• Conference Object  

      Attack-aware Lightpath Provisioning in Elastic Optical Networks with Traffic Demand Variations 

      Manousakis, Konstantinos; Panayiotou, Tania; Kolios, Panayiotis; Tomkos, Ioannis; Ellinas, Georgios (2019)
      This work considers lightpath provisioning in elastic optical networks with traffic demand variations while accounting for the impact of jamming attacks. Traffic requests are modeled based on their variation in traffic and ...
    • Conference Object  

      Centralized and Distributed Machine Learning-Based QoT Estimation for Sliceable Optical Networks 

      Panayiotou, Tania; Savvas, Giannis; Tomkos, Ioannis; Ellinas, Georgios (2019)
      Dynamic network slicing has emerged as a promising and fundamental framework for meeting 5G’s diverse use cases. As machine learning (ML) is expected to play a pivotal role in the efficient control and management of these ...
    • Conference Object  

      Charging Policies for PHEVs used for Service Delivery: A Reinforcement Learning Approach 

      Panayiotou, Tania; Chatzis, Sotirios P.; Panayiotou, Christos; Ellinas, Georgios (2018)
      This work examines a cost optimization problem for plug-in hybrid electric vehicles (PHEVs) used for service delivery, in the presence of energy consumption uncertainty. For the cost optimization problem, an optimal policy ...
    • Article  

      A Data-Driven Bandwidth Allocation Framework With QoS Considerations for EONs 

      Panayiotou, Tania; Manousakis, Konstantinos; Chatzis, Sotirios P.; Ellinas, Georgios (2019)
      This paper proposes a data-driven bandwidth allocation (BA) framework for periodically and dynamically reconfiguring an elastic optical network according to predictive BA (PBA) models. The proposed framework is scalable ...
    • Conference Object  

      Data-Driven Bandwidth Allocation in EONs 

      Panayiotou, Tania; Ellinas, Georgios (2018)
      We investigate periodically and dynamically reconfiguring elastic optical networks (EONs) utilizing predictive bandwidth allocation models found by applying reinforcement learning. These models aim at efficiently utilizing ...
    • Conference Object  

      Machine Learning for QoT Estimation of Unseen Optical Network States 

      Panayiotou, Tania; Savva, Giannis; Shariati, Behnam; Tomkos, Ioannis; Ellinas, Georgios (2019)
      We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core crosstalk that is prominent in optical ...
    • Conference Object  

      On learning bandwidth allocation models for time-varying traffic in flexible optical networks 

      Panayiotou, Tania; Manousakis, Konstantinos; Chatzis, Sotirios P.; Ellinas, Georgios (2018)
      We examine the problem of bandwidth allocation (BA) on flexible optical networks in the presence of traffic demand uncertainty. We assume that the daily traffic demand is given in the form of distributions describing the ...