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IoT Orchestration in the Fog

Abstract : Internet of Things (IoT) continues its evolution, causing a drastically growth of traffic and processing demands. Consequently, 5G players are urged to rethink their infrastructures. In this context, Fog computing bridges the gap between Cloud and edge devices, providing nearby devices with analytics and data storage capabilities, increasing considerably the capacity of the infrastructure.However, the Fog raises several challenges which decelerate its adoption. Among them, the orchestration is crucial, handling the life-cycle management of IoT applications. In this thesis, we are mainly interested in: i) the provisioning problem, i.e., placing multi-component IoT applications on the heterogeneous Foginfrastructure; and ii) the reconfiguration problem, i.e., how to dynamically adapt the placement of applications, depending on application needs and evolution of resource usage.To perform the orchestration studies, we first propose FITOR, an orchestration system for IoT applications in the Fog environment. This solution addresses the lack of practical Fog solutions, creating a realistic environment on which we can evaluate the orchestration proposals.We study the Fog service provisioning issue in this practical environment. In this regard, we propose two novel strategies, OFSP and GOFSP, which optimize the placement of IoT application components while coping with their strict performance requirements. To do so, we first propose an Integer Linear Programming formulation for the IoT application provisioning problem. Based on extensive experiments, the results obtained show that the proposed strategies are able to decrease the provisioning cost while meeting the applicationrequirements.Finally, we tackle the reconfiguration problem, proposing and evaluating a series of reconfiguration algorithms, based on both online scheduling and online learning approaches. Through an extensive set of experiments, we demonstrate that the performance strongly depends on the quality and availability of information from Fog infrastructure and IoT applications. In addition, we show that a reactive and greedy strategy can overcome the performance of state-of-the-art online learning algorithms, as long as the strategy has access to a little extra information.
Keywords : Iot Fog Optimization
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Contributor : Abes Star :  Contact
Submitted on : Wednesday, February 3, 2021 - 12:57:26 PM
Last modification on : Monday, April 12, 2021 - 6:41:07 PM


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  • HAL Id : tel-03130144, version 1


Bruno de Moura Donassolo. IoT Orchestration in the Fog. Emerging Technologies [cs.ET]. Université Grenoble Alpes [2020-..], 2020. English. ⟨NNT : 2020GRALM051⟩. ⟨tel-03130144⟩



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