2023Activity reportProject-TeamMIMOVE

3.1 Emergent mobile distributed systems

Uncertainty in the execution environment calls for designing mobile distributed systems that are able to run in a beforehand unknown, ever-changing context. Nevertheless, the complexity of such change cannot be tackled at system design-time. Emergent mobile distributed systems are systems which, due to their automated, dynamic, environment-dependent composition and execution, emerge in a possibly non-anticipated way and manifest emergent properties, i.e., both systems and their properties take their complete form only at runtime and may evolve afterwards. This contrasts with the typical software engineering process, where a system is finalized during its design phase. MiMove's research focuses on enabling the emergence of mobile distributed systems while assuring that their required properties are met. This objective builds upon pioneering research effort in the area of emergent middleware initiated by members of the team and collaborators 2, 4.

3.2 Large-scale mobile sensing and actuation

The extremely large scale and dynamicity expected in future mobile sensing and actuation systems lead to the clear need for algorithms and protocols for addressing the resulting challenges. More specifically, since connected devices will have the capability to sense physical phenomena, perform computations to arrive at decisions based on the sensed data, and drive actuation to change the environment, enabling proper coordination among them will be key to unlocking their true potential. Although similar challenges have been addressed in the domain of networked sensing, including by members of the team 8, the specific challenges arising from the extremely large scale of mobile devices – a great number of which will be attached to people, with uncontrolled mobility behavior – are expected to require a significant rethink in this domain. MiMove's research investigates techniques for efficient coordination of future mobile sensing and actuation systems with a special focus on their dependability.

3.3 Mobile social crowd-sensing

While mobile social sensing opens up the ability of sensing phenomena that may be costly or impossible to sense using embedded sensors (e.g., subjective crowdedness causing discomfort or joyfulness, as in a bus or in a concert) and leading to a feeling of being more socially involved for the citizens, there are unique consequent challenges. Specifically, MiMove's research focuses on the problems involved in the combination of the physically sensed data, which are quantitative and objective, with the mostly qualitative and subjective data arising from social sensing. Enabling the latter calls for introducing mechanisms for incentivising user participation and ensuring the privacy of user data, as well as running empirical studies for understanding the complex social behaviors involved. These objectives build upon previous research work by members of the team on mobile social ecosystems and privacy, as well as a number of efforts and collaborations in the domain of smart cities and transport that have resulted in novel mobile applications enabling empirical studies of social sensing systems.

4.1 Mobile urban systems for smarter cities

With the massive scale adoption of mobile devices and further expected significant growth in relation with the Internet of Things, mobile computing is impacting most – if not all – the ICT application domains. One such domain is the one of "smart cities". The smart city vision anticipates that the whole urban space, including buildings, power lines, gas lines, roadways, transport networks, and cell phones, can all be wired together and monitored. Detailed information about the functioning of the city then becomes available to both city dwellers and businesses, thus enabling better understanding and consequently management of the city's infrastructure and resources. This raises the prospect that cities will become more sustainable environments, ultimately enhancing the citizens' well being. There is the further promise of enabling radically new ways of living in, regulating, operating and managing cities, through the increasing active involvement of citizens by ways of crowd-sourcing/sensing and social networking.

Still, the vision of what smart cities should be about has been and keeps evolving at a fast pace in close concert with the latest technology trends. It is notably worth highlighting how mobile and social network use has reignited citizen engagement, thereby opening new perspectives for smart cities beyond data analytics that have been initially one of the core foci for smart cities technologies. Similarly, open data programs foster the engagement of citizens in the city operation and overall contribute to make our cities more sustainable. The unprecedented democratization of urban data fueled by open data channels, social networks and crowd sourcing enables not only the monitoring of the activities of the city but also the assessment of their nuisances based on their impact on the citizens, thereby prompting social and political actions. However, the comprehensive integration of urban data sources for the sake of sustainability remains largely unexplored. This is an application domain that we focus on, further leveraging our research on emergent mobile distributed systems, large-scale mobile sensing & actuation, and mobile social crowd-sensing.

