Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context information and adapting systems behavior accordingly. Several context models have been defined and various context-aware middleware has been developed in order to simplify the development of context-aware applications. Unfortunately, the development of an application by using these middleware products introduces several technical details in the application. These technical details are specific to a given middleware and reduce the possibility of reusing the application on other middleware. In this paper, we propose an MDD (Model Driven Development) approach that makes it possible to design context-aware applications independently of the platform. This approach is based on several phases that approach step by step the context platform and allow designers to automatically map their models to several platforms through the definition of automatic and modular transformations. To be able to apply this approach we define a new UML profile for context-aware applications, that we use to explore our approach.

A model transformation can be decomposed into a sequence of subtransformations, i.e. a transformation chain, each addressing a limited set of concerns. However, with current transformation technologies it is hard to (re)use and compose subtransformations without being very familiar with their implementation details. Furthermore, the difficulty of combining different transformation technologies often thwarts choosing the most appropriate technology for each subtransformation. In this paper we propose a model-based approach to reuse and compose subtransformations in a technology-independent fashion. This is accomplished by developing a unified representation of transformations and facilitating detailed transformation specifications. We have implemented our approach in a tool called UniTI, which also provides a transformation chain editor. We have evaluated our approach by comparing it to alternative approaches.

Abstract-The expansion of wireless communication and mobile hand-held devices is affecting how software deployment is being performed. Deployed applications have to be suited to the users requirements, to the resources of his terminal and to the surrounding environment. In this paper, we define a methodology which enables classical deployment tools provided by componentbased middlewares to be adaptive. This methodology was experimentally tested and evaluated.

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The promise of disparate features envisioned by the 3GPP for 5G, such as offering enhanced Mobile Broadband connectivity while providing massive Machine Type Communications likely with very low data rates and maintaining Ultra Reliable Low Latency Communications requirements, create a very challenging environment for protecting the 5G networks themselves and associated assets. To overcome such complexity, future 5G networks must employ a very high degree of network and service management automation, which is a security challenge by itself as well as an opportunity for smarter and more efficient security functions. In this paper, we present the smart, trustworthy and liable 5G security platform being designed and developed in the INSPIRE-5Gplus 1 project. This platform takes advantage of new techniques such as Machine Learning (ML), Artificial Intelligence (AI), Distributed Ledger Technologies (DLT), network softwarization and Trusted Execution Environment (TEE) for closed-loop and end-to-end security management following a 1 https://www.inspire-5gplus.eu Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).