Management of Spectral Resources in Elastic Optical Networks

Recent developments in the area of mobile technologies, data center networks, cloud computing and social networks have triggered the growth of a wide range of network applications. The data rate of these applications also vary from a few megabits per second (Mbps) to several Gigabits per second (Gbps), thereby increasing the burden on the Inter- net. To support this growth in Internet data traffic, one foremost solution is to utilize the advancements in optical networks. With technology such as wavelength division multiplexing (WDM) networks, bandwidth upto 100 Gbps can be exploited from the optical fiber in an energy efficient manner. However, WDM networks are not efficient when the traffic demands vary frequently. Elastic Optical Networks (EONs) or Spectrum Sliced Elastic Optical Path Networks (SLICE) or Flex-Grid has been recently proposed as a long-term solution to handle the ever-increasing data traffic and the diverse demand range. EONs provide abundant bandwidth by managing the spectrum resources as fine-granular orthogonal sub-carriers that makes it suitable to accommodate varying traffic demands. However, the Routing and Spectrum Allocation (RSA) algorithm in EONs has to follow additional constraints while allocating sub-carriers to demands. These constraints increase the complexity of RSA in EONs and also, make EONs prone to the fragmentation of spectral resources, thereby decreasing the spectral efficiency. The major objective of this dissertation is to study the problem of spectrum allocation in EONs under various network conditions. With this objective, this dissertation presents the author\u27s study and research on multiple aspects of spectrum allocation in EONs: how to allocate sub-carriers to the traffic demands, how to accommodate traffic demands that varies with time, how to minimize the fragmentation of spectral resources and how to efficiently integrate the predictability of user demands for spectrum assignment. Another important contribution of this dissertation is the application of EONs as one of the substrate technologies for network virtualization

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Industrial Wireless Sensor Networks

Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs

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

Dynamic Resource Allocation in Metro Elastic Optical Networks using Lyapunov Drift Optimization

Consistent growth in the volume and dynamic behavior of traffic mandates new requirements for fast and adaptive resource allocation in metro networks. We propose a dynamic resource allocation technique for adaptive minimization of spectrum usage in metro elastic optical networks. We consider optical transmission as a service specified by its bandwidth profile parameters, which are minimum, average, and maximum required transmission rates. To consider random traffic events, we use a stochastic optimization technique to develop a novel formulation for dynamic resource allocation in which service level specifications and network stability constraints are addressed. Next, we employ the elegant theory of Lyapunov optimization to solve the stochastic optimization problem and derive a fast integer linear program, which is periodically solved to create an adaptation between available resources and dynamic network state. To quantize the performance of the proposed technique, we report its spectral efficiency as a function of peak to average traffic ratio and Lyapunov penalty coefficient. Simulation results show that the dynamic resource allocation procedure can improve spectral efficiency by a factor of 3.3 for a peak to average traffic ratio of 1.37 and a Lyapunov penalty coefficient of 1000 in comparison with fixed network planning. There is also a trade-off between transmission delay and spectrum utilization in the proposed technique, which can be adjusted by a Lyapunov penalty coefficient

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)

Benchmarking and viability assessment of optical packet switching for metro networks

Optical packet switching (OPS) has been proposed as a strong candidate for future metro networks. This paper assesses the viability of an OPS-based ring architecture as proposed within the research project DAVID (Data And Voice Integration on DWDM), funded by the European Commission through the Information Society Technologies (IST) framework. Its feasibility is discussed from a physical-layer point of view, and its limitations in size are explored. Through dimensioning studies, we show that the proposed OPS architecture is competitive with respect to alternative metropolitan area network (MAN) approaches, including synchronous digital hierarchy, resilient packet rings (RPR), and star-based Ethernet. Finally, the proposed OPS architectures are discussed from a logical performance point of view, and a high-quality scheduling algorithm to control the packet-switching operations in the rings is explained

Priority realloc : a threefold mechanism for route and resources allocation in EONs

