Cloud Computing has risen a great interest over the last years as it represents an enabling technology for flexible and ubiquitous access over the network to a set of shared computing resources. This work comes from an industrial experience aiming at exploiting the cloud potential for virtualizing complex infrastructures such as an entire Air Traffic Center (ATC), a clear example of complex SoS (System of Systems). The use of virtualization is convenient because industry can leverage in-house test-beds to perform distributed testing campaigns in pre-operational phases or to design new automatic fail-over mechanisms for fully distributed systems. In order to realize such mitigation and recovery techniques in the ATC field, indeed, a cloud platform is required to guarantee a low VM provisioning time with the objective of minimizing the service disruption. In this perspective, after having introduced the principal concepts and factors of the provisioning time, we propose a deep analysis and comparison for two different Infrastructure-as-a-Service (IaaS) platforms, namely Open Stack and Open Nebula (using KVM as hypervisor), that were selected through a preliminary scouting phase
The distributed and complexity nature of modern critical infrastructures that have to provide integrated services through the interoperability of heterogeneous subsystems, even spread among different countries, require new methodologies and tools to dominate overall systems complexity. In particular, in order to get knowledge about their real behavior and define dependability improvement actions, such complex and distributed systems should be reproduced and simulated locally. On the other hand, the extraordinary large number of their components cause a large-scale of the resulting model, limiting its resolution by current simulators. This paper presents a framework to implement hybrid simulation of distributed large-scale critical infrastructures, such as Air Traffic Control (ATC) and Vessel Traffic System (VTS). High Level Architecture (HLA) has been introduced into the engine simulations platform as its design and development foundation, whereas cloud-based virtualization techniques have been exploited in order to reproduce the overall distributed system on a local adaptive testbed. The use of such a framework can result in a considerable reduction of costs in all the system life phases, as well as an increased system dependability level.
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