Stochastische Analyse und lernbasierte Algorithmen zur Ressourcenbereitstellung in optischen Netzwerken

The unprecedented growth in Internet traffic has driven the innovations in provisioning of optical resources as per the need of bandwidth demands such that the resource utilization and spectrum efficiency could be maximized. With the advent of the next generation flexible optical transponders and switches, the flexible-grid-based elastic optical network (EON) is foreseen as an alternative to the widely deployed fixed-grid-based wavelength division multiplexing networks. At the same time, the flexible resource provisioning also raises new challenges for EONs. One such challenge is the spectrum fragmentation. As network traffic varies over time, spectrum gets fragmented due to the setting up and tearing down of non-uniform bandwidth requests over aligned (i.e., continuous) and adjacent (i.e., contiguous) spectrum slices, which leads to a non-optimal spectrum allocation, and generally results in higher blocking probability and lower spectrum utilization in EONs. To address this issue, the allocation and reallocation of optical resources are required to be modeled accurately, and managed efficiently and intelligently. The modeling of routing and spectrum allocation in EONs with the spectrum contiguity and spectrum continuity constraints is well-investigated, but existing models do not consider the fragmentation issue resulted by these constraints and non-uniform bandwidth demands. This thesis addresses this issue and considers both the constraints to computing exact blocking probabilities in EONs with and without spectrum conversion, and with spectrum reallocation (known as defragmentation) for the first time using the Markovian approach. As the exact network models are not scalable with respect to the network size and capacity, this thesis proposes load-independent and load-dependent approximate models to compute approximate blocking probabilities in EONs. Results show that the connection blocking due to fragmentation can be reduced by using a spectrum conversion or a defragmentation approach, but it can not be eliminated in a mesh network topology. This thesis also deals with the important network resource provisioning task in EONs. To this end, it first presents algorithmic solutions to efficiently allocate and reallocate spectrum resources using the fragmentation factor along spectral, time, and spatial dimensions. Furthermore, this thesis highlights the role of machine learning techniques in alleviating issues in static provisioning of optical resources, and presents two use-cases: handling time-varying traffic in optical data center networks, and reducing energy consumption and allocating spectrum proportionately to traffic classes in fiber-wireless networks.Die flexible Nutzung des Spektrums bringt in Elastischen Optischen Netze (EON) neue Herausforderungen mit sich, z.B., die Fragmentierung des Spektrums. Die Fragmentierung entsteht dadurch, dass die Netzwerkverkehrslast sich im Laufe der Zeit ändert und so wird das Spektrum aufgrund des Verbindungsaufbaus und -abbaus fragmentiert. Das für eine Verbindung notwendige Spektrum wird durch aufeinander folgende (kontinuierliche) und benachbarte (zusammenhängende) Spektrumsabschnitte (Slots) gebildet. Dies führt nach den zahlreichen Reservierungen und Freisetzungen des Spektrums zu einer nicht optimalen Zuordnung, die in einer höheren Blockierungs-wahrscheinlichkeit der neuen Verbindungsanfragen und einer geringeren Auslastung von EONs resultiert. Um dieses Problem zu lösen, müssen die Zuweisung und Neuzuordnung des Spektrums in EONs genau modelliert und effizient sowie intelligent verwaltet werden. Diese Arbeit beschäftigt sich mit dem Fragmentierungsproblem und berücksichtigt dabei die beiden Einschränkungen: Kontiguität und Kontinuität. Unter diesen Annahmen wurden analytische Modelle zur Berechnung einer exakten Blockierungswahrscheinlichkeit in EONs mit und ohne Spektrumskonvertierung erarbeitet. Außerdem umfasst diese Arbeit eine Analyse der Blockierungswahrscheinlichkeit im Falle einer Neuzuordnung des Sprektrums (Defragmentierung). Diese Blockierungsanalyse wird zum ersten Mal mit Hilfe der Markov-Modelle durchgeführt. Da die exakten analytischen Modelle hinsichtlich der Netzwerkgröße und -kapazität nicht skalierbar sind, werden in dieser Dissertation verkehrslastunabhängige und verkehrslastabhängige Approximationsmodelle vorgestellt. Diese Modelle bieten eine Näherung der Blockierungswahrscheinlichkeiten in EONs. Die Ergebnisse zeigen, dass die Blockierungswahrscheinlichkeit einer Verbindung aufgrund von einer Fragmentierung des Spektrums durch die Verwendung einer Spektrumkonvertierung oder eines Defragmentierungsverfahrens verringert werden kann. Eine effiziente Bereitstellung der optischen Netzwerkressourcen ist eine wichtige Aufgabe von EONs. Deswegen befasst sich diese Arbeit mit algorithmischen Lösungen, die Spektrumressource mithilfe des Fragmentierungsfaktors von Spektral-, Zeit- und räumlichen Dimension effizient zuweisen und neu zuordnen. Darüber hinaus wird die Rolle des maschinellen Lernens (ML) für eine verbesserte Bereitstellung der optischen Ressourcen untersucht und das ML basierte Verfahren mit der statischen Ressourcenzuweisung verglichen. Dabei werden zwei Anwendungsbeispiele vorgestellt und analysiert: der Umgang mit einer zeitveränderlichen Verkehrslast in optischen Rechenzentrumsnetzen, und eine Verringerung des Energieverbrauchs und die Zuweisung des Spektrums proportional zu Verkehrsklassen in kombinierten Glasfaser-Funknetzwerken

