Technical Note: \cal Q-Learning
Machine Learning
Optical packet switching multiple path routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Computational Complexity Issues in Operative Diagnostics of Graph-Based Systems
IEEE Transactions on Computers
Dynamic buffer management using per-queue thresholds: Research Articles
International Journal of Communication Systems
Metrics for packet reordering—A comparative analysis
International Journal of Communication Systems
Novel reinforcement learning-based approaches to reduce loss probability in buffer-less OBS networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
QoS differentiation in optical packet-switched networks
Computer Communications
An RL-based scheduling algorithm for video traffic in high-rate wireless personal area networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Cognitive network management with reinforcement learning for wireless mesh networks
IPOM'07 Proceedings of the 7th IEEE international conference on IP operations and management
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A practical approach to scheduler implementation for optical burst/packet switching
ONDM'10 Proceedings of the 14th conference on Optical network design and modeling
A novel approach for failure localization in all-optical mesh networks
IEEE/ACM Transactions on Networking (TON)
Traffic engineering in next-generation optical Networks
IEEE Communications Surveys & Tutorials
Multiple attack localization and identification in all-optical networks
Optical Switching and Networking
Optical network design to minimize switching and transceiver equipment costs
Optical Switching and Networking
Fault and attack management in all-optical networks
IEEE Communications Magazine
Tolerance of intentional attacks in complex communication networks
IEEE Communications Magazine
Failure Location Algorithm for Transparent Optical Networks
IEEE Journal on Selected Areas in Communications
The effect of packet reordering in a backbone link on application throughput
IEEE Network: The Magazine of Global Internetworking
AN EVOLUTIONARY ALGORITHM APPROACH FOR DEDICATED PATH PROTECTION PROBLEM IN ELASTIC OPTICAL NETWORKS
Cybernetics and Systems - Intelligent Network Security and Survivability
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While transparent optical networks become more and more popular as the basis of the Next Generation Internet (NGI) infrastructure, such networks raise many security issues because they lack the massive use of optoelectronic monitoring. To increase these networks' security, they will need to be equipped with proactive and reactive mechanisms to protect themselves not only from failures and attacks but also from ordinary reliability problems. This work presents a novel self-healing framework to deal with attacks on Transparent Optical Packet Switching (TOPS) mesh networks. Contrary to traditional approaches which deal with attacks at the fiber level, our framework allows to overcome attacks at the wavelength level as well as to understand how they impact the network's performance. The framework has two phases: the dimensioning phase (DP) dynamically determines the optical resources for a given mesh network topology whereas the learning phase (LP) generates an intelligent policy to gracefully overcome attacks in the network. DP uses heuristic reasoning to engineer the network while LP relies on a reinforcement learning algorithm that yields a self-healing policy within the network. We use a Monte Carlo simulation to analyze the performance of the aforementioned framework not only under different types of attacks but also using three realistically sized mesh topologies with up to 40 nodes. We compare our framework against shortest path (SP) and multiple path routing (MPR) showing that the self-organized routing outperforms both, leading to a reduction in packet loss of up to 88% with average packet loss rates of 1x10^-^3. Finally, some conclusions are presented as well as future research lines.