Michael Mrissa

French National Centre for Scientific Research, Lutetia Parisorum, Île-de-France, France

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Publications (52)12.46 Total impact

  • Pierre DE VETTOR · Michael Mrissa · Djamal Benslimane
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    ABSTRACT: Organizations, companies and Web platforms hold large amounts of unused data. These data are trapped in separate data sources, locked up in legacy formats and only reachable through several different protocols, making usage difficult. It is therefore necessary to manage this multiplicity of data sources in order to build a solution able to combine this multi-origin data into a coherent smart data set. We define a meta-model and models to describe data source diversity in a flexible way. We therefore propose an adaptive architecture that generates data integration workflows at runtime. We evaluate our approach to offer scalability, responsiveness, and dynamic and transparent data source management. We apply our approach in a live scenario from a French company to show how it adapts to industrial needs and facilitates smart data production and reuse. This paper describes our models and strategies and presents our resource-oriented architecture.
    No preview · Article · Jun 2015
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    Pierre DE VETTOR · Michael Mrissa · Djamal Benslimane
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    ABSTRACT: Providing quality-aware techniques for reusing data available on the Web is a major concern for today's organizations. High quality data that offers higher added-value to the stakeholders is called smart data. Smart data can be obtained by combining data coming from diverse data sources on the Web such as Web APIs, SPARQL endpoints, Web pages and so on. Generating smart data involves complex data processing tasks, typically realized manually or in a static way in current organizations, with the help of statically configured workflows. In addition, despite the recent advances in this field, transfering large amounts of data to be processed still remains a tedious task due to unreliable transfer conditions or transfer rate/latency problems. In this paper, we propose an adaptive architecture to generate smart data, and focus on a solution to handle volume diversity during data processing. Our approach aims at maintaining good response time performance upon user request. It relies on the use of RESTful resources and remote code execution over temporary data storage where business data is cached. Each resource involved in data processing accesses the storage to process data on-site.
    Preview · Article · Jun 2015
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    Mehdi Terdjimi · Lionel Médini · Michael Mrissa

    Preview · Article · May 2015
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    ABSTRACT: The Web of Things extends the Internet of Things by leveraging Web-based languages and protocols to access and control each physical object. In this article, the authors summarize ongoing work promoting the concept of an avatar as a new virtual abstraction to extend physical objects on the Web. An avatar is an extensible and distributed runtime environment endowed with an autonomous behavior. Avatars rely on Web languages, protocols, and reason about semantic annotations to dynamically drive connected objects, exploit their capabilities, and expose user-understandable functionalities as Web services. Avatars are also able to collaborate together to achieve complex tasks.
    No preview · Article · Mar 2015 · IEEE Internet Computing
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    ABSTRACT: W3C Workshop on the Web of Things
    Preview · Article · Jun 2014
  • Michael Mrissa · Lionel Medini · Jean-Paul Jamont
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    ABSTRACT: As the number of connected objects increases, there is a need to offer rich user experience and facilitate communication between physical objects with Web-based solutions. Our work relies on the notion of avatar to extend an object on the Web. We herein propose a model for the avatar to expose functionalities based on the capabilities objects offer. We motivate our work with a temperature regulation scenario and we evaluate the applicability of our proposal with an implementation.
    No preview · Conference Paper · Jun 2014
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    ABSTRACT: Nowadays, the Web offers huge amounts of data sources for the benefit of the community. However, there is a lack of practical approach for converting and linking multi-origin data sources into one coherent smart data set. In this paper, we define a service-oriented architecture to attach explicit semantics to data, to solve heterogeneity issues, and to remove data inconsistencies in order to convert raw documents to quality Linked Data. We motivate the need for a service oriented architecture for smart data with a live scenario based on the Audience Labs company information system. We show how our service-oriented architecture adapts to the company needs and facilitates semantic annotation, data integration and exploitation of the resulting smart data.
    No preview · Conference Paper · Apr 2014
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    ABSTRACT: Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new privacy concerns that traditional privacy models do not handle. In addition, DaaS composition may reveal privacy-sensitive information. In this paper, we propose a formal privacy model in order to extend DaaS descriptions with privacy capabilities. The privacy model allows a service to define a privacy policy and a set of privacy requirements. We also propose a privacy-preserving DaaS composition approach allowing to verify the compatibility between privacy requirements and policies in DaaS composition. We propose a negotiation mechanism that makes it possible to dynamically reconcile the privacy capabilities of services when incompatibilities arise in a composition. We validate the applicability of our proposal through a prototype implementation and a set of experiments.
    No preview · Article · Apr 2014 · IEEE Transactions on Services Computing

  • No preview · Article · Jan 2014 · International Journal of Autonomous and Adaptive Communications Systems
  • J.-P. Jamont · L. Médini · M. Mrissa
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    ABSTRACT: This paper presents aMAS-oriented approach to enable emergence and execution of complex functionality among a fleet of heterogeneous connected objects. It relies on theWeb of Things paradigm, in which such objects communicate using Web standards. In order to homogenize the objects and extend their capabilities, our approach is based on agents that can be deployed either on objects or in the cloud. Such agents can embody the object behaviors and perform negotiation to achieve collaborative functionalities.
    No preview · Article · Jan 2014

