Specification, Development, and Verification of CASCADAS Autonomic Computing and Networking Toolkit

Increasing complexity, heterogeneity, and dynamism of current networks (telecommunications, ICT, and Internet) are making current computational and communication infrastructures brittle, inefficient, and almost unmanageable. As a matter of fact, computing and storage are progressively embedded in all sorts of nodes and devices that are interconnected through a variety of (wireless and wired) technologies in Networks of Networks (NoNs). Dynamicity, pervasivity, and interconnectivity of future NoNs will increase the complexity of their management, control, and optimization more and more, and will open new challenges for service delivery in such environments. Autonomic communications principles and technologies can provide effective computing and networking solutions overcome these bottlenecks and to foster such challenging evolution. This chapter presents the main concepts of an autonomic communications toolkit designed and developed in the EU project CASCADAS for creating and supervising service networking ecosystems, structured as ensembles of distributed and cooperating autonomic components. Moreover, it describes several use-cases developed for its validation and demonstration and reports the experimental results to assess the toolkit performances. A brief overview of future research directions concludes the chapter.

Ontology-Based Network Management for Autonomic Communications

This chapter is focused on state-of-the art issues in the area of ontology-based autonomic communications and it considers how ontologies can be useful for network management as a way to achieve semantic interoperability among different network management models. In addition, it presents the autonomic communications paradigm as a possible solution to the ever-growing complexity of commercial networks due to the increasing complexity of individual network elements, the need for intelligent network and communication services and the heterogeneity of connected equipment. Finally, the chapter analyses how ontologies can be used to combine data correlation and inference technologies in autonomic networks. Such technologies are used as core components to build autonomic networks.