CASCADAS

The overall goal of CASCADAS is identifying, developing, and evaluating architectures and solutions based on a general-purpose component model for autonomic communication services; specifically in such context autonomic service components autonomously achieve self-organization and self-adaptation towards the provision of adaptive and situated communication-intensive services. In other words, the project is driven by the ambition of identifying a fundamental, uniform abstraction for situated and autonomic communication entities, at all levels of granularity. This abstraction is called an ACE (Autonomic Communication Element), and it represents the cornerstone of the component model, in which the four driving scientific project principles (situation awareness, semantic self-organisation, self-similarity, autonomic component-ware) will properly converge.

The study of ACEs is also the basis for achieving a number of other ambitious objectives that will be explicitly tackled by the project. These objectives derives from the need of providing ACEs with the necessary support of algorithms, knowledge, tools and infrastructures (to be realized again as sorts of ACE based middle-services) to make ACEs a practical and trust-worth paradigm. On the other hand, they derives from the willingness to attack and explore some crucial aspects related to the complexity and dynamism challenges that stand in situated and autonomic communication vision. These main research objectives, each conceived in terms of a separated scientific WP and each aimed at delivering specific methodological and software tools, include:

• The development of pervasive supervision functionalities across ensembles of interacting ACEs;
• The development of algorithms and techniques to achieve dynamic adaptation and enforce given service
• Properties through self-organized component aggregation of ACEs;
• The development of trust, security and self-preservation techniques;
• The identification of models and tools for the organization, correlation and composition of knowledge networks, according to which ACEs can exploit all the available information about their situation, however sparse and diverse.