Security-Aware RWA for Dynamic Traffic Using Path Protection In WDM Networks

Security and attack management have become the prime concern for the network operators due to high data transfer rates and vulnerabilities associated with transparency in WDM networks. In the recent years, there is a substantial increase in perception to develop suitable mechanisms for subduing the adverse effects of malicious attacks such as high power jamming and tapping attacks.In transparent optical networks (TONs) traffic is carried over the optical fibers in the form of signals called lightpaths, creating a virtual topology over the physical interconnections of an optical fiber. This allows an exchange of an enormous amount of data at a very high speed. A fault or an attack on the network can lead to data tampering and data loss. Unlike faults, malicious attacks may not be localized and we cannot handle them with the standard fault-tolerance mechanisms in WDM networks. The Routing and Wavelength Assignment (RWA) problem assigns appropriate routes and wavelengths to all associated lightpaths in the network. Most the researchers considered the static traffic model, where the network requests (i.e. lightpaths to be established) are known in advance and last over long durations. In this thesis, we are solving the security-aware problem for dynamic requests by using protection strategy known as dedicated path protection (DPP). In the dynamic model, lightpaths are generated on-demand, and RWA must be performed based on available resources that are not being used by ongoing lightpaths. We propose an Integer linear programming (ILP) formulation to maximize requests satisfaction and reducing the disruption in the network due to malicious attacks (In-band and out-band)

Resilient Resource Allocation Schemes in Optical Networks

Recent studies show that deliberate malicious attacks performed by high-power sig- nals can put large amount of data under risk. We investigate the problem of sur- vivable optical networks resource provisioning scheme against malicious attacks, more specically crosstalk jamming attacks. These types of attacks may cause ser- vice disruption (or possibly service denial). We consider optical networks based on wavelength-division multiplexing (WDM) technology and two types of jamming at- tacks: in-band and out-of-band attacks. We propose an attack-aware routing and wavelength assignments (RWA) scheme to avoid or reduce the damaging effects of potential attacking signals on individual or multiple legitimate lightpaths travers- ing the same optical switches and links. An integer linear programs (ILPs) as well as heuristic approaches were proposed to solve the problem. We consider dynamic traffic where each demand is dened by its start time and a duration. Our results show that the proposed approaches were able to limit the vulnerability of lightpaths to jamming attacks. Recently, large-scale failures caused by natural disasters and/or deliberate at- tacks have left major parts of the networks damaged or disconnected. We also investigate the problem of disaster-aware WDM network resource provisioning in case of disasters. We propose an ILP and efficient heuristic to route the lightpaths in such a way that provides protection against disasters and minimize the network vi resources such as the number of wavelength links used in the network. Our models show that signicant resource savings can be achieved while accommodating users demands. In the last few years, optical networks using Space Division Multiplexing (SDM) has been proposed as a solution to the speed bottleneck anticipated in data center (DC) networks. To our knowledge the new challenges of designing such communica- tion systems have not been addressed yet. We propose an optimal approach to the problem of developing a path-protection scheme to handle communication requests in DC networks using elastic optical networking and space division multiplexing. We have formulated our problem as an ILP. We have also proposed a heuristic that can handle problems of practical size. Our simulations explore important features of our approach

Attack-Aware Routing and Wavelength Assignment of Scheduled Lightpath Demands

In Transparent Optical Networks, tra c is carried over lightpaths, creating a vir- tual topology over the physical connections of optical bers. Due to the increasingly high data rates and the vulnerabilities related to the transparency of optical network, security issues in transparent wavelength division multiplexing (WDM) optical net- works have become of great signi cance to network managers. In this thesis, we intro- duce some basic concepts of transparent optical network, the types and circumstances of physical-layer attacks and analysis of related work at rst. In addition, based on the previous researches, we present a novel approach and several new objective cri- terions for the problem of attack-aware routing and wavelength assignment. Integer Linear Programming (ILP) formulation is used to solve the routing sub-problem with the objective to minimize the disruption of physical-layer attack as well as to opti- mize Routing and Wavelength Assignment (RWA) of scheduled transparent optical network

Attack Aware RWA for Sliding Window Scheduled Traffic Model

In Transparent optical networks (TONs), the data signals remain in the optical domain for the entire transmission path. The capability of handling high data rates and features like transparency makes TONs susceptible to several physical layer attacks. Hence, designing TONs with a capability of handling such high power jamming attacks is an important network security problem. In this work, we propose an integer linear program (ILP) formulation to control the propagation of these physical layer attacks in TONs, for the demands which need periodic bandwidth usage at certain predefined timings. There are two different approaches for handling these scheduled traffic demands, fixed window and sliding window. Our research deals with the sliding window scheduled traffic model, which is more flexible when compared with fixed window, as the start and end timings of the demand are unknown and they slide within a larger window setting. Hence, we present an ILP to handle the routing and wavelength assignment (RWA) problem for sliding window scheduled traffic model, with an objective to minimize the attack radius for all the commodities

Multi-Period Attack-Aware Optical Network Planning under Demand Uncertainty

In this chapter, novel attack‐aware routing and wavelength assignment (Aa‐RWA) algorithms for multiperiod network planning are proposed. The considered physical layer attacks addressed in this chapter are high‐power jamming attacks. These attacks are modeled as interactions among lightpaths as a result of intra‐channel and/or inter‐channel crosstalk. The proposed Aa‐RWA algorithm first solves the problem for given traffic demands, and subsequently, the algorithm is enhanced in order to deal with demands under uncertainties. The demand uncertainty is considered in order to provide a solution for several periods, where the knowledge of demands for future periods can only be estimated. The objective of the Aa‐RWA algorithm is to minimize the impact of possible physical layer attacks and at the same time minimize the investment cost (in terms of switching equipment deployed) during the network planning phase

Attack-aware routing and wavelength assignment for dynamic traffic in WDM networks

Transparent Optical Networks (TONs) can communicate large amount of data at a high speed among nodes of the network. So, any type of failure whether caused by component failure or caused by an attack can cause a significant loss of data. In case of faults, the network can restore its functionality, by identifying the malfunctioning component of the network and solving the problem. This is not the case with a deliberate, malicious attack. That is why security and attack management is becoming a very important issue in WDM networks. In the previous years, a number of researchers worked on solving the attack problem. One common approach is to plan the network in a way that minimizes the influence of an attack, by using appropriate routing and wavelength assignment (RWA) strategies. Most of the research in this area focuses on the static traffic model, where the set of traffic demands is known in advance. In this thesis, we propose a new security-aware RWA technique for dynamic traffic, using dedicated path protection. The goal is to improve the performance of WDM networks by accommodating more traffic demands, while reducing the probability of disruption due to malicious attacks

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

Resource Allocation in Communication and Social Networks

abstract: As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.Dissertation/ThesisPh.D. Computer Science 201

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets