3,005 research outputs found

    Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining

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    Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.Comment: Extended version of submitted paper - v7 - July 201

    Chained Orchestrator Algorithm for RAN-Slicing Resource Management: A Contribution to Ultra-Reliable 6G Communications

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    The exponentially growing trend of Internet-connected devices and the development of new applications have led to an increase in demands and data rates flowing over cellular networks. If this continues to have the same tendency, the classification of 5G services must evolve to encompass emerging communications. The advent of the 6G Communications concept takes this into account and raises a new classification of services. In addition, an increase in network specifications was established. To meet these new requirements, enabling technologies are used to augment and manage Radio Access Network (RAN) resources. One of the most important mechanisms is the logical segmentation of the RAN, i.e. RAN-Slicing. In this study, we explored the problem of resource allocation in a RAN-Slicing environment for 6G ecosystems in depth, with a focus on network reliability. We also propose a chained orchestrator algorithm for dynamic resource management that includes estimation techniques, inter-slice resource sharing and intra-slice resource assignment. These mechanisms are applied to new types of services in the future generation of cellular networks to improve the network latency, capacity and reliability. The numerical results show a reduction in blocked connections of 38.46% for eURLLC type services, 21.87% for feMBB services, 12.5% for umMTC, 11.86% for ELDP and 11.76% for LDHMC.Spanish National Program of Research, Development, Innovation, under Grant RTI2018-102002-A-I00Junta de Extremadura under Project IB18003 and Grant GR2109

    Copying and Evolution of Neuronal Topology

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    We propose a mechanism for copying of neuronal networks that is of considerable interest for neuroscience for it suggests a neuronal basis for causal inference, function copying, and natural selection within the human brain. To date, no model of neuronal topology copying exists. We present three increasingly sophisticated mechanisms to demonstrate how topographic map formation coupled with Spike-Time Dependent Plasticity (STDP) can copy neuronal topology motifs. Fidelity is improved by error correction and activity-reverberation limitation. The high-fidelity topology-copying operator is used to evolve neuronal topologies. Possible roles for neuronal natural selection are discussed

