Abstract
Complexity of IoT systems and tasks that are put before them require shifts in the way resources and service provisioning are managed. The concept of fog computing is introduced so as to enhance IoT systems scalability, reactivity, efficiency and privacy. In this paper we present fog computing solution with context aware decision-making procedures distributed between IoT cloud platform and IoT gateways. The solution performs decision-making for smart actuation, based on analysis of sensory data streams, and context informed fog computing resource and service provisioning management based on topology changes. The state-of-the-art mainly focuses either on smart actuation enabled through insightful data analysis and machine learning, or on managing fog system itself in order to improve performance and efficiency. Our solution showcases how one software framework can be used to achieve both. Proof of concept experiments executed on a fog computing testbed validate our solutions performance in improving resilience and responsiveness of the fog computing system in context of topology changes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Message Queuing Telemetry Transport: http://www.mqtt.org.
- 2.
FHEM: http://www.fhem.de.
- 3.
EnOcean: http://www.enocean.com.
- 4.
Mosquitto: http://www.mosquitto.org.
- 5.
Haystack: http://www.haystacktechnologies.com.
References
Da Xu, L., He, W., Li, S.: Internet of things in industries: a survey. IEEE Trans. Ind. Inf. 10, 2233–2243 (2014)
Sicari, S., Rizzardi, A., Grieco, L.A., Coen-Porisini, A.: Security, privacy and trust in Internet of Things: the road ahead. Comput. Netw. 76, 146–164 (2015)
Luan, T.H., Gao, L., Li, Z., Xiang, Y., Wei, G., Sun, L.: Fog computing: focusing on mobile users at the edge. arXiv preprint arXiv:1502.01815 (2015)
Ciccozzi, F., Spalazzese, R.: MDE4IoT: supporting the internet of things with model-driven engineering. In: International Symposium on Intelligent and Distributed Computing, pp. 67–76. Springer (2016)
Piette, F., Caval, C., Dinont, C., Seghrouchni, A.E.F., Taillibert, P.: A multi-agent approach for the deployment of distributed applications in smart environments. In: International Symposium on Intelligent and Distributed Computing, pp. 37–46. Springer (2016)
Burchard, J., Chemodanov, D., Gillis, J., Calyam, P.: Wireless mesh networking protocol for sustained throughput in edge computing. In: 2017 International Conference on Computing, Networking and Communications (ICNC), pp. 958–962. IEEE (2017)
Xu, Y., Mahendran, V., Radhakrishnan, S.: Towards SDN-based fog computing: Mqtt broker virtualization for effective and reliable delivery. In: 2016 8th International Conference on Communication Systems and Networks (COMSNETS), pp. 1–6. IEEE (2016)
Wagle, S.: Semantic data extraction over MQTT for IoTcentric wireless sensor networks. In: International Conference on Internet of Things and Applications (IOTA), pp. 227–232. IEEE (2016)
Tosic, M., Ikovic, O., Boskovic, D.: SDN based service provisioning management in smart buildings. In: 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 754–759. IEEE (2016)
Tosic, M., Ikovic, O., Boskovic, D.: Soft sensors in wireless networking as enablers for SDN based management of content delivery. In: 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 559–564. IEEE (2016)
Karagiannis, V., Chatzimisios, P., Vazquez-Gallego, F., Alonso-Zarate, J.: A survey on application layer protocols for the Internet of Things. Trans. IoT Cloud Comput. 3(1), 11–17 (2015)
Hakiri, A., Berthou, P., Gokhale, A., Abdellatif, S.: Publish/subscribe-enabled software defined networking for efficient and scalable iot communications. IEEE Commun. Mag. 53(9), 48–54 (2015)
Singh, M., Rajan, M., Shivraj, V., Balamuralidhar, P.: Secure MQTT for Internet of Things (iot). In: 2015 Fifth International Conference on Communication Systems and Network Technologies (CSNT), pp. 746–751. IEEE (2015)
Anders, A.: Enocean Wireless Systems—Range Planning Guide. EnOcean Gmbh (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Pešić, S., Tošić, M., Iković, O., Ivanović, M., Radovanović, M., Bošković, D. (2018). Context Aware Resource and Service Provisioning Management in Fog Computing Systems. In: Ivanović, M., Bădică, C., Dix, J., Jovanović, Z., Malgeri, M., Savić, M. (eds) Intelligent Distributed Computing XI. IDC 2017. Studies in Computational Intelligence, vol 737. Springer, Cham. https://doi.org/10.1007/978-3-319-66379-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-66379-1_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66378-4
Online ISBN: 978-3-319-66379-1
eBook Packages: EngineeringEngineering (R0)