"Designing systems that evolve and adapt automatically to changes in their environment."
My doctoral research at Université de Lille and Inria focuses on the self-adaptation of distributed systems in the cloud. I develop innovative approaches to enable microservices to dynamically adapt to load variations, failures and evolving business requirements.
Designing systems capable of modifying their behaviour in response to changes in their environment, without human intervention.
Optimising cloud deployments and dynamically managing resources to guarantee performance and resilience of applications.
Modelling and optimising adaptation processes with BPMN, integrating adaptability into enterprise workflows.
AdaptiFlow is a lightweight Java framework designed to enable microservice self-adaptation in real time. It implements the MAPE-K pattern (Monitor, Analyze, Plan, Execute – Knowledge) to allow cloud applications to automatically adapt to changes in their environment.
Adaptable TeaStore is a demo application based on TeaStore (a reference microservices benchmark) enhanced with AdaptiFlow's self-adaptation capabilities. It concretely illustrates how an e-commerce system can adapt automatically to traffic spikes.
My work has been presented at leading international workshops and conferences in the field of software engineering.
ZEMTSOP NDADJI B.A., Simon Bliudze, Clément Quinton.
Presentation of AdaptiFlow, a lightweight framework enabling the integration of self-adaptation capabilities into existing microservices architectures, evaluated on the TeaStore benchmark.
French national research institute for digital science and technology
Lille research centre, team specialising in distributed systems and software architecture.
Faculty of Science and Technology
PhD in Computer Science within the CRIStAL laboratory (Research Centre in Computer Science, Signal and Automation of Lille).
I am open to academic and industrial collaborations. Feel free to reach out to discuss joint projects or partnership opportunities.