Abstract
In the application of the Internet of Things (IoT), all data is stored in the cloud, that causes the long distance of the network logic between the cloud and the device side or client side, this might leads to network delay or slow response time. A challenging issue is how to increase the speed of response time in the cloud computing and the IoT environment for clients. In this paper, we propose a complete set of Edge Computing architecture. There are three layers, namely, Cloud side, Edge side, and Device side. Cloud side mainly deals with more complicated operations and data backup. For overall system infrastructure, we deployed Kubernetes cluster on an OpenStack platform. Edge side optimizes the service of cloud computing systems by performing data processing at the edge of the network. In this phase, we created an Edge Gateway to increase the capacity and performance and reduce the communications bandwidth needed between sensors and the central data.
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References
Cicirelli F, Guerrieri A, Spezzano G, Vinci A (2017) An edge-based platform for dynamic smart city applications. Future Gener Comput Syst
Toffetti G, Brunner S, Blöchlinger M, Spillner J, Bohnert TM (2017) Self-managing cloud-native applications: design, implementation, and experience. Future Gener Comput Syst 72:165–179
Yang C-T, Chan Y-W, Liu J-C, Lou B-S (2017) An implementation of cloud-based platform with r packages for spatiotemporal analysis of air pollution. J Supercomput, pp 1–22
Liu P-Y, Tsan Y-T, Chan Y-W, Chan W-C, Shi Z-Y, Yang C-T, Lou B-S (2018) Associations of pm2. 5 and aspergillosis: ambient fine particulate air pollution and population-based big data linkage analyses. J Ambient Intell Humanized Comput, pp 1–11
Yang C-T, Chen S-T, Chang C-H, Den W, Wang Y-T, Kristiani E (2018) Implementation of an intelligent indoor environmental monitoring and management system in cloud. Future Gener Comput Syst
Yang C-T, Chen S-T, Chang C-H, Den W, Wu C-C (2018) Implementation of an environmental quality and harmful gases monitoring system in cloud. J Med Biol Eng, pp 1–14
Kozhirbayev Z, Richard OS (2017) A performance comparison of container-based technologies for the cloud. Future Gener Comput Syst 68:175–182
Yang C-T, Chen C-J, Chen T-Y (2017) Implementation of ceph storage with big data for performance comparison. Lecture notes in electrical engineering, 424:625–633
Mikula A, Adamov D, Adam M, Chudoba J, Vec J (2016) Grid site monitoring and log processing using elk, 1787:54–61
Shu P, Gu R, Dong Q, Yuan C, Huang Y (2016) Accelerating big data applications on tiered storage system with various eviction policies, pp 1350–1357
Giaffreda R, Dupont C, Capra L (2017) Edge computing in iot context: horizontal and vertical linux container migration. In: 2017 Global internet of things summit (GIoTS). IEEE, pp 1–4
Openstack (2017). https://www.openstack.org/
Yamato Y (2016) Proposal of optimum application deployment technology for heterogeneous iaas cloud, pp 34–37
Netto HV, Lung LC, Correia M, Luiz AF, de Souza LMS (2017) State machine replication in containers managed by kubernetes. J Syst Archit 73:53–59
Kubernetes (2017) https://kubernetes.io/
Acknowledgements
This work was supported in part by the Ministry of Science and Technology, Taiwan R.O.C., under grants number MOST 104-2221-E-029-010-MY3 and MOST 106-3114-E-029-003.
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Kristiani, E., Yang, CT., Wang, Y.T., Huang, CY. (2019). Implementation of an Edge Computing Architecture Using OpenStack and Kubernetes. In: Kim, K., Baek, N. (eds) Information Science and Applications 2018. ICISA 2018. Lecture Notes in Electrical Engineering, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-13-1056-0_66
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DOI: https://doi.org/10.1007/978-981-13-1056-0_66
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