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Autonomic resilience of distributed IoT applications in the Fog

Umar Ibn Zaid Ozeer 1, 2, 3 
2 POLARIS - Performance analysis and optimization of LARge Infrastructures and Systems
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
3 CONVECS - Construction of verified concurrent systems
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Recent computing trends have been advocating for more distributed paradigms, namelyFog computing, which extends the capacities of the Cloud at the edge of the network, thatis close to end devices and end users in the physical world. The Fog is a key enabler of theInternet of Things (IoT) applications as it resolves some of the needs that the Cloud failsto provide such as low network latencies, privacy, QoS, and geographical requirements. Forthis reason, the Fog has become increasingly popular and finds application in many fieldssuch as smart homes and cities, agriculture, healthcare, transportation, etc.The Fog, however, is unstable because it is constituted of billions of heterogeneous devicesin a dynamic ecosystem. IoT devices may regularly fail because of bulk production andcheap design. Moreover, the Fog-IoT ecosystem is cyber-physical and thus devices aresubjected to external physical world conditions which increase the occurrence of failures.When failures occur in such an ecosystem, the resulting inconsistencies in the applicationaffect the physical world by inducing hazardous and costly situations.In this Thesis, we propose an end-to-end autonomic failure management approach for IoTapplications deployed in the Fog. The approach manages IoT applications and is composedof four functional steps: (i) state saving, (ii) monitoring, (iii) failure notification,and (iv) recovery. Each step is a collection of similar roles and is implemented, taking intoaccount the specificities of the ecosystem (e.g., heterogeneity, resource limitations). Statesaving aims at saving data concerning the state of the managed application. These includeruntime parameters and the data in the volatile memory, as well as messages exchangedand functions executed by the application. Monitoring aims at observing and reportinginformation on the lifecycle of the application. When a failure is detected, failure notificationsare propagated to the part of the application which is affected by that failure.The propagation of failure notifications aims at limiting the impact of the failure and providinga partial service. In order to recover from a failure, the application is reconfigured and thedata saved during the state saving step are used to restore a cyber-physical consistent stateof the application. Cyber-physical consistency aims at maintaining a consistent behaviourof the application with respect to the physical world, as well as avoiding dangerous andcostly circumstances.The approach was validated using model checking techniques to verify important correctnessproperties. It was then implemented as a framework called F3ARIoT. This frameworkwas evaluated on a smart home application. The results showed the feasibility of deployingF3ARIoT on real Fog-IoT applications as well as its good performances in regards to enduser experience.
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Umar Ibn Zaid Ozeer. Autonomic resilience of distributed IoT applications in the Fog. Databases [cs.DB]. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAM054⟩. ⟨tel-02570825⟩

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