IENE 2020 International Conference “LIFE LINES – Linear Infrastructure Networks with Ecological Solutions””. Programme Book,

In the past 12 to 14 of January 2021, the University of Évora, in the framework of the LIFE LINES project, and the Infrastructure and Ecology Network Europe held the online event IENE International Conference, under the theme “LIFE LINES – Linear Infrastructure Networks with Ecological Solutions”. The local organising committee of the IENE 2020 had contributors from several institutions including the Mediterranean Institute for Agriculture, Environment and Development; REN; Infrastructures of Portugal; and the Municipalities of Montemor-o-Novo and Évora. This was the first IENE International Conference entirely online and participants could attend it from home and working place, regardless of their location in the world. We had 293 confirmed attendees (from 354 registered) from 40 different countries representing the five continents. During three days, participants were able to assist to 115 full oral presentations, 36 lightning talks, 13 workshops and chat with 40 posters authors, representing studies and projects worldwide. The event counted with 50 thematic sessions, running in five parallel sessions mixing live and pre-recorded interventions

IENE 2020 International Conference LIFE LINES – Linear Infrastructure Networks with Ecological Solutions. Abstract Book

In the past 12 to 14 of January 2021, the University of Évora, in the framework of the LIFE LINES project, and the Infrastructure and Ecology Network Europe held the online event IENE International Conference, under the theme “LIFE LINES – Linear Infrastructure Networks with Ecological Solutions”. We had 293 attendees from 40 different countries representing the five continents. During three days, participants were able to assist to 115 full oral presentations, 36 lightning talks, 13 workshops and chat with 40 posters authors, representing studies and projects worldwide. The event counted with 50 thematic sessions, running in five parallel sessions mixing live and pre-recorded interventions

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Emulator for Distributed DDoS Datasets (EDDD)

With the rapid escalation in prevalence and severity of Distributed Denial of Service (DDoS) attacks, the need for robust and effective countermeasures has become paramount. This thesis presents a unique approach to tackling this issue through the development of an emulator tool that generates distributed DDoS datasets. Addressing the limitations of existing, predominantly centralized DDoS datasets, this tool provides a distributed perspective, offering critical insights into the dynamics of these attacks. Built upon the open-source flexibility of Network Simulator 3 (NS3), the emulator is capable of modeling SYN flood traffic, ICMP flood traffic, and legitimate traffic, each one based on pre-existing datasets, thereby increasing the richness and realism of simulated DDoS scenarios. The tool’s architectural design allows for comprehensive configuration of network structures that can realistically span multiple countries, significantly enhancing the range of attack scenarios that can be explored. Providing outputs in the widely used PCAP format and featuring a straightforward command-line interface, the tool is designed to be highly accessible for both research and deployed applications. In essence, this tool constitutes a significant step forward in DDoS research, laying a solid foundation for future enhancements. It stands as a testament to the potential for improving our understanding and mitigation strategies in the face of increasingly complex and destructive DDoS attacks. The insights it offers into attack dynamics mark a valuable addition to the ongoing efforts in network security

Intrusion detection system alert correlation with operating system level logs

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2009Includes bibliographical references (leaves: 63-66)Text in English; Abstract: Turkish and Englishvii, 67 leavesInternet is a global public network. More and more people are getting connected to the Internet every day to take advantage of the Internetwork connectivity. It also brings in a lot of risk on the Internet because there are both harmless and harmful users on the Internet. While an organization makes its information system available to harmless Internet users, at the same time the information is available to the malicious users as well. Most organizations deploy firewalls to protect their private network from the public network. But, no network can be hundred percent secured. This is because; the connectivity requires some kind of access to be granted on the internal systems to Internet users. The firewall provides security by allowing only specific services through it. The firewall implements defined rules to each packet reaching to its network interface. The IDS complements the firewall security by detected if someone tries to break in through the firewall or manages to break in the firewall security and tried to have access on any system in the trusted site and alerted the system administrator in case there is a breach in security. However, at present, IDSs suffer from several limitations. To address these limitations and learn network security threats, it is necessary to perform alert correlation. Alert correlation focuses on discovering various relationships between individual alerts. Intrusion alert correlation techniques correlate alerts into meaningful groups or attack scenarios for ease to understand by human analysts. In order to be sure about the alert correlation working properly, this thesis proposed to use attack scenarios by correlating alerts on the basis of prerequisites and consequences of intrusions. The architecture of the experimental environment based on the prerequisites and consequences of different types of attacks, the proposed approach correlates alerts by matching the consequence of some previous alerts and the prerequisite of some later ones with OS-level logs. As a result, the accuracy of the proposed method and its advantage demonstrated to focus on building IDS alert correlation with OS-level logs in information security systems

