (2014). https://doi.org/10.1007/978-3-319-13153-5-32
Skala, K., Davidovic, D., Afghan, E., Sojat, Z.: Scalable distributed computing hierarchy: cloud, fog and dew computing. Open J. Cloud Comput. (OJCC) 2(1), 16–24 (2015)
Tang, B., Chen, Z., Hefferman, G., Wei, T., He, H., Yang, Q.: A hierarchical distributed fog computing architecture for big data analysis in smart cities. In: Proceedings of the ASE BigData and Social Informatics, , ACM , Kaohsiung, Taiwan (2015). https://doi.org/10.1145/2818869.2818898
Rahmani, A., Thanigaivelan, N., Gia, T., Granados, J., Negash, B., Liljeberg, P., Tenhunen, H.: Smart eHealth gateway: bringing intelligence to internet-of-things based ubiquitous healthcare systems. In: 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), pp. 826–834, IEEE, Las Vegas, USA (2015). https://doi.org/10.1109/CCNC.2015.7158084
Bonomi, F.: The smart and connected vehicle and the internet of things
Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pp. 13–16, ACM, Helsinki, Finland (2012). https://doi.org/10.1145/2342509.2342513
Bonomi, F., Milito, R., Natarajan, P., Zhu, J.: Fog computing: a platform for internet of things and analytics. In: Bessis N., Dobre C. (eds.) Big Data and Internet of Things: A Roadmap for Smart Environments, vol. 546 , pp. 169–186, Springer (2014)
Gazis, V., Leonardi, A., Mathioudakis, K., Sasloglou, K., Kirikas, P., Sudhaakar, R.: Components of fog computing in an industrial internet of things context. In: 12th Annual IEEE International Conference on Sensing, Communication, and Networking - Workshops (SECON Workshops), pp. 1–6, IEEE, Seattle, USA(2015). https://doi.org/10.1109/SECONW.2015.7328144
Cisco fog computing solutions: unleash the power of the internet of things http://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf
Busching, F., Schildt, S., Wolf, L.: DroidCluster: towards smartphone cluster computing- the streets are paved with potential computer clusters. In: 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 114-117, IEEE, Macau, China (2012). https://doi.org/10.1109/ICDCSW.2012.59
Masri, W., Ridhawi, I.A., Mostafa, N., Pourghomi, P.: Minimizing delay in IoT systems through collaborative fog-to-fog (F2F) communication. In: 9th IEEE International Conference on Ubiquitous and Future Networks (ICUFN), pp. 1005-1010, IEEE, Milan (2017). https://doi.org/10.1109/ICUFN.2017.7993950
Kumar, A., Narendra, N.C., Bellur, U.: Uploading and replicating internet of things (IoT) data on distributed cloud storage. In: IEEE 9th International Conference on Cloud Computing (CLOUD), pp. 670-677,IEEE, San Francisco, CA (2016). https://doi.org/10.1109/CLOUD.2016.0094
Masip-Bruin, X., Marn-Tordera, E., Tashakor, G., Jukan, A., Ren, G.J.: Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems. In: IEEE Wireless Communications, vol. 23, no. 5, pp. 120–128 ,IEEE(2016). https://doi.org/10.1109/MWC.2016.7721750
Souza, V.B., Masip-Bruin, X., Marin-Tordera, E., Ramirez, W., Sanchez, S.: Towards distributed service allocation in fog-to-cloud (F2C) scenarios. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6, IEEE, Washington, DC (2016). https://doi.org/10.1109/GLOCOM.2016.7842341
Narendra, N.C., Koorapati, K., Ujja, V.: Towards cloud-based decentralized storage for internet of things data. In: IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), pp. 160–168, IEEE, Bangalore (2015). https://doi.org/10.1109/CCEM.2015.9
Malandrino, F., Kirkpatrick, S., Chiasserini, C.F. : How close to the edge? delay/utilization trends in MEC. In: Proceedings of the ACM Workshop on Cloud-Assisted Networking, pp. 37–42, ACM, CA, USA (2016)
Hu, P., Ning, H., Qiu, T., Zhang, Y., Luo, X.: Fog computing based face identification and resolution scheme in internet of things. In: IEEE Transactions on Industrial Informatics, vol. 13, no. 4, pp. 1910–1920 , IEEE (2017). https://doi.org/10.1109/TII.2016.2607178
Chen, N., Chen, Y., You, Y., Ling, H., Liang, P., Zimmermann, R.: Dynamic urban surveillance video stream processing using fog computing. In: 2nd IEEE International Conference on Multimedia Big Data (BigMM), pp. 105–112, IEEE, Taipei (2016). https://doi.org/10.1109/BigMM.2016.53
Brogi, A., Stefano, F.: QoS-aware deployment of IoT applications through the Fog. In: IEEE Internet of Things Journal, vol. 4, no. 5, pp. 1185–1192, IEEE (2017). https://doi.org/10.1109/JIOT.2017.2701408
Sarkar, S., Misra, S.: Theoretical modelling of fog computing: a green computing paradigm to support IoT applications. In: IET Networks, vol. 5, no. 2, pp. 23–29, IEEE (2016). https://doi.org/10.1049/iet-net.2015.0034
Luan, T.H., Gao, L., Li, Z., Xiang, Y., Wei, G., Sun, L.: Fog computing: focusing on mobile users at the edge (2015). In: arXiv preprint arXiv:1502.01815
Hong, K., Lillethun, D., Ramachandran, U., Ottenwlder, B., Koldehofe, B.: Mobile fog: a programming model for large-scale applications on the internet of things. In: SIGCOMM workshop on Mobile cloud computing, pp. 15–20, ACM , Hong Kong, China (2013). https://doi.org/10.1145/2491266.2491270
Acknowledgements
This research was supported by Media Lab Asia (Visvesvaraya Ph.D. Scheme for Electronics and IT, Project Code-CSVSE) under the department of MeitY, Government of India and carried out at Cloud Computing Research Laboratory, Department of CSE, National Institute of Technology Rourkela, India.
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Maiti, P., Shukla, J., Sahoo, B., Turuk, A.K. (2019). Mathematical Modeling of QoS-Aware Fog Computing Architecture for IoT Services. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 814. Springer, Singapore. https://doi.org/10.1007/978-981-13-1501-5_2
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