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1November 1, 20202November 2, 20203November 3, 2020PhD defense of Bruno Donassolo: IoT Orchestration in the Fog
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November 4, 2020I am pleased to invite you to my thesis defense entitled: « IoT Orchestration in the Fog ». This thesis has been conducted in the context of the <I/O lab>, a joint lab between Inria and Orange Labs. The defense will be in English and will take place in the auditorium of the IMAG building (700 Avenue Centrale, 38401 Saint-Martin-d'Hères).
Video-conference link: https://meet.univ-grenoble-alpes.fr/b/bru-m9j-mfv
You are also invited to share a “pot” following the defense (if the sanitary conditions allow)
The members of jury are:
- Mme E. Veronica BELMEGA, Maître de conférences, Université CY Cergy Paris, Reviewer
- M. Adrien LEBRE, Professeur des Universités, IMT Atlantique, Reviewer
- M. Frédéric DEPREZ, Directeur de recherche, INRIA Grenoble Rhône-Alpes, Examiner
- Mme Nathalie MITTON, Directrice de recherche, Inria Lille-Nord Europe, Examiner
- M. Ola ANGELSMARK, Ingénieur de recherche, Ericsson Research, Examiner
- M. Arnaud LEGRAND, Directeur de recherche, CNRS, Supervisor
- M. Panayotis MERTIKOPOULOS, Chargé de recherche, CNRS, Co-supervisor
- Mme Ilhem FAJJARI, Ingénieur de recherche, Orange Labs, Co-supervisor
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 Fog infrastructure; 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, O-FSP and GO-FSP, 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 application requirements. 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.
Bâtiment IMAG (amphitheater)Saint-Martin-d'Hères, 38400France5November 5, 20206November 6, 20207November 7, 20208November 8, 20209November 9, 202010November 10, 202011November 11, 202012November 12, 202013November 13, 202014November 14, 202015November 15, 202016November 16, 202017November 17, 202018November 18, 202019November 19, 202020November 20, 202021November 21, 202022November 22, 202023November 23, 202024November 24, 202025November 25, 202026November 26, 202027November 27, 202028November 28, 202029November 29, 202030November 30, 2020December
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