New Students

Nikolaos Georgantas

Research Scientist + 33 (0)1 80 49 41 68 nikolaos . georgantas @ inria . fr

Brief bio

I am Research Scientist at Inria Paris and I lead the MiMove team.
I was before with the ARLES team, predecessor of MiMove. I was co-founder of Ambientic, a spin-off based on ARLES’ research that developed mobile collaborative applications.
I hold a Habilitation Degree in Computer Science from UPMC/Sorbonne University and a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens.

Research interests

Software engineering for distributed systems, middleware, mobile computing, semantic web, edge computing. I am particularly interested in interoperability, QoS analysis and resource management in the heterogeneous Internet of Things.

Current research

Items (1) to (5) below summarize our latest results in the Emergent system composition and adaptation research theme of MiMove. Item (6) further relates to the Mobile and social crowdsensing research theme.

  1. Automated synthesis of mediators for middleware-layer protocol interoperability in the IoT. We introduce a solution for the automated synthesis of protocol mediators, which can interconnect heterogeneous Things across the high fragmentation barrier in the IoT systems landscape. Our systematic approach relies on the Data eXchange (DeX) API & connector model, which comprehensively abstracts existing and potentially future IoT middleware protocols.
  2. Performance analysis of the middleware overlay infrastructure of mobile Things. In this work, we make use of the DeX connector model for functional interoperability in the IoT. Nevertheless, to ensure QoS in IoT applications, it is also essential to leverage a QoS analysis methodology that takes into account the IoT protocol diversity. We introduce analyses based on a Timed Automata model for DeX interactions, which can unify various underlying IoT interactions. Extending the previous, we introduce more realistic models and analyses for IoT interactions based on Queueing Network Models.
  3. QoS-aware resource allocation for mobile IoT pub/sub systems. QoS-aware resource allocation for pub/sub systems is challenging, especially in face of mobile peers’ disconnections. After formulating the optimal resource allocation problem in mobile pub/sub systems, we introduce a model for the end-to-end response time, which relies on QNMs that represent cloud resources and peers’ disconnections. Based on this model, we propose a cost-effective resource allocation strategy.
  4. Experimentation as a service (EaaS) over semantically interoperable IoT testbeds. Infrastructures enabling experimental assessment of IoT solutions are scarce and typically bound to a specific application domain, thus not facilitating the testing of horizontal solutions. As partner of the EU H2020 FIESTA-IoT project, we contributed to a platform that supports EaaS over a federation of 11 IoT testbeds from heterogeneous application domains with over 10,000 IoT devices overall, which produce hundreds of thousands of observations per day. We focused particularly on the semantic interoperability solution among heterogeneous testbeds.
  5. Efficient scheduling of streaming operators for IoT edge analytics. To efficiently handle Data stream processing & analytics (DSPA) applications, the edge/fog computing paradigm is used to process data streams closer to their sources, thus reducing network usage and application response times. We propose SOO, a resource-aware and time-efficient heuristic that identifies a good placement for DSPA operators on the edge-fog-cloud architecture towards optimizing the trade-off between the computational and network resource usage.
    • Ongoing PhD thesis by Patient Ntumba
    • Publication: [hal]
    • NEW! Our paper “Efficient scheduling of streaming operators for IoT edge analytics” has been accepted at FMEC’21
  6. Interoperability across heterogeneous online social network services. Users are typically locked in their OSNSs, encountering restrictions about what they can do with their personal data, the people they can interact with and the information they get access to. We aim at overcoming such a limitation by enabling users to meet and interact beyond the boundary of their OSNSs, including reaching out to ”friends” of distinct closed OSNSs. We specifically introduce Universal Social Network Bus (USNB), which revisits the ”service bus” paradigm that enables interoperability across computing systems, to address the requirements of ”social interoperability”.

Academic professional activities

  • Associate editor of MDPI Sensors – Internet of Things.
  • Associate editor of the International Journal of Ambient Computing and Intelligence (IJACI).
  • TPC Member: The Web Conference, IEEE SMARTCOMP, ACM SAC, SOSE, WETICE.
  • Member of the PhD monitoring committee at Inria Paris [2012–18].
  • Member of the Inria PhD scholarship, Inria postdoc scholarship and Inria professor leave scholarship selection committees at Inria Paris [until 2016].
  • President [2021] and member [2018-2019] of the EDITE Doctoral School selection committee “Communications, Networks and Systems” for PhD fellowships.
  • Monitor for the ANR project INTEROP [2018].
  • Reviewer for the Leverhulme Trust Grant 2021 call for project proposals.
  • Reviewer for the Emergence 2021 call for project proposals, Sorbonne University Alliance.


  • Our paper “USNB: Enabling Universal Online Social Interactions” [hal] received the Best Paper Award at CIC’2017.
  • Our paper “QoS-Aware Resource Allocation for Mobile IoT Pub/Sub Systems” [hal] received the Best Paper Award at ICIOT’2018.


For my publications you may check at Google ScholarDBLP or the list below (HAL-Inria).