This project is focused on optimization of multilayer application-aware networks. The key goal of the project is to develop, implement, and analyze models and algorithms for optimization of multilayer application-aware networks. An application-aware network can be defined as a network that is able to identify and classify applications and then use suitable optimization techniques to provision these application using resources accessible in the network in order to achieve acceptable application performance metrics. In turn, a multilayer network is a network modeled as a set of separate layers using various technologies and protocols applied to transmit data. In the context of this project, we assume that the network consists of two layers: packet layer and optical layer. The packet layer is used to directly serve the applications, i.e., to establish in the network demands required to serve various types of applications. In turn, the optical layer is used to establish virtual topologies to provision flows aggregated over the packet layer service demands.
The network optimization can be performed considering each single layer of the network separately. However, multilayer optimization allows to improve the overall network performance, namely, reduce CAPEX expenditures and at the same time holding the QoS (Quality of Service) parameters required by the applications by identifying the network configurations that jointly optimizes packet and optical resources. The idea of application-aware networking has been known for many years, however the vast majority of previous works in this area have been focused on a single layer (packet layer) optimization, i.e., the routing algorithms have been aware only of the packet layer resources and constraints. While at the same time, the configuration of optical layer resources have not been updated according to changing requirements. Moreover, recent trends in application characteristics, namely, the increasing diversity of requirements in almost all performance indicators (e.g., bitrate, latency, resilience, security) and new network capabilities trigger the need of multilayer application-aware networking.
In this Project, we form a hypothesis that it is possible to design new optimization methods for multilayer application-aware networks in order to improve the network performance by utilizing additional information that can be provided by cognitive processes including data analytics mechanisms based on machine learning methods. Potential recipients of the Project results are network operators, network service providers, and producers of network equipment and software, since results of the Project can be applied to design and optimize communication networks.
News and Seminars
2021.07.07 Paper (Goścień R., Knapińska A., Włodarczyk A., Modeling and Prediction of Daily Traffic Patterns—WASK and SIX Case Study) accepted to Electronics 2021, 10(14), DOI information: https://doi.org/10.3390/electronics10141637
2021.06.12 Paper (Lechowicz P., Knapińska A., Goścień R., Fragmentation-Aware Traffic Grooming with Lane Changes in Spectrally–Spatially Flexible Optical Networks) accepted to Electronics 2021, 10(12), DOI information: https://doi.org/10.3390/electronics10121502
2021.06.30 Seminar: Aleksandra Knapińska “Long-term traffic prediction with ensemble learning on data streams”
2021.06.30 Seminar: Dr Róża Goścień “On the Efficient Flow Restoration in Spectrally-Spatially Flexible Optical Networks”
2021.03.31 Seminar: Aleksandra Knapińska “Multilayer Application-Aware Networks - Literature Review”
2021.03.31 Seminar: Daniel Szostak “Survey of Machine Learning approaches for Network Traffic Forecasting”
2021.03.17 Paper (Knapińska A., Lechowicz P., Walkowiak K., Machine-Learning Based Prediction of Multiple Types of Network Traffic) accepted to the International Conference on Computational Science ICCS 2021 (link https://www.iccs-meeting.org/iccs2021/) held June 16-18, 2021 in Kraków, Poland.
2021.02.03 Seminar: Aleksandra Knapińska “Machine-Learning Based Prediction of Multiple Types of Network Traffic”
2021.02.03 Seminar: Damian Mroziński “Optimization of conergent packet switched 5G transport networks with latency-sensitive traffic flows”
2021.02.03 Seminar: Dominik Dulas “AI-assisted dimensioning methods for Network Slicing in Next Generation Mobile Networks”
2020.12.02 Seminar: Dr Piotr Lechowicz “Regression-based fragmentation metrics in spectrally-spatially flexible optical networks”
2020.12.02 Seminar: Prof. Miroslaw Klinkowski (National Institute of Telecommunications, Warsaw) “Optimization of 5G conergent transport networks with packet switching and time sensitive traffic”
2020.10.07 Seminar: Prof. Krzysztof Walkowiak “Advanced methods for optimization of multilayer application-aware networks – Project kick-off meeting”