  • No preview · Article · Sep 2013
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    ABSTRACT: The composition of data-as-a-service (DaaS) services is a powerful solution for building value-added applications on top of existing ones. However, privacy concerns are still among the key challenges that keep hampering DaaS composition. Indeed, services may follow different, conflicting privacy specifications with respect to the data they use and provide. In this paper, we propose an approach for the privacy-aware composition of DaaS services. Our approach allows us to specify privacy requirements and policies and verify the compatibility of services involved in a composition. We propose an adaptation protocol that makes it possible to reconcile the privacy specifications of services when incompatibilities arise in a composition. We validate the applicability of our proposal through a set of experiments.
    Full-text · Article · Sep 2013 · IEEE Systems Journal
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    ABSTRACT: Data services have almost become a standard way for data publishing and sharing on top of the Web. In this paper, we present a secure and privacy-preserving execution model for data services. Our model controls the information returned during service execution based on the identity of the data consumer and the purpose of the invocation. We implemented and evaluated the proposed model in the healthcare application domain. The obtained results are promising.
    Full-text · Conference Paper · Jun 2013
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    ABSTRACT: Service composition is a major advance service-oriented computing brings to enable the development of distributed applications. However, the distributed nature of services hampers their composition with data heterogeneity problems. In this paper, we address these problems with a decentralized Mediation-as-a-Service architecture that solves data inconsistencies occurring during the composition of business services. As a particular data heterogeneity, we focus on the data interpretation problem and introduce conflictual aspect mediation services and conflictual aspect ontologies to solve data interpretation inconsistencies. We demonstrate how our architecture enables decentralized publication and discovery of mediation services. We motivate our work with a concrete scenario and validate our proposal with experiments.
    No preview · Conference Paper · Jun 2013
  • Pierre De Vettor · Michael Mrissa · Carlos Pedrinaci
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    ABSTRACT: Background and Motivation. The past few years have seen important advances in the domain of Semantic Web Services (SWS), especially in data mediation. Most work in the area has focused on the semantic alignement of input/output concepts at design time, and on schema-level integration [1]. Correct communication is not guaranteed even when two services are connected to each other with compatible input/output concepts. Indeed, conceptually compatible data may not be usable when data representation and scaling conflicts occur. To address this problem, which we refered to as the contextual heterogeneity problem, we rely on the Minimal Service Model [2] and operate with Linked Services as SWS that offer explicit semantics. In this paper, we present our Mediation as a Service (MaaS) architecture and demonstrate its applicability with a running scenario and a prototype.
    No preview · Conference Paper · Sep 2012
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    ABSTRACT: Modern enterprises across all spectra are increasingly adopting SOA-based data integration architectures to rapidly respond to transient data business needs. In this chapter, the authors analyze a new class of enterprise data integration application, called Data Mashup, in which data services are composed on the fly to answer new data business demands. The chapter reviews the different approaches to data mashup, discusses their limitations, and identifies the main requirements to data mashup. The authors next propose a declarative data mashup approach addressing the identified requirements. Finally, the chapter presents some research directions that must be followed in order for data mashup technology to mature.
    No preview · Article · Jan 2012
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    ABSTRACT: In this paper, we present a formal model for preserving privacy in Web services. We define a Web service-aware privacy model that deals with the privacy of input data, output data, and operation usage. We introduce a matching protocol that caters for partial and total privacy compatibility. We propose also a negotiation model to reconcile clients' requirements with providers' policies in case of incompatibility.
    No preview · Article · Jan 2012
  • Idir Amine Amarouche · Michael Mrissa · Zaia Alimazighi
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    ABSTRACT: In the domain of DaaS {DaaS: Data-as-a-Service or information-providing service), completing a query means calling many services which are heterogeneous and built independently from the context in which they will be used. This heterogeneity leads to several compatibility problems during DaaS composition. In order to solve them, we propose a semantic description model which allows context characterization. The proposed model enables data mediation in the composition for resolving the conflicts caused by heterogeneities between DaaSs. We rely on two-layered mediated ontology for deriving automatically DaaSs compositions that incorporate necessary mediation services. A preliminary evaluation has been performed based on our initial investigation leading to better improvement.
    No preview · Article · Nov 2011
  • [Show abstract] [Hide abstract]
    ABSTRACT: Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new privacy concerns that traditional privacy models do not handle since they only focus on the service interface without taking into account privacy constraints related to the data exchanged with a DaaS during its invocation. In addition, DaaSs compositions may reveal also privacy-sensitive information. In this paper we propose a privacy formal model in order to extend DaaS descriptions with privacy capabilities. The privacy model allows a service to define a privacy policy and a set of privacy requirements. We propose also a privacy-preserving DaaS composition approach allowing to verify the compatibility between privacy requirements and policies in DaaS composition. We validate the applicability of our proposal with some experiments.
    No preview · Conference Paper · Aug 2011
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    ABSTRACT: Data Mashup is a special class of mashup appli- cation that combines information on the fly from multiple data sources to respond to transient business needs. Data mashup is a difficult task that would require an important programming skill on the side of mashups' creators, and involves handling many challenging privacy and security concerns raised by data providers. This situation prevents non-expert users from mashing up data at large. In this paper, we present a declarative approach for mashing-up data. The approach allows data mashup creators to build data mashups without any program- ming involved. The approach builds the mashups automatically and takes into account the data's privacy concerns. We evaluate the efficiency of the approach via a thorough set of experiments. The results show that handling data privacy introduces only a negligible cost in the mashup building time. Keywords-Privacy, Data Mashup, DaaS Web Services.
    No preview · Conference Paper · Jul 2011

Publication Stats

291 Citations
12.46 Total Impact Points

Institutions

  • 2010-2015
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
  • 2009-2015
    • University of Lyon
      Lyons, Rhône-Alpes, France
  • 2004-2014
    • Claude Bernard University Lyon 1
      Villeurbanne, Rhône-Alpes, France
  • 2008-2009
    • University of Namur
      • PROJUCIT Research Center
      Namen, Walloon, Belgium
  • 2005
    • Université Bordeaux 1
      Talence, Aquitaine, France