    Energy-aware routing techniques for software-defined networks

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    Achieving energy efficiency has recently become a key topic of networking research due to the ever-increasing power consumption and CO2 emissions generated by large data networks. This problem is becoming even more concerning and challenging given the drastic traffic increase expected over the next few years. However, the use of efficient energy-aware strategies could overturn this situation reducing the electricity consumption of Internet data transmission networks, as well as contributing to mitigate the environmental impact of other sectors. The existence of redundant network elements with high capacities is a common design practice in current network infrastructures in order to face suddenly failures or peak traffic flows. However, these additional resources remain either unused or barely used most of the time leading to an undesired energy waste. Therefore, putting into sleep mode (i.e. a low-power state) unused elements is an effective and widely-accepted strategy to decrease the consumption of data networks. In this context, SDN can be seen as an attractive solution to achieve the long-awaited energy efficiency in current communications systems, since they allow a flexible programmability suitable for this problem. This doctoral thesis tackles the problem of optimizing the power consumption in SDN through the design of energy-aware routing techniques that minimize the number of network elements required to satisfy an incoming traffic load. Different from existing related works, we focus on optimizing energy consumption in SDN with in-band control traffic in order to close this important gap in the literature and provide solutions compatible with operational backbone networks. Complementing the general aim of improving the energy efficiency in SDN, this research is also intended to cover important related features such as network performance, QoS requirements and real-time operation. Accordingly, this study gives a general perspective about the use of energy efficient routing techniques, which cover integrated routing considerations for the data and control plane traffic in SDN. By using realistic input data, significant values of switched-off links and nodes are reached, which demonstrates the great opportunity for saving energy given by our proposals. The obtained results have also validated the intrinsic trade-off between environmental and performance concerns, considering several performance indicators. These findings confirm that energy-aware routing schemes should be designed considering specific traffic requirements and performance metric bounds. Moreover, it is shown that jointly considering QoS requirements and energy awareness is an effective approach to improve, not only the power consumption, but the performance on critical parameters such as control traffic delay and blocking rate. Similarly, the proposed dynamic traffic allocation with congestion-aware rerouting is able to handle demanding traffic arrival without degrading the performance of higher priority traffic. In general, our proposals are fine-grained, easy to implement and quite balanced and effective in their results looking for a suitable and readily deployment in real-world SDN scenarios. Therefore, the conducted research and contributions reported through this document not only add to what is known about the potential of energy-aware routing techniques, but also stand as a valuable solution on the road to a sustainable networking.L'assoliment de l'eficiència energètica s'ha convertit recentment en un tema clau de recerca de xarxes a causa dels creixents nivells de consum d'energia i emissions de CO2 generats per les xarxes de dades. Aquest problema es torna cada vegada més preocupant i desafiant, donat el dràstic augment del trànsit esperat en els propers anys. No obstant això, l'ús d'estratègies energètiques eficients podria invertir aquesta situació, reduint el consum d'electricitat de les xarxes de dades d'Internet i contribuint a mitigar l'impacte ambiental d'altres sectors. L'existència d'elements de xarxa redundants i amb grans capacitats és una pràctica de disseny habitual en les infraestructures de xarxes actuals per afrontar fallades sobtades o fluxos de trànsit més elevats. Tanmateix, aquests recursos addicionals romanen poc o gens utilitzats la major part del temps, generant un desaprofitament d'energia no desitjat. Per tant, posar en mode de repòs (és a dir, un estat de baixa potència) elements no utilitzats és una estratègia efectiva i àmpliament acceptada per disminuir el consum en xarxes de dades. En aquest context, les xarxes definides per programari (SDN) es poden considerar una solució atractiva per aconseguir l'esperada eficiència energètica en els sistemes de comunicacions actuals, ja que permeten una flexible programabilitat idònia per a aquest problema. Aquesta tesi doctoral aborda el problema d'optimitzar el consum d'energia en SDN a través del disseny de tècniques d'encaminament conscients de l'energia que minimitzen la quantitat d'elements de xarxa necessaris per satisfer una càrrega de trànsit entrant. Diferent dels treballs existents, aquesta tesi es centra a optimitzar el consum d'energia en SDN amb el control de tràfic dins de banda per tancar aquesta important bretxa en la literatura i proporcionar solucions compatibles amb xarxes troncals operatives. Complementant l'objectiu general de millorar l'eficiència energètica en SDN, aquesta recerca també pretén cobrir altres importants paràmetres relacionats, com ara el rendiment de la xarxa, els requisits de qualitat de servei (QoS) i el funcionament en temps real. En conseqüència, aquest estudi ofereix una perspectiva general sobre l'ús de tècniques d'encaminament eficients energèticament, que contempla consideracions integrades per al tràfic de dades i del pla de control en SDN. Prenent dades d'entrada realistes, es van aconseguir desconnectar significatives quantitats d'enllaços i nodes, la qual cosa demostra la gran oportunitat d'estalvi d'energia que ofereixen les nostres propostes. Els resultats obtinguts també validen el estret compromís entre les preocupacions ambientals i les qüestions de rendiment de la xarxa, considerant diversos indicadors de rendiment. Aquests resultats confirmen que els esquemes d'encaminament conscients de l'energia s'han de dissenyar tenint en compte els requisits de tràfic específics i els límits desitjats de les mètriques de rendiment. A més, es demostra que, considerant conjuntament els requisits de QoS i de l'energia necessària, és un enfocament eficaç per millorar, no només el consum d'energia, sinó també el rendiment en paràmetres crítics, com la latència del tràfic de control i la probabilitat de bloqueig. De manera semblant, l'assignació dinàmica de tràfic proposta, amb re-encaminament conscient de la congestió, permet gestionar grans volums de trànsit sense degradar el rendiment de les demandes de major prioritat. En general, les nostres propostes són precises, fàcils d'implementar i bastant equilibrades i efectives en els seus resultats, buscant un desplegament adequat i fàcil en escenaris pràctics de SDN. Per tant, la recerca realitzada i les contribucions contingudes en aquest document no només afegeixen el que es coneix sobre el potencial de les tècniques d'encaminament conscients de l'energia, sinó que també representen una valuosa solució en el camí cap a una xarxa sostenibl

    Wavelength reconfigurability for next generation optical access networks

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    Next generation optical access networks should not only increase the capacity but also be able to redistribute the capacity on the fly in order to manage larger variations in traffic patterns. Wavelength reconfigurability is the instrument to enable such capability of network-wide bandwidth redistribution since it allows dynamic sharing of both wavelengths and timeslots in WDM-TDM optical access networks. However, reconfigurability typically requires tunable lasers and tunable filters at the user side, resulting in cost-prohibitive optical network units (ONU). In this dissertation, I propose a novel concept named cyclic-linked flexibility to address the cost-prohibitive problem. By using the cyclic-linked flexibility, the ONU needs to switch only within a subset of two pre-planned wavelengths, however, the cyclic-linked structure of wavelengths allows free bandwidth to be shifted to any wavelength by a rearrangement process. Rearrangement algorithm are developed to demonstrate that the cyclic-linked flexibility performs close to the fully flexible network in terms of blocking probability, packet delay, and packet loss. Furthermore, the evaluation shows that the rearrangement process has a minimum impact to in-service ONUs. To realize the cyclic-linked flexibility, a family of four physical architectures is proposed. PRO-Access architecture is suitable for new deployments and disruptive upgrades in which the network reach is not longer than 20 km. WCL-Access architecture is suitable for metro-access merger with the reach up to 100 km. PSB-Access architecture is suitable to implement directly on power-splitter-based PON deployments, which allows coexistence with current technologies. The cyclically-linked protection architecture can be used with current and future PON standards when network protection is required

    Stochastische Analyse und lernbasierte Algorithmen zur Ressourcenbereitstellung in optischen Netzwerken

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    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
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