Abstract

In this paper, we propose an AIMD-based TCP load balancing architecture in a backbone network where TCP flows are split between two explicitly routed paths, namely the primary and the secondary paths. We propose that primary paths have strict priority over the secondary paths with respect to packet forwarding and both paths are rate-controlled using ECN marking in the core and AIMD rate adjustment at the ingress nodes. We call this technique "prioritized AIMD". The buffers maintained at the ingress nodes for the two alternative paths help us predict the delay difference between the two paths which forms the basis for deciding on which path to forward a new-coming flow. We provide a simulation study for a large mesh network to demonstrate the efficiency of the proposed approach in terms of the average per-flow goodput and byte blocking rates. © Springer-Verlag Berlin Heidelberg 2004.

Abstract

This work seeks to improve the energy efficiency of backbone networks by automatically managing the paths of network flows to reduce the over-provisioning. Compared to numerous works in this field, we stand out by focusing on low computational complexity and smooth deployment of the proposed solution in the context of Software Defined Networks (SDN). To ensure that we meet these requirements, we validate the proposed solutions on a network testbed built for this purpose. Moreover, we believe that it is indispensable for the research community in computer science to improve the reproducibility of experiments. Thus, one can reproduce most of the results presented in this thesis by following a couple of simple steps. In the first part of this thesis, we present a framework for putting links and line cards into sleep mode during off-peak periods and rapidly bringing them back on when more network capacity is needed. The solution, which we term ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE), was implemented using state-of-art dynamic graph algorithms. STREETE achieves execution times of tens of milliseconds on a 50-node network. The approach was also validated on a testbed using the ONOS SDN controller along with OpenFlow switches. We compared our algorithm against optimal solutions obtained via a Mixed Integer Linear Programming (MILP) model to demonstrate that it can effectively prevent network congestion, avoid turning-on unneeded links, and provide excellent energy-efficiency. The second part of this thesis studies solutions for maximizing the utilization of existing components to extend the STREETE framework to workloads that are not very well handled by its original form. This includes the high network loads that cannot be routed through the network without a fine-grained management of the flows. In this part, we diverge from the shortest path routing, which is traditionally used in computer networks, and perform a particular load balancing of the network flows. In the last part of this thesis, we combine STREETE with the proposed load balancing technique and evaluate the performance of this combination both regarding turned-off links and in its ability to keep the network out of congestion. After that, we use our network testbed to evaluate the impact of our solutions on the TCP flows and provide an intuition about the additional constraints that must be considered to avoid instabilities due to traffic oscillations between multiple paths.; Ce travail a pour but d'améliorer l'efficacité énergétique des réseaux de cœur en éteignant un sous-ensemble de liens par une approche SDN (Software Defined Network). Nous nous différencions des nombreux travaux de ce domaine par une réactivité accrue aux variations des conditions réseaux. Cela a été rendu possible grâce à une complexité calculatoire réduite et une attention particulière au surcoût induit par les échanges de données. Pour valider les solutions proposées, nous les avons testées sur une plateforme spécialement construite à cet effet.Dans la première partie de cette thèse, nous présentons l'architecture logicielle ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE). Le cœur de la solution repose sur un re-routage dynamique du trafic en fonction de la charge du réseau dans le but d'éteindre certains liens peu utilisés. Cette solution utilise des algorithmes de graphes dynamiques pour réduire la complexité calculatoire et atteindre des temps de calcul de l'ordre des millisecondes sur un réseau de 50 nœuds. Nos solutions ont aussi été validées sur une plateforme de test comprenant le contrôleur SDN ONOS et des commutateurs OpenFlow. Nous comparons nos algorithmes aux solutions optimales obtenues grâce à des techniques de programmation linéaires en nombres entiers et montrons que le nombre de liens allumés peut être efficacement réduit pour diminuer la consommation électrique tout en évitant de surcharger le réseau.Dans la deuxième partie de cette thèse, nous cherchons à améliorer la performance de STREETE dans le cas d’une forte charge, qui ne peut pas être écoulée par le réseau si des algorithmes de routages à plus courts chemins sont utilisés. Nous analysons des méthodes d'équilibrage de charge pour obtenir un placement presque optimal des flux dans le réseau.Dans la dernière partie, nous évaluons la combinaison des deux techniques proposées précédemment : STREETE avec équilibrage de charge. Ensuite, nous utilisons notre plateforme de test pour analyser l'impact de re-routages fréquents sur les flux TCP. Cela nous permet de donner des indications sur des améliorations à prendre en compte afin d'éviter des instabilités causées par des basculements incontrôlés des flux réseau entre des chemins alternatifs. Nous croyons à l'importance de fournir des résultats reproductibles à la communauté scientifique. Ainsi, une grande partie des résultats présentés dans cette thèse peuvent être facilement reproduits à l'aide des instructions et logiciels fournis.

Abstract

The principle of load balancing is to distribute the data load more evenly over the network in order to increase the network performance and efficiency. With dynamic load balancing the routing is undated at certain intervals. This thesis was developed to evaluate load balancing methods in the IP-network of TeliaSonera.Load balancing using short path routing, bottleneck load balancing and load balancing using MPLS have been evaluated. Short path routing is a flow sharing technique that allows routing on paths other than the shortest one. Load balancing using short path routing is achieved by dynamic updates of the link weights. Bottleneck is in its nature a dynamic load balancing algorithm. Unlike load balancing using short path routing it updates the flow sharing, not the metrics. The algorithm uses information about current flow sharing and link loads to detect bottlenecks within the network. The information is used to calculate new flow sharing parameters. When using MPLS, one or more complete routing paths (LSPs) are defined at each edge LSR before sending any traffic. MPLS brings the ability to perform flow sharing by defining the paths to be used and how the outgoing data load is to be shared among these. The model has been built from data about the network supplied by TeliaSonera. The model consists of a topology part, a traffic part, a routing part and cost part. The traffic model consists of a OD demand matrix. The OD demand matrix has been estimated from collected link loads. This was done with estimation models; the gravity model and an optimisation model. The algorithms have been analysed at several scenarios; normal network, core node failure, core link failure and DWDM system failure. A cost function, where the cost increases as the link load increases has been used to evaluate the algorithms. The signalling requirements for implementation of the load balancing algorithm have also been investigated.

Abstract

In telecommunication networks based on the current Ethernet technology, routing of traffic demands is based on multiple spanning trees: the network operator configures different routing spanning trees and assigns each demand to be routed in one of the selected spanning trees. A major optimization issue in this solution is the combined determination of (i) a set of appropriate spanning trees, and (ii) assignment of demands to the trees, in order to achieve an optimal load balancing on the links of the network. In this paper we consider models and solving techniques for lexicographical optimization of two load balancing objective functions. The first objective is the min-max optimization of the n worst link loads (with n up to the total number of network links), and the second objective is the minimization of the average link load (when n is smaller than the total number of network links). Besides exact methods, a heuristic technique that can compute both feasible solutions and lower bounds for the addressed optimization problem is proposed. Finally, we discuss effectiveness of different solution using results of a numerical study of realistic case studies. The authors wish to thank Michal Zagozdzon for the fruitful discussions on the adaptation of the max-min fairness solution methods to the problems addressed in this paper. This work has been done under the Joint Specific Project METRO-ETHERNET within the FP7 Network of Excellence "Euro NF". The Portuguese coauthors have been partially funded by FCT (Fundacao para a Ciencia e a Tecnologia) through project PTDC/EIA/64772/2006 and through the post-doc grant SFRH/BPD/41581/2007 of D. Santos. The co-authors from Warsaw University of Technology have been partially funded by the Polish Ministry of Science and Higher Education (MNiSW, grant no. N517 397334 "Optimization Models for NGI Core Networks"). M. Pioro has been also supported by the Swedish Research Council (Vetenskapsradet, grant no. 621-2006-5509 "Modeling and Design of Core Internet Networks").

Abstract

In recent years there has been a large increase in the connection of photovoltaic generators to the low voltage distribution network in urban residential areas. In the future, it is predicted that this trend will continue and be accompanied with a rise in the uptake and connection of electric vehicles and heat pumps. Recently, monitoring trials have found widespread current unbalance in the feeders that transmit electrical energy to and from these urban residential areas. This unbalance is likely to be accentuated by the gradual and piecemeal uptake of the aforementioned devices. The combined impact of the changes and present day unbalance is likely to be more frequent thermal and voltage constraint violations unless new strategies are adopted to manage the flow of electrical energy. Here, a novel device named the 'phase switcher' that has no customer compliance requirements is proposed as a new tool for distribution network operators to manage the thermal and voltage constraints of cables. The phase switcher is shown to unlock cable ampacity and maximise voltage headroom and it achieves this through phase balancing in real time. A centralised local feeder controller is simulated to employ dynamic and scheduled phase switcher control algorithms on a real network model, and it's ability to unlock cable ampacity and reduce cable losses is quantified. Also, a small model based controller algorithm is presented and shown to perform almost as well as others despite having a very limited sensing and communication system requirement. Phase switchers are also quantified for their ability to increase feeder voltage headroom when employed to improve the balance of photovoltaic distributed generators across phases. To this end, an exhaustive offline photovoltaic capacity prediction technique is documented which shows that when phase switchers are placed explicitly to a known photovoltaic installation scenario, an almost linear relationship exists between the penetration level and maximum node voltage when PSs or phase conductor rejointing is considered as an option for implementation. Finally, a fast feeder assessment algorithm is detailed that is found to be better and more robust at estimating extreme maximum and minimum photovoltaic penetration level scenarios that cause over-voltage. All the work is presented within a new general mathematical framework that facilitates formulation of the problem and calculation of device phase connections for networks containing phase switchers.