Deterministic ethernet in a safety critical environment

This thesis explores the concept of creating safety critical networks with low congestion and latency (known as critical networking) for real time critical communication (safety critical environment). Critical networking refers to the dynamic management of all the application demands in a network within all available network bandwidth, in order to avoid congestion. Critical networking removes traffic congestion and delay to provide quicker response times. A Deterministic Ethernet communication system in a Safety Critical environment addresses the disorderly Ethernet traffic condition inherent in all Ethernet networks. Safety Critical environment means both time critical (delay sensitive) and content critical (error free). Ethernet networks however do not operate in a deterministic fashion, giving rise to congestion. To discover the common traffic patterns that cause congestion a detailed analysis was carried out using neural network techniques. This analysis has investigated the issues associated with delay and congestion and identified their root cause, namely unknown transmission conditions. The congestion delay, and its removal, was explored in a simulated control environment in a small star network using the Air-field communication standard. A Deterministic Ethernet was created and implemented using a Network Traffic Oscillator (NTO). NTO uses Critical Networking principles to transform random burst application transmission impulses into deterministic sinusoid transmissions. It is proved that the NTO has the potential to remove congestion and minimise latency. Based on its potential, it is concluded that the proposed Deterministic Ethernet can be used to improve network security as well as control long haul communication

Landscape functional connectivity and animal movement: application of remote sensing for increasing efficiency of road mitigation measures

Roads are a major threat to wildlife due to induced mortality and restrictions to animal movement. A central issue in conservation biology is the accurate site identification for the implementation of multispecies mitigation measures, on roads. Those measures entail high costs and methodological challenges and their efficiency highly depend on the right location. The aim of this PhD is to inform, through remote sensing and connectivity modelling, how to increase the efficiency of planning mitigation measures to reduce roadkill and promote connectivity; and demonstrate the usefulness of remote sensing in defining suitable areas for the conservation of an endangered species that often occurs in the vicinity of roads. To do so, we first assessed whether occurrence-based strategies were able to infer functional connectivity, compared to those more complex and financially demanding based on telemetry, with respect to daily and dispersal movements. Secondly, we assessed whether remote sensing data were sufficiently informative to identify key habitats for a threatened species around road verges. Thirdly, we assessed the predictive and prioritisation ability of road mitigation units intercepting multispecies corridors to prevent vulnerability to roadkill. Findings revealed that simple models are suitable as complex ones for both daily and dispersal movements, allowing for costly-effective connectivity assessments. Results demonstrated the ability of free remote sensing data to identify microhabitat conditions in verges and surrounding landscape, for a threatened rodent, allowing for the delimitation of refugee areas and definition of monitoring strategies for the species. Undemanding data (occurrence and remote sensing) were able to describe species-specific ecological requirements for birds, bats and non-flying mammals as well as roadkill patterns, possibly due to similar overlapping corridors and habitats, despite some mismatches that occurred for highly mobile species. This framework ensured high efficiency in prioritisation of multispecies roadkill mitigation planning, resilient to long-term landscape dynamics; Conectividade funcional da paisagem e movimento animal: aplicação da detecção remota para aumentar a eficiência de medidas de mitigação em estradas. Resumo: As estradas constituem uma enorme ameaça para a vida selvagem devido à mortalidade. Uma questão central é a identificação dos locais para implementar medidas de mitigação multiespécies, em estradas. Essas medidas envolvem custos elevados e desafios metodológicos e sua eficiência depende muito da localização correcta. O objetivo deste doutoramento é informar, através de detecção remota e conectividade, como aumentar a eficiência do planeamento de medidas de mitigação para reduzir atropelamentos e promover a conectividade; e demonstrar a utilidade da detecção remota na definição de áreas adequadas para a conservação de espécies ameaçadas que podem ocorrer nas proximidades de estradas. Portanto, primeiro avaliamos se os dados resultantes de amostragens simples eram capazes de inferir conectividade funcional, em comparação com estratégias complexas, respeito aos movimentos diários e de dispersão. Segundo, avaliamos se os dados de detecção remota eram suficientemente informativos para identificar habitats-chave para uma espécie ameaçada em torno das margens das estradas. Terceiro, avaliamos a capacidade preditiva e de prioritização das unidades de mitigação de estradas que cruzam corredores multi-espécies para reduzir o risco de atropelamentos. Os resultados revelaram que os modelos simples são adequados quanto os complexos para os movimentos diários e de dispersão. Os resultados demonstraram a capacidade dos dados de detecção remota gratuitos em identificar condições de microhabitats nos habitats de berma e na paisagem circundante, para um roedor ameaçado, permitindo a delimitação de áreas de refúgio. Dados pouco exigentes (ocorrência e detecção remota) foram capazes de descrever os requisitos ecológicos específicos de aves, morcegos e mamíferos não voadores, bem como padrões de atropelamentos, possivelmente devido a corredores e habitats semelhantes, apesar de haver algumas incompatibilidades para espécies de maior mobilidade. Essa estrutura foi capaz de garantir uma elevada eficiência na prioritização de planeamento de mitigação de atropelamentos para multi-espécies, resiliente à dinâmica da paisagem de longo prazo