In particular, we concentrate on the following specialized applications:

• Democratization of urban data for healthy cities. We integrate the various urban data sources, especially by way of crowd-Xing, to better understand city nuisances. This goes from raw pollution sensing (e.g., sensing noise) to the sensing of its impact on citizens (e.g., how people react to urban noise and how this affects their health).
• Social applications. Mobile applications are being considered by sociologists as a major vehicle to actively involve citizens and thereby prompt them to become activists. We study such a vehicle from the ICT perspective and in particular elicit relevant middleware solutions to ease the development of such “civic apps".

5.1 New software

6.1 Collaborative systems for large-scale online citizen participation

Participants: William Aboucaya, Rafael Angarita, Valérie Issarny, Nikolaos Georgantas.

Online participatory platforms have become a common means to involve citizens in public decision-making, allowing for participation at a larger scale than their offline counterparts, both in the number of participants and in the geographical distribution. However, the term “participatory platform” covers a wide range of extremely different systems, implying differences in the problems encountered by platforms administrators and contributors. More precisely, such platforms face specific issues when they aim at allowing citizens to collaborate to produce common contributions or when the number of contributors involved becomes particularly high. This Ph.D. research aims at identifying issues in contemporary online citizen participation platforms and proposing technical means to create participatory platforms more collaborative and suitable for large-scale online participation. My thesis is mainly based on previous works produced in the Computer-Supported Collaborative Work (CSCW) and Natural Language Processing (NLP) fields of computer science research. The contributions of this thesis are: the identification of flaws in a specific citizen participation platform and the recommendation of platform design-oriented alternatives to solve them; the representation of a participatory platform as a knowledge graph and its enrichment using a preexisting external knowledge base; the identification of the different objectives motivating the creation of participatory platforms and of the different types of features for interaction implemented based on a series of interviews; the conception and implementation of a Natural Language Inference-based method to reduce issues faced by online citizen participation when the number of contributors becomes particularly high.

6.2 Building Online Public Consultation Knowledge Graphs

Participants: William Aboucaya, Sonia Guehis, Rafael Angarita.

Online consultation platforms have improved the possibilities for citizens to have an input on public decision making. However, and especially at large scale, identification of the topics discussed and entities evoked has been identified as difficult for both citizens and platform administrators. In this paper, we leverage topic modeling, Named Entity Recognition and Linking and Semantic Textual Similarity to build a knowledge graph representing the different contributions to the République Numérique online citizen consultation in French language. The generated graph links the different proposals to topics identified in the consultation and to relevant DBpedia resources. The model proposed for representation of citizen consultations as knowledge graphs simplifies the retrieval of proposals focused on specific topics or mentioning a given entity. It also allows us to improve contextualization of important words in proposals by linking them to short definitions extracted from Wikipedia.

6.3 AutoClass: AutoML for Data Stream Classification

Participants: Maroua Bahri, Nikolaos Georgantas.

Automated Machine Learning (autoML) is a novel topic that aims to tackle the parameter configuration issue using automatic monitoring models and comprises different machine learning tasks, such as feature selection, model selection, and hyper-parameter tuning. It makes easier use of algorithms for non-ML experts as well as ML experts by automating tasks that rely on expert domain knowledge. Nevertheless, autoML is in its infancy stage and not well explored yet in the offline and stream settings. In this paper, we propose automated Classification (auto-Class) method for automated algorithm selection and configuration for data stream classification. AutoClass consists of training an ensemble of different tuned configurations and selecting the best-performing configuration to do the prediction. We present experiments performed on a diverse set of real and artificial datasets and show how our proposed approach can outperform the performance of competitive state-of-the-art ensemble and single-based methods.

6.4 A Service Bus Architecture for Highly Distributed and Dynamic IoT Environments

Participants: Marco Garofalo, Zakaria Benomar, Francesco Longo, Giovanni Merlino, Nikolaos Georgantas, Antonio Puliafito.

The Internet of Things (IoT) impacts numerous application domains nowadays, including smart cities, smart factories, and intelligent transportation, to name a few. However, leveraging the IoT within software applications raises tremendous challenges from the networking up to the application layer due to the ultra-large-scale, extreme heterogeneity, and dynamics of IoT. This paper explores how the service-oriented architecture paradigm may be revisited to address communication challenges posed by the IoT for the development of distributed applications in the IoT realm.