Abstract

Cataloged from PDF version of article. In this thesis, we propose a multi-path TCP load balancing traffic engineering methodology in IP networks. In this architecture, TCP traffic is split at the flow level between the primary and secondary paths in order to prevent the adverse effect of packet reordering on TCP performance occuring in packet-based load balancing schemes. Traffic splitting is done by using a random early rerouting algorithm that controls the queuing delay difference between the two alternative paths. We apply strict priority queuing in order to prevent the knock-on effect that arises when primary and secondary path queues have equal priority. Probe packets are used for getting congestion information from the output queues of links along the paths and AIMD (Additive Increase/Multiplicative Decrease) based rate control using this congestion information is applied to the traffic routed over these paths. We compare two queuing architectures, namely first-in-first-out (FIFO) and strict priority. We show through simulations that strict priority queuing has higher performance, it is relatively more robust than FIFO queuing and it eliminates the knock-on effect. We show that avoiding packet reordering by flow level splitting significantly improves the performance of long flows. The capabilities of ns-2 simulator is improved bu using optimizations in order to apply the simulator to relatively large networks. We show that incorporating a-priori knowledge of the traffic demand matrix into the proposed architecture can further improve its performance in terms of load balancing and byte rejection ratio. Alparslan, Onur M.S.

Abstract

International audience; Intelligent transportation clouds could provideServices such as autonomy, mobility, decision support and thestandard development Environment for traffic managementstrategies, and so on. With mobile agent technology, anurban-traffic management system based on Agent-BasedDistributed and Adaptive Platforms for Transportation Systems(Adapts) is both feasible and effective. However, the large-scaleuse of mobile agents will lead to the emergence of a complex,powerful organization layer that requires enormous computingand power resources. To deal with this problem, we propose aprototype urban-traffic management system using multi agentbased intelligent traffic clouds. Cloud computing can help us tohandle the large amount of storage resources and masstransportation of data effectively and efficiently.

Abstract

International audience; In dense wireless networks, inter-cell interference highly limits the capacity and quality of service perceived by users. Previous work has shown that approaches based on frequency reuse provide important capacity gains. We model a wireless network with Inter-Cell Interference Coordination (ICIC) at the flow level where users arrive and depart dy- namically, in order to optimize quality of service indicators perceivable by users such as file transfer time for elastic traffic. We propose an algorithm to tune the parameters of ICIC schemes automatically based on measurements. The convergence of the algorithm to a local optimum is proven, and a heuristic to improve its convergence speed is given. Numerical experiments show that the distance between local optima and the global optimum is very small, and that the algorithm is fast enough to track changes in traffic on the time scale of hours. The proposed algorithm can be implemented in a distributed way with very small signaling load.

Abstract

Link State routing protocols, such as Open Shortest Path First (OSPF), are widely applied to intra-domain routing in todays IP networks. They provide a good scalability without lost of simplicity. A router running OSPF distributes traf- fic uniformly over Equal-cost Multi-path (ECMP), enabling a better distribution of packets among the existent links. More recently, other load balancing strategies, that consider non even splitting of traffic, have been put forward. Such is the case of the Distributed Exponentially-weighted Flow SpliTting (DEFT), that enables traf- fic to be directed through non equal-cost multi-paths, while preserving the OSPF simplicity. As the optimal link weight computation is known to be NP-hard, intel- ligence heuristics are particularly suited to address this optimization problem. In this context, this work compares the solutions provided by Evolutionary Al- gorithms (EA) for the weight setting problem, considering both ECMP and DEFT load balancing alternatives. In addition to a single objective network congestion optimization problem, both load balancing schemes are also applied to a multi- objective optimization approach able to attain routing configurations resilient to traffic demand variations. COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT -Fundação para a Ciência e Tecnologia within the ProjectScope: UID/CEC/00319/2013.