Cotutela Universitat Politècnica de Catalunya i Escola Politécnica da Universidade de São PauloBackbone networks are responsible for long-haul data transport serving many clients with a large volume of data. Since long-haul data transport service must rely on a robust high capacity network the current technology broadly adopted by the industry is Wavelength Division Multiplexing (WDM). WDM networks enable one single fiber to operate with multiple high capacity channels, drastically increasing the fiber capacity. In WDM networks each channel is associated with an individual wavelength. Therefore a whole wavelength capacity is assigned to a connection, causing waste of bandwidth in case the connection bandwidth requirement is less than the channel total capacity. In the last half decade, Elastic Optical Networks (EON) have been proposed and developed based on the flexible use of the optical spectrum known as the flexigrid. EONs are adaptable to clients requirements and may enhance optical networks performance. For these reasons, research community and data transport providers have been demonstrating increasingly high interest in EONs which are likely to replace WDM as the universally adopted technology in backbone networks in the near future. EONs have two characteristics that may limit its efficient resources use. The spectrum fragmentation, inherent to the dynamic EON operation, decreases the network capacity to assign resources to connection requests increasing network blocking probability. The spectrum fragmentation also intensifies the denial of service to higher rate request inducing service unfairness. Due to the fact EONs were just recently developed and proposed, the aforementioned issues were not yet extensively studied and solutions are still being proposed. Furthermore, EONs do not yet provide specific features as differentiated service mechanisms. Differentiated service strategies are important in backbone networks to guarantee client's diverse requirements in case of a network failure or the natural congestion and resources contention that may occur at some periods of time in a network. Impelled by the foregoing facts, this thesis objective is three-fold. By means of developing and proposing a mechanism for routing and resources assignment in EONs, we intend to provide differentiated service while decreasing fragmentation level and increasing service fairness. The mechanism proposed and explained in this thesis was tested in an EON simulation environment and performance results indicated that it promotes beneficial performance enhancements when compared to benchmark algorithms.Redes backbone sao responsáveis pelo transporte de dados à longa distância que atendem a uma grande quantidade de clientes com um grande volume de dados. Como redes backbone devem basear-se em uma rede robusta e de alta capacidade, a tecnologia atual amplamente adotada pela indústria é Wavelength Division Multiplexing (WDM). Redes WDM permitem que uma única fibra opere com múltiplos canais de alta largura de banda, aumentando drasticamente a capacidade da fibra. Em redes WDM cada canal está associado a um comprimento de onda particular. Por conseguinte, toda capacidade do comprimento de onda é atribuída a uma única conexão, fazendo com que parte da largura de banda seja desperdiçada no caso em que a requisição de largura de banda da conexão seja menor do que a capacidade total do canal. A partir da metade da última década, as Redes Ópticas Elásticas (Elastic Optical Networks - EON) têm sido propostas e desenvolvidas com base no uso flexível do espectro óptico conhecido como flexigrid. EONs são adaptáveis às requisiçes por banda dos clientes e podem, portanto, melhorar o desempenho das redes ópticas. Por estas razões, EONs têm recebido cada vez mais interesse dos meios de pesquisa e provedores de serviço e provavelmente substituirão WDM como a tecnologia universalmente adotada pela indústria em redes backbone. EONs têm duas características que podem limitar a utilização eficiente de recursos. A fragmentação do espectro, inerente à operação dinâmica das EONs, pode diminuir a capacidade da rede em distribuir recursos ao atender