6.5 FaaS for IoT: Evolving Serverless towards Deviceless in I/O clouds

Participants: Giovanni Merlino, Giuseppe Tricomi, Luca D’Agati, Zakaria Benomar, Francesco Longo, Antonio Puliafito.

The burgeoning paradigms of Fog and Edge computing propose delegating Cloud-related tasks to the network's periphery, thus placing computational resources closer to data producers. This shift promises to boost the performance of IoT-based services, providing swift response times while conserving bandwidth. Despite their potential, the current Edge/Fog computing platforms must provide the required flexibility for dynamic service orchestration within a data-oriented context. Addressing this gap, the Function-as-a-Service (FaaS) model emerges as an exceptional strategy for Edge/Fog deployments. Its ability to manage an ever-expanding ecosystem of devices with remarkable flexibility and efficiency holds considerable promise. This paper articulates a novel approach to enhancing the adaptability of IoT Edge/Fog deployments. We propose an innovative extension to OpenStack, an open-source Cloud management system, which pushes its functionality towards the network Edge. Our approach empowers OpenStack to facilitate FaaS services within a distributed IoT infrastructure, thus infusing unprecedented adaptability and efficiency into the Edge/Fog computing paradigms.

7.1 European initiatives

7.2 National initiatives

8.1 Promoting scientific activities

8.2 Teaching - Supervision - Juries

• Maroua Bahri , "Databases", for 2nd year engineering students (12h, 107 students), lecturer at Télécom Paris.
• Maroua Bahri , "Data stream mining", for 2nd year master students (3h), lecturer at Télécom Paris.
• Maroua Bahri , "Data stream mining", for specialized master students (14h, 6 students), lecturer at Université Paris-Cité.

9.1 Major publications

• 1 articleR.Rafael Angarita, B.Bruno Lefèvre, S.Shohreh Ahvar, E.Ehsan Ahvar, N.Nikolaos Georgantas and V.Valerie Issarny. Universal Social Network Bus: Towards the Federation of Heterogeneous Online Social Network Services.ACM Transactions on Internet Technology2019HALDOI
• 2 articleA.Amel Bennaceur and V.Valérie Issarny. Automated Synthesis of Mediators to Support Component Interoperability.IEEE Transactions on Software Engineering2015, 22HALback to text
• 3 articleB.Benjamin Billet and V.Valérie Issarny. Spinel: An Opportunistic Proxy for Connecting Sensors to the Internet of Things.ACM Transactions on Internet Technology172March 2017, 1 - 21HALDOI
• 4 inproceedingsG.Gordon Blair, A.Amel Bennaceur, N.Nikolaos Georgantas, P.Paul Grace, V.Valérie Issarny, V.Vatsala Nundloll and M.Massimo Paolucci. The Role of Ontologies in Emergent Middleware: Supporting Interoperability in Complex Distributed Systems.Big Ideas track of ACM/IFIP/USENIX 12th International Middleware ConferenceLisbon, Portugal2011, URL: http://hal.inria.fr/inria-00629059/enback to text
• 5 articleG.Georgios Bouloukakis, N.Nikolaos Georgantas, P.Patient Ntumba and V.Valérie Issarny. Automated synthesis of mediators for middleware-layer protocol interoperability in the IoT.Future Generation Computer Systems101December 2019, 1271-1294HALDOI
• 6 articleM.Mauro Caporuscio, P.-G.Pierre-Guillaume Raverdy and V.Valérie Issarny. ubiSOAP: A Service Oriented Middleware for Ubiquitous Networking.IEEE Transactions on Services Computing992012, URL: http://hal.inria.fr/inria-00519577DOI
• 7 inproceedingsY.Yifan Du, F.Francoise Sailhan and V.Valerie Issarny. Let Opportunistic Crowdsensors Work Together for Resource-efficient, Quality-aware Observations.PerCom 2020: IEEE International Conference on Pervasive Computing and CommunicationsAustin / Virtual, United StatesMarch 2020HALDOI
• 8 articleS.Sara Hachem, A.Animesh Pathak and V.Valérie Issarny. Service-Oriented Middleware for Large-Scale Mobile Participatory Sensing.Pervasive and Mobile Computing2014, URL: http://hal.inria.fr/hal-00872407back to text

9.2 Publications of the year