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.
The increasing demand of bandwidth, low latency\ud
and reliability, even in mobile scenarios, has pushed the\ud
evolution of the networking technologies in order to satisfy the\ud
requirements of innovative services. In this context, Software\ud
Defined Networking (SDN), namely a new networking\ud
paradigm that proposes the decoupling of the control plane\ud
from the forwarding plane, enables network control\ud
centralization and automation of the network management. In\ud
order to address the performance issues related to the SDN\ud
Control Plane, this paper proposes a distributed load balancing\ud
algorithm with the aim of dynamically balancing the control\ud
traffic across a cluster of SDN Controllers, thus minimizing the\ud
latency and increasing the overall cluster throughput. The\ud
algorithm is based on game theory and converges to a specific\ud
equilibrium known as Wardrop equilibrium. Numerical\ud
simulations show that the proposed algorithm outperforms a\ud
standard static configuration approach
The paper describes an innovative and fully cognitive approach which offers the opportunity to cope with some key limitations of the present telecommunication networks by means of the introduction of a novel architecture design in the perspective of the emerging Future Internet framework. Within this architecture, the Quality of Experience (QoE) Management functionalities are aimed at approaching the desired QoE level of the applications by dynamically selecting the most appropriate Class of Service supported by the network. In the present work, this selection is driven by an optimal and adaptive control strategy based on the renowned Q-Learning algorithm. The proposed dynamic approach differs from the traffic classification approaches found in the literature, where a static assignment of Classes of Service to applications is performed
The increasing number of the Internet connected devices requires novel solutions to control the next generation network resources. The cooperation between the Software Defined Network (SDN) and the Network Function Virtualization (NFV) seems to be a promising technology paradigm. The bottleneck of current SDN/NFV implementations is the use of a centralized controller. In this paper, different scenarios to identify the pro and cons of a distributed control-plane were investigated. We implemented a prototypal framework to benchmark different centralized and distributed approaches. The test results have been critically analyzed and related considerations and recommendations have been reported. The outcome of our research influenced the control plane design of the following European R&D projects: PLATINO, FI-WARE and T-NOVA.
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