às solicitações por conexões aumentando a probabilidade de bloqueio na rede. A fragmentação do espectro também intensifica a negação de serviço às solicitações por taxa de transmissão mais elevada, gerando injustiça no serviço prestado. Como EONs foram desenvolvidas recentemente, respostas às questões acima mencionadas ainda estão sob estudo e soluções continuam sendo propostas na literatura. Além disso, EONs ainda não fornecem funções específicas como um mecanismo que proveja diferenciação de serviço. Estratégias de diferenciação de serviço são importantes em redes backbone para garantir os diversos requisitos dos clientes em caso de uma falha na rede ou do congestionamento e disputa por recursos que podem ocorrer em alguns períodos em uma rede. Impulsionada pelos fatos anteriormente mencionados, esta tese possui três objetivos. Através do desenvolvimento e proposta de um mecanismo de roteamento e atribuição de recursos para EONs, temos a intenção de disponibilizar diferenciação de serviço, diminuir o nível de fragmentação de espectro e aumentar a justiça na distribuição de serviços. O mecanismo proposto nesta tese foi testado em simulações de EONs. Resultados indicaram que o mecanismo proposto promove benefícios através do aprimoramento da performance de uma rede EON quando comparado com algoritmos de referência.Les xarxes troncals son responsables per el transport de dades a llarga distància que serveixen a una gran quantitat de clients amb un gran volum de dades. Com les xarxes troncals han d'estar basades en una xarxa robusta i d'alta capacitat, la tecnologia actual àmpliament adoptada per la indústria és el Wavelength Division Multiplexing (WDM). Xarxes WDM permeten operar amb una sola fibra multicanal d'alt ample de banda, el que augmenta molt la capacitat de la fibra. A les xarxes WDM cada canal est a associat amb una longitud d'ona particular. En conseqüència, tota la capacitat del canal es assignada a una sola connexió, fent que part dels recurs siguin perduts en el cas en que l'ample de banda sol licitada sigui menys que la capacitat total del canal. A gairebé deu anys les xarxes òptiques elàstiques (Elastic Optical Networks -EON) son propostes i desenvolupades basades en el ús visible de l'espectre òptic conegut com Flexigrid. EONs són adaptables a les sol·licituds per ample de banda dels clients i per tant poden millorar el rendiment de les xarxes òptiques. Per aquestes raons, EONs han rebut cada vegada més interès en els mitjans d’investigació i de serveis i, probablement, han de reemplaçar el WDM com la tecnologia universalment adoptada en les xarxes troncals. EONs tenen dues característiques que poden limitar l'ús eficient dels recursos seus. La fragmentació de l'espectre inherent al funcionament dinàmic de les EONs, pot disminuir la capacitat de la xarxa en distribuir els recursos augmentant la probabilitat de bloqueig de connexions. La fragmentació de l'espectre també intensifica la denegació de les sol·licituds de servei per connexions amb una major ample de banda, el que genera injustícia en el servei ofert. Com les EONs s'han desenvolupat recentment, solucions als problemes anteriors encara estan en estudi i les solucions segueixen sent proposades en la literatura. D'altra banda, les EONs encara no proporcionen funcions especifiques com mecanisme de diferenciació de provisió de serveis. Estratègies de diferenciació de servei són importants en les xarxes troncals per garantir les diverses necessitats dels clients en cas d'una fallada de la xarxa o de la congestió i la competència pels recursos que es poden produir en alguns períodes. Impulsada pels fets abans esmentats, aquesta tesi te tres objectius. A través del desenvolupament i proposta d'un mecanisme d'enrutament i assignació de recursos per EONs, tenim la intenció d'oferir la diferenciació de serveis, disminuir el nivell de fragmentació de l'espectre i augmentar l'equitat en la distribució dels serveis. El mecanisme proposat en aquesta tesi ha estat provat en simulacions EONs. Els resultats van indicar que el mecanisme promou millores en el rendiment de la EON, en comparació amb els algoritmes de referència.Postprint (published version

