Abstract
The Internet of Things is a thriving paradigm that makes people’s lives easier. In the IoT, devices equipped with sensors and actuators communicate through standardized Internet protocols to reach common goals. In Smart Homes, for example, monitoring the current state of an environment, such as the room temperature, could lead to an automated triggering of actions, such as activating the heating system. Small IoT applications, e.g., in Smart Homes, are usually more easy to manage since they do not include a large amount of devices. However, in larger and more complex IoT environments, e.g., Smart Cities and Smart Factories, management and control become a tedious task, especially since IoT devices do not offer the robustness of traditional computer systems. In case of device failures, IoT applications could become unstable or even fail completely. To make matters even worse, faulty sensor measurements could lead to an undesired behavior of IoT applications, even though there are no obvious errors that are detectable by monitoring systems. Therefore, in this paper, we introduce a first approach that aims at improving IoT applications’ fault tolerance throughout their whole lifecycle by introducing feedback loops ranging from application modeling, to deployment and operation, until their retirement.
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References
Aceto, G., Botta, A., De Donato, W., Pescapè, A.: Cloud monitoring: a survey. Comput. Netw. 57(9), 2093–2115 (2013)
Brattstrom, M., Morreale, P.: Scalable agentless cloud network monitoring. In: Proceedings - 4th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2017 and 3rd IEEE International Conference of Scalable and Smart Cloud, SSC 2017, pp. 171–176 (2017)
Chakraborty, T., et al.: Fall-curve: a novel primitive for IoT Fault detection and isolation. In: SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems, pp. 95–107 (2018)
Chetan, S., Ranganathan, A., Campbell, R.: Towards fault tolerance pervasive computing. IEEE Technol. Soc. Mag. 24(1), 38–44 (2005)
Del Gaudio, D., Hirmer, P.: A lightweight messaging engine for decentralized data processing in the Internet of Things. SICS Softw.-Intens. Cyber-Phys. Syst. 35(i) (2019)
Del Gaudio, D., Hirmer, P.: Seamless integration of devices in industry 4.0 environments. Internet Things 12, 100321 (2020)
Del Gaudio, D., Reichel, M., Hirmer, P.: A life cycle method for device management in dynamic IoT environments. In: Proceedings of the 5th International Conference on Internet of Things, Big Data and Security (2020)
Défago, X., et al.: The phi accrual failure detector. In: RR IS-RR-2004-010, Japan Advanced Institute of Science and Technology, pp. 66–78 (2004)
Hirmer, P., Behringer, M.: FlexMash 2.0 – flexible modeling and execution of data mashups. In: Daniel, F., Gaedke, M. (eds.) RMC 2016. CCIS, vol. 696, pp. 10–29. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-53174-8_2
Hirmer, P., Breitenbücher, U., da Silva, A.C.F., Képes, K., Mitschang, B., Wieland, M.: Automating the provisioning and configuration of devices in the internet of things. Complex Syst. Informatics Model. Q. 9, 28–43 (2016)
Kodeswaran, P., Kokku, R., Sen, S., Srivatsa, M.: Idea: a system for efficient failure management in smart IoT environments. In: MobiSys 2016 - Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services, pp. 43–56 (2016)
Panda, M., Khilar, P.: Distributed byzantine fault detection technique in wireless sensor networks based on hypothesis testing. Comput. Electr. Eng. 48, 270–285 (2015)
Ranjan, R., et al.: The next grand challenges: integrating the internet of things and data science. IEEE Cloud Comput. 5(3), 12–26 (2018)
Seeger, J., Deshmukh, R.A., Sarafov, V., Broring, A.: Dynamic IoT choreographies. IEEE Pervasive Comput. 18(1), 19–27 (2019)
Sharma, A.B., Golubchik, L., Govindan, R.: Sensor faults: detection methods and prevalence in real-world datasets. ACM Trans. Sensor Netw. 6(3), 1–39 (2010)
Franco da Silva, A.C., Hirmer, P., Wieland, M., Mitschang, B.: SitRS XT-towards near real time situation recognition. J. Inf. Data Manage. 7(1), 4 (2016)
Su, P.H., Shih, C.S., Hsu, J.Y.J., Lin, K.J., Wang, Y.C.: Decentralized fault tolerance mechanism for intelligent IoT/M2M middleware. In: 2014 IEEE World Forum on Internet of Things, WF-IoT 2014, pp. 45–50 (2014)
Vermesan, O., Friess, P.: Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems. River Publishers, Aalborg (2013)
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Del Gaudio, D., Hirmer, P. (2021). Towards Feedback Loops in Model-Driven IoT Applications. In: Barzen, J. (eds) Service-Oriented Computing. SummerSOC 2021. Communications in Computer and Information Science, vol 1429. Springer, Cham. https://doi.org/10.1007/978-3-030-87568-8_6
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