Phd Position F/m Latency-driven Resources Placement
Il y a 7 mois
Le descriptif de l’offre ci-dessous est en Anglais_
**Type de contrat **:CDD
**Niveau de diplôme exigé **:Bac + 5 ou équivalent
**Fonction **:Doctorant
**A propos du centre ou de la direction fonctionnelle**:
The Inria Rennes - Bretagne Atlantique Centre is one of Inria's eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
**Mission confiée**:
Cloud computing and its three facets (IaaS, PaaS and SaaS) have become essential in today Internet Applications, offering many advantages such as scalability, elasticity or flexibility. With its different service models, the cloud still faces many issues prone to impact either the end-user (QoS), the provider (Cost) and the environment (Sustainability).
However, evaluating realistic large-scale fog infrastructure constitute a complex task given the cost of deployment and the absence of a realistic view of the real-world deployments. In an IoT context, geo-distributed fog infrastructures mostly rely on SDN approaches [5] that contribute to conceal the networking aspects such as the topology or the routing decisions[8]. In consequence, it appears that the impact of the elasticity of a fog solution is mainly evaluated on the data plane side [4].
The objective of this thesis is to study the optimization of resource placement in Fog-based IoT systems based on latency measurement, by evaluating the control plane cost of a change in the architecture. It will particularly address the problem of how to identify the origin of a latency issue, and based on this finding, propose an optimization that take into account the cost and elasticity of the control plane.
**References**:
[1] Dániel Géhberger, Dávid Balla, Markosz Maliosz, and Csaba Simon. Performance eval
- uation of low latency communication alternatives in a containerized cloud environment. In 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), pages 9-16, 2018.
[2] Devasena Inupakutika, Gerson Rodriguez, David Akopian, Palden Lama, Patricia Chalela, and Amelie G. Ramirez. On the performance of cloud-based mhealth ap
- plications: A methodology on measuring service response time and a case study. IEEE Access, 10:53208-53224, 2022.
[3] Zheng Li and Francisco Millar-Bilbao. Characterizing the cloud’s outbound network latency: An experimental and modeling study. In 2020 IEEE Cloud Summit, pages 172-173, 2020.
[4] Carla Mouradian, Diala Naboulsi, Sami Yangui, Roch H. Glitho, Monique J. Morrow, and Paul A. Polakos. A comprehensive survey on fog computing: State-of-the-art and research challenges. IEEE Communications Surveys and Tutorials, 20(1):416-464, 2018.
[5] Feyza Yildirim Okay and Suat Ozdemir. Routing in fog-enabled iot platforms: A survey and an sdn-based solution. IEEE Internet of Things Journal, 5(6):4871-4889, 2018.
[7] U. Tomer and P. Gandhi. An enhanced software framework for improving qos in iot. Engineering, Technology and Applied Science Research, 12(5):9172-9177, Oct. 2022
[8] Benjamin Warnke, Yuri Cotrado Sehgelmeble, Johann Mantler, Sven Groppe, and Ste
[9] Sami Yangui, Pradeep Ravindran, Ons Bibani, Roch H. Glitho, Nejib Ben Hadj
- Alouane, Monique J. Morrow, and Paul A. Polakos. A platform as-a-service for hy
- brid cloud/fog environments. In 2016 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), pages 1-7, 2016.
**Principales activités**:
- Explore the State-of-the-Art of the IoT/Fog Emulation/Simulation platform
- Integrate an IoT solution in a Fog architecture platform
- Propose a profile and a classification of latency issues
- Propose an innovative way to optimize a resource placement taking into account the latency metrics and the control plane capabilities
**Compétences**:
- A master degree in distributed systems and/or Cloud computing/Networking
- Good knowledge of distributed systems
- Good programming skills (e.g., C++ and Python)
- Basic knowledge of simulation
- Excellent communication and writing skills in English (Note that knowledge of French is appreciated but not required for this position)
- Knowledge of the following technologies is not mandatory but will be considered as a plus:
- Cloud resource scheduling
- Routing, Software Defined networks
- Revision control systems: git, svn
- Linux distribution: Debian, Ubuntu
**Avantages**:
- Subsidized meals
- Partial reimbursement of public transport costs
- Possibility of teleworking (90 days per year) and flexible organization of working hours
- Partial payment of insurance costs
**Rémunération**:
Monthly gross salary amounting to 2051 euros for the first and second years and 2158 euros for the third year
**Informations générales**:
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