Connectivity aware routing - a method for finding bandwidth constrained paths over a variety of network topologies

Multimedia traffic and real-time e-commerce applications can experience quality degradation in traditional networks such as the Internet. These difficulties can be overcome in networks which feature dynamically set up paths with bandwidth and delay guarantees. The problem of selecting such constrained paths is the task of quality of service (QoS) routing. Researchers have proposed several ways of implementing QoS routing, preferring either mechanisms which distribute network load or algorithms which conserve resources. Our previous studies have shown that network connectivity is an important factor when deciding which of these two approaches gives the best performance. In this paper we propose an algorithm, which features both load distribution and resource conservation. It takes a hybrid approach which balances between these two extreme approaches, according to the level of network connectivity. Our simulations indicate that this algorithm offers excellent performance over a than existing algorithms

Design issues in quality of service routing

The range of applications and services which can be successfully deployed in packet-switched networks such as the Internet is limited when the network does nor provide Quality of Service (QoS). This is the typical situation in today's Internet. A key aspect in providing QoS support is the requirement for an optimised and intelligent mapping of customer traffic flows onto a physical network topology. The problem of selecting such paths is the task of QoS routing QoS routing algorithms are intrinsically complex and need careful study before being implemented in real networks. Our aim is to address some of the challenges present m the deployment of QoS routing methods. This thesis considers a number of practical limitations of existing QoS routing algorithms and presents solutions to the problems identified. Many QoS routing algorithms are inherently unstable and induce traffic fluctuations in the network. We describe two new routing algorithms which address this problem The first method - ALCFRA (Adaptive Link Cost Function Routing Algorithm) - can be used in networks with sparse connectivity, while the second algorithm - CAR (Connectivity Aware Routing) - is designed to work well in other network topologies. We also describe how to ensure co-operative interaction of the routing algorithms in multiple domains when hierarchial routing is used and also present a solution to the problems of how to provide QoS support m a network where not all nodes are QoS-aware. Our solutions are supported by extensive simulations over a wide range of network topologies and their performance is compared to existing algorithms. It is shown that our solutions advance the state of the art in QoS routing and facilitate the deployment of QoS support in tomorrow's Internet

EGOIST: Overlay Routing Using Selfish Neighbor Selection

A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into an existing overlay, and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are analytically tractable, especially via game-theoretic analysis. In this paper, we unify these two thrusts by using insights gleaned from novel, realistic theoretic models in the design of Egoist – a prototype overlay routing system that we implemented, deployed, and evaluated on PlanetLab. Using measurements on PlanetLab and trace-based simulations, we demonstrate that Egoist's neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, we demonstrate that Egoist is competitive with an optimal, but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overhead. Finally, we discuss some of the potential benefits Egoist may offer to applications.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CISE/CNS 0524477, CNS/NeTS 0520166, CNS/ITR 0205294; CISE/EIA RI 0202067; CAREER 04446522); European Commission (RIDS-011923

Network Aware Compute and Memory Allocation in Optically Composable Data Centres with Deep Reinforcement Learning and Graph Neural Networks

Resource-disaggregated data centre architectures promise a means of pooling resources remotely within data centres, allowing for both more flexibility and resource efficiency underlying the increasingly important infrastructure-as-a-service business. This can be accomplished by means of using an optically circuit switched backbone in the data centre network (DCN); providing the required bandwidth and latency guarantees to ensure reliable performance when applications are run across non-local resource pools. However, resource allocation in this scenario requires both server-level \emph{and} network-level resource to be co-allocated to requests. The online nature and underlying combinatorial complexity of this problem, alongside the typical scale of DCN topologies, makes exact solutions impossible and heuristic based solutions sub-optimal or non-intuitive to design. We demonstrate that \emph{deep reinforcement learning}, where the policy is modelled by a \emph{graph neural network} can be used to learn effective \emph{network-aware} and \emph{topologically-scalable} allocation policies end-to-end. Compared to state-of-the-art heuristics for network-aware resource allocation, the method achieves up to $20\%$ higher acceptance ratio; can achieve the same acceptance ratio as the best performing heuristic with $3\times$ less networking resources available and can maintain all-around performance when directly applied (with no further training) to DCN topologies with $10^2\times$ more servers than the topologies seen during training.Comment: 10 pages + 1 appendix page, 8 figure

Energy-aware routing techniques for software-defined networks

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

Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]

The key goal in optical network design is to introduce intelligence in the network and deliver capacity when and where it is needed. It is critical to understand the dependencies between network topology properties and the achievable network throughput. Real topology data of optical networks are scarce, and often large sets of synthetic graphs are used to evaluate their performance including proposed routing algorithms. These synthetic graphs are typically generated via the Erdos–Renyi (ER) and Barabasi–Albert (BA) models. Both models lead to distinct structural properties of the synthetic graphs, including degree and diameter distributions. In this paper, we show that these two commonly used approaches are not adequate for the modeling of real optical networks. The structural properties of optical core networks are strongly influenced by internodal distances. These, in turn, impact the signal-to-noise ratio, which is distance dependent. The analysis of optical network performance must, therefore, include spatial awareness to better reflect the graph properties of optical core network topologies. In this work, a new variant of the BA model, taking into account the internodal signal-to-noise ratio, is proposed. It is shown that this approach captures both the effects of graph structure and physical properties to generate better networks than traditional methods. The proposed model is compared to spatially agnostic approaches, in terms of the wavelength requirements and total information throughput, and highlights how intelligent choices can significantly increase network throughputs while saving fiber