エラスティック光ネットワークにおけるトラヒック収容性を向上させるための無瞬断デフラグメンテーション

In elastic optical networks (EONs), a major obstacle to using the spectrum resources efficiently is spectrum fragmentation. Much of the research activities in EONs focuses on finding defragmentation methods which remove the spectrum fragmentation. Among the defragmentation methods presented in the literature, hitless defragmentation has been introduced as an approach to limit the spectrum fragmentation in elastic optical networks without traffic disruption. It facilitates the accommodation of new request by creating large spectrum blocks, as it moves active lightpaths (retuning) to fill in gaps left in the spectrum by expired ones.　Nevertheless, hitless defragmentation witnesses limitations for gradual retuning with the conventionally used first fit allocation. The first fit allocation stacks all lightpaths to the lower end of the spectrum. This leads to a large number of lightpaths that need to be retuned and are subject to interfere with each other\u27s retuning. This thesis presents two schemes, which are based on hitless defragmentation, to increase the admissible traffic in EONs.　Firstly, a route partitioning scheme for hitless defragmentation in default EONs is presented. The proposed scheme uses route partitioning with the first-last fit allocation to increase the possibilities of lightpath retuning by avoiding the retuning interference among lightpaths. The first-last fit allocation is used to set a bipartition with one partition allocated with the first fit and the second with the last fit. Lightpaths that are allocated on different partitions cannot interfere with each other. Thus the route partitioning avoids the interferences among lightpaths when retuning. The route partitioning problem is defined as an optimization problem to minimize the total interferences.　Secondly, this thesis presents a defragmentation scheme using path exchanging in 1+1 path protected EONs. For 1+1 path protection, conventional defragmentation approaches consider designated primary and backup paths. This exposes the spectrum to fragmentations induced by the primary lightpaths, which are not to be disturbed in order to achieve hitless defragmentation. The presented path exchanging scheme exchanges the path function of the 1+1 protection with the primary toggling to the backup state while the backup becomes the primary. This allows both lightpaths to be reallocated during the defragmentation process while they work as backup, offering hitless defragmentation. Considering path exchanging, a static spectrum reallocation optimization problem that minimizes the spectrum fragmentation while limiting the number of path exchanging and reallocation operations is defined.　For each of the presented schemes, after the problem is defined as an optimization problem, it is then formulated as an integer linear programming problem (ILP). A decision version of each defined problem is proven NP-complete. A heuristic algorithm is then introduced for large networks, where the ILP used to represent the problem is not tractable. The simulation results show that the proposed schemes outperform the conventional ones and improve the total admissible traffic.電気通信大学201

エラスティック光ネットワークにおけるトラヒック収容性を向上させるための無瞬断デフラグメンテーション

In elastic optical networks (EONs), a major obstacle to using the spectrum resources efficiently is spectrum fragmentation. Much of the research activities in EONs focuses on finding defragmentation methods which remove the spectrum fragmentation. Among the defragmentation methods presented in the literature, hitless defragmentation has been introduced as an approach to limit the spectrum fragmentation in elastic optical networks without traffic disruption. It facilitates the accommodation of new request by creating large spectrum blocks, as it moves active lightpaths (retuning) to fill in gaps left in the spectrum by expired ones.　Nevertheless, hitless defragmentation witnesses limitations for gradual retuning with the conventionally used first fit allocation. The first fit allocation stacks all lightpaths to the lower end of the spectrum. This leads to a large number of lightpaths that need to be retuned and are subject to interfere with each other\u27s retuning. This thesis presents two schemes, which are based on hitless defragmentation, to increase the admissible traffic in EONs.　Firstly, a route partitioning scheme for hitless defragmentation in default EONs is presented. The proposed scheme uses route partitioning with the first-last fit allocation to increase the possibilities of lightpath retuning by avoiding the retuning interference among lightpaths. The first-last fit allocation is used to set a bipartition with one partition allocated with the first fit and the second with the last fit. Lightpaths that are allocated on different partitions cannot interfere with each other. Thus the route partitioning avoids the interferences among lightpaths when retuning. The route partitioning problem is defined as an optimization problem to minimize the total interferences.　Secondly, this thesis presents a defragmentation scheme using path exchanging in 1+1 path protected EONs. For 1+1 path protection, conventional defragmentation approaches consider designated primary and backup paths. This exposes the spectrum to fragmentations induced by the primary lightpaths, which are not to be disturbed in order to achieve hitless defragmentation. The presented path exchanging scheme exchanges the path function of the 1+1 protection with the primary toggling to the backup state while the backup becomes the primary. This allows both lightpaths to be reallocated during the defragmentation process while they work as backup, offering hitless defragmentation. Considering path exchanging, a static spectrum reallocation optimization problem that minimizes the spectrum fragmentation while limiting the number of path exchanging and reallocation operations is defined.　For each of the presented schemes, after the problem is defined as an optimization problem, it is then formulated as an integer linear programming problem (ILP). A decision version of each defined problem is proven NP-complete. A heuristic algorithm is then introduced for large networks, where the ILP used to represent the problem is not tractable. The simulation results show that the proposed schemes outperform the conventional ones and improve the total admissible traffic.電気通信大学201