No abstract

Network Functions Virtualization is focused on\ud migrating traditional hardware-based network functions to\ud software-based appliances running on standard high volume\ud severs. There are a variety of challenges facing early adopters of\ud Network Function Virtualizations; key among them are resource\ud and service mapping, to support virtual network function orchestration.\ud Service providers need efficient and effective mapping\ud capabilities to optimally deploy network services. This paper\ud describes TeNOR, a micro-service based network function virtualisation\ud orchestrator capable of effectively addressing resource\ud and network service mapping. The functional architecture and\ud data models of TeNOR are described, as well as two proposed\ud approaches to address the resource mapping problem. Key\ud evaluation results are discussed and an assessment of the mapping\ud approaches is performed in terms of the service acceptance ratio\ud and scalability of the proposed approaches

This paper presents an original discrete-time, distributed, non-cooperative load balancing algorithm, based on mean field game theory, which does not require explicit communications. The algorithm is proved to converge to an arbitrarily small neighborhood of a specific equilibrium among the loads of the providers, known as Wardrop equilibrium. Thanks to its characteristics, the algorithm is suitable for the Software Defined Networking (SDN) scenario, where service requests coming from the network nodes, i.e., the switches, are managed by the so-called SDN Controllers, playing the role of providers. The proposed approach is aimed at dynamically balancing the requests of the switches among the SDN Controllers to avoid congestion. The paper also suggests the adoption of SDN Proxies to improve the scalability of the overall SDN paradigm and presents an implementation of the algorithm in a proof-of-concept SDN scenario, which shows the effectiveness of the proposed solution with respect to the current approaches.

Industrial and Automation Control systems traditionally achieved security thanks to the use of proprietary protocols and isolation from the telecommunication networks. Nowadays, the advent of the Industrial Internet of Things poses new security challenges. In this paper, we first highlight the main security challenges that advocate for new risk assessment and security strategies.To this end we propose a security framework and advanced tools to properly manage vulnerabilities, and to timely react to the threats. The proposed architecture fills the gap between computer science and control theoretic approaches. The physical layers connected to Industrial Control Systems are prone to disrupt when facing cyber-attacks. Considering the modules of the proposed architecture, we focus on the development of a practical framework to compare information about physical faults and cyber-attacks. This strat-egy is implemented in the ATENA architecture which has been designed as an innovative solution for the protection of critical assets.

No abstract