2 research outputs found
Composition adaptative de services pour lâInternet des objets
L'internet des objets (IoT) est une technologie Ă©mergente, qui reprĂ©sente lâintĂ©gration ou la fusion de l'espace d'information et de l'espace physique. Au fil du temps, lâIoT est devenu de plus en plus populaire dans plusieurs endroits. Afin de rĂ©pondre Ă la demande compliquĂ©e des utilisateurs, la plupart des appareils IoT ne fonctionnent pas seuls, une composition de services multiples doit ĂȘtre effectuĂ©e et elle est dĂ©finie comme la composition de services. Pour des raisons de conductivitĂ©s, pannes, batterie, charge et autres, la disponibilitĂ© des services IoT est imprĂ©visible. Cette imprĂ©visibilitĂ© de la disponibilitĂ© et l'Ă©volution dynamique des besoins des utilisateurs, font que la composition du service doit gĂ©rer cette dynamique et s'adapter Ă de nouvelles configurations non prĂ©vues Ă la conception. La composition adaptative des services consiste Ă modifier le systĂšme pour lui permettre de se comporter correctement dans diffĂ©rents contextes afin d'assurer la disponibilitĂ© des services offerts, afin de rĂ©pondre Ă une situation non prĂ©vue lors de la phase de conception. De ce fait, notre objectif est de proposer une mĂ©thode de composition de services IoT adaptative et sensible au contexte afin de satisfaire les besoins des
utilisateurs.
Dans notre travail, nous considĂ©rons que la croissance de l'Internet des Objets (IoT) implique la disponibilitĂ© d'un trĂšs grand nombre de services qui peuvent ĂȘtre similaires ou identiques, la gestion de la QualitĂ© de Service (QoS) permet de diffĂ©rencier un service d'un autre. La composition de services offre la possibilitĂ© d'effectuer des activitĂ©s complexes en
combinant les fonctionnalités de plusieurs services au sein d'un seul processus. TrÚs peu de travaux ont présenté une solution de composition de services adaptative gérant les attributs de QoS, en plus dans le domaine de la santé, qui est l'un des plus difficiles et délicats car il concerne la précieuse vie humaine. Dans cette thÚse, nous présenterons une approche de
composition de services adaptative sensible aux QoS basée sur un algorithme génétique multipopulation dans un environnement Fog-IoT. Notre algorithme P-MPGA implémente une méthode de sélection intelligente qui nous permet de sélectionner le bon service. En outre, PMPGA implémente un systÚme de surveillance qui surveille les services pour gérer le
changement dynamique des environnements IoT. Les résultats expérimentaux montrent les excellents résultats du P-MPGA en termes de temps d'exécution, de valeurs de fitness moyennes et de rapport temps d'exécution / meilleure valeur de fitness malgré l'augmentation de la population. P-MPGA peut rapidement obtenir un service composite satisfaisant les besoins de
QoS de l'utilisateur, ce qui le rend adapté à un environnement IoT à grande échelle
Trust Modelling and Management for Collaborative and Composite Applications in the Internet of Things
A future Internet of Things (IoT) will feature a service-oriented architecture consisting of lightweight computing platforms offering individual, loosely coupled microservices. Often, an end-user will request a bespoke service that will require a composition of two or more microservices offered by different service providers. This architecture offers several advantages that are key to the realisation of the IoT vision, such as modularity, increased reliability and technology heterogeneity and interoperability. As a result, the adoption of this architecture in the IoT is being extensively researched. However, the underlying complexities of service compositions and the increased security risks inherent in such a massively decentralised and distributed architecture remain key problems. The use of trust management to secure the IoT remains a current and interesting topic; its potential as a basis for service compositions has not been thoroughly researched, however.
Security through trust presents a viable solution for threat management in the IoT. Currently, a well-defined trust management framework for collaborative and composite applications on an IoT platform does not exist. In this thesis, a collaborative application refers to the one that enables collaboration among its users to jointly complete certain tasks, whereas a composite application is the one composed of multiple existing services to deliver integrated functionalities. To estimate reliably the trust values of nodes within a system, the trust should be measured by suitable parameters that are based on the nodesâ functional properties in the application context. Existing models do not clearly outline the parametrisation of trust. Also, trust decay is inadequately modelled in many current models. In addition, trust recommendations are usually inaccurately weighted with respect to previous trust, thereby increasing the effect of bad recommendations.
This thesis focuses on providing solutions to the twin issues of trust-based security and trust-based compositions for the IoT. First, a new model, CTRUST, is proposed to resolve the above stated shortcomings of previous trust models. In CTRUST, trust is accurately parametrised while recommendations are evaluated through belief functions. The effects of trust decay and maturity on the trust evaluation process were studied. Each trust component is neatly modelled by appropriate mathematical functions. CTRUST was implemented in a collaborative download application and its performance was evaluated based on the utility derived and its trust accuracy, convergence, and resiliency. The results indicate that IoT collaborative applications based on CTRUST gain a significant improvement in performance, in terms of efficiency and security.
In a second study, the trust properties of service compositions in the IoT, along with the effect of the service architecture on the security and performance of the composed service, are investigated. Novel approaches are considered in relation to trust decomposition and composition, respectively. Relevant trust evaluation functions are derived to guide the compositions, which are used to extend CTRUST into a new trust model, SC-TRUST. SC-TRUST is implemented in a suitable simulation and the results are evaluated. The model reliably guides service compositions while ensuring utility to the end-user. Overall, the analyses and evaluations support the conclusion that the trust models are effective in terms of performance gain and security. The models are scalable and lightweight such that they could be deployed to secure applications and drive meaningful services and collaborations in the envisaged IoT and Web 3.0 sphere