28 research outputs found

    A Traffic Engineering Algorithm for Provisioning Virtual Private Networks in the Enhanced Hose Model

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    Abstract: A Virtual Private Network is a logical network established on top of a public packet switched network. To guarantee that quality of service requirements, specified by customers, can be met, the network service provider needs to reserve enough resources on the network and allocate/manage them in an optimal way. Traffic engineering algorithms can be used by the Network Service Provider to establish multiple Virtual Private Networks in an optimal way, while meeting customers' Quality of Service requirements. For delay sensitive network applications, it is critical to meet both bandwidth and delay requirements. In contrast to traditional Virtual Private Network Quality of Service models (customer-pipe model and hose model), which focused only on bandwidth requirements, a new model called the enhanced hose model has been proposed, which considers both bandwidth and delay requirements. However, to the best of our knowledge, thus far, traffic engineering problems associated with establishing multiple enhanced hose model Virtual Private Networks have not been investigated. In this paper, we proposed a novel Virtual Private Network traffic engineering algorithm, called the minimum bandwidth-delay cost tree algorithm to address these problems. According to experimental simulations conducted and reported in our paper, the minimum bandwidth-delay cost tree algorithm can indeed achieved better performance (lower rejection ratios) compared to previous algorithms

    Auto-bandwidth control in dynamically reconfigured hybrid-SDN MPLS networks

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    The proposition of this work is based on the steady evolution of bandwidth demanding technology, which currently and more so in future, requires operators to use expensive infrastructure capability smartly to maximise its use in a very competitive environment. In this thesis, a traffic engineering control loop is proposed that dynamically adjusts the bandwidth and route of flows of Multi-Protocol Label Switching (MPLS) tunnels in response to changes in traffic demand. Available bandwidth is shifted to where the demand is, and where the demand requirement has dropped, unused allocated bandwidth is returned to the network. An MPLS network enhanced with Software-defined Networking (SDN) features is implemented. The technology known as hybrid SDN combines the programmability features of SDN with the robust MPLS label switched path features along with traffic engineering enhancements introduced by routing protocols such as Border Gateway Patrol-Traffic Engineering (BGP-TE) and Open Shortest Path First-Traffic Engineering (OSPF-TE). The implemented mixed-integer linear programming formulation using the minimisation of maximum link utilisation and minimum link cost objective functions, combined with the programmability of the hybrid SDN network allows for source to destination demand fluctuations. A key driver to this research is the programmability of the MPLS network, enhanced by the contributions that the SDN controller technology introduced. The centralised view of the network provides the network state information needed to drive the mathematical modelling of the network. The path computation element further enables control of the label switched path's bandwidths, which is adjusted based on current demand and optimisation method used. The hose model is used to specify a range of traffic conditions. The most important benefit of the hose model is the flexibility that is allowed in how the traffic matrix can change if the aggregate traffic demand does not exceed the hose maximum bandwidth specification. To this end, reserved hose bandwidth can now be released to the core network to service demands from other sites

    Queuing delays in randomized load balanced networks

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    Valiant’s concept of Randomized Load Balancing (RLB), also promoted under the name ‘two-phase routing’, has previously been shown to provide a cost-effective way of implementing overlay networks that are robust to dynamically changing demand patterns. RLB is accomplished in two steps; in the first step, traffic is randomly distributed across the network, and in the second step traffic is routed to the final destination. One of the benefits of RLB is that packets experience only a single stage of routing, thus reducing queueing delays associated with multi-hop architectures. In this paper, we study the queuing performance of RLB, both through analytical methods and packet-level simulations using ns2 on three representative carrier networks. We show that purely random traffic splitting in the randomization step of RLB leads to higher queuing delays than pseudo-random splitting using, e.g., a round-robin schedule. Furthermore, we show that, for pseudo-random scheduling, queuing delays depend significantly on the degree of uniformity of the offered demand patterns, with uniform demand matrices representing a provably worst-case scenario. These results are independent of whether RLB employs priority mechanisms between traffic from step one over step two. A comparison with multi-hop shortest-path routing reveals that RLB eliminates the occurrence of demand-specific hot spots in the network

    The VPN Conjecture Is True

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    CPS-Net: In-Network Aggregation for Synchrophasor Applications

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    Abstract-Synchrophasors are sensors that sample power grids and publish these measurements over a network to a number of grid applications such as voltage monitoring, state estimation, visualization, etc. The sampled data is QoS sensitive and must be delivered reliably with minimal delays to the target applications. However, during network overloads or grid emergencies when the volume of data transmitted is high, it is important to gracefully degrade performance and data stream delivery in an applicationspecific manner. We propose CPS-Net, a flexible 3-layered network architecture that allows application-specified in-network aggregation of synchrophasor data streams during overload. The lowest layer provides basic path-specific QoS while the middle layer provides real-time wide-area publish-subscribe capabilities integrated with traffic engineering of data streams across multiple lower level paths and trees. The top layer provides a distributed stream processing infrastructure for application-specified aggregation functions. During network overload, the lower layer triggers the co-optimization of higher layers and application-specific aggregation of data is performed. The user is presented with a simple stream processing programming model and the details of the network, placement and composition of operators are abstracted away. Initial simulation results, using a voltage stability monitoring smart grid application, show that CPS-Net architecture can gracefully degrade data streams for synchrophasor applications

    The InfoSec Handbook

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    Reducing the Cost of Operating a Datacenter Network

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    Datacenters are a significant capital expense for many enterprises. Yet, they are difficult to manage and are hard to design and maintain. The initial design of a datacenter network tends to follow vendor guidelines, but subsequent upgrades and expansions to it are mostly ad hoc, with equipment being upgraded piecemeal after its amortization period runs out and equipment acquisition is tied to budget cycles rather than changes in workload. These networks are also brittle and inflexible. They tend to be manually managed, and cannot perform dynamic traffic engineering. The high-level goal of this dissertation is to reduce the total cost of owning a datacenter by improving its network. To achieve this, we make the following contributions. First, we develop an automated, theoretically well-founded approach to planning cost-effective datacenter upgrades and expansions. Second, we propose a scalable traffic management framework for datacenter networks. Together, we show that these contributions can significantly reduce the cost of operating a datacenter network. To design cost-effective network topologies, especially as the network expands over time, updated equipment must coexist with legacy equipment, which makes the network heterogeneous. However, heterogeneous high-performance network designs are not well understood. Our first step, therefore, is to develop the theory of heterogeneous Clos topologies. Using our theory, we propose an optimization framework, called LEGUP, which designs a heterogeneous Clos network to implement in a new or legacy datacenter. Although effective, LEGUP imposes a certain amount of structure on the network. To deal with situations when this is infeasible, our second contribution is a framework, called REWIRE, which using optimization to design unstructured DCN topologies. Our results indicate that these unstructured topologies have up to 100-500\% more bisection bandwidth than a fat-tree for the same dollar cost. Our third contribution is two frameworks for datacenter network traffic engineering. Because of the multiplicity of end-to-end paths in DCN fabrics, such as Clos networks and the topologies designed by REWIRE, careful traffic engineering is needed to maximize throughput. This requires timely detection of elephant flows---flows that carry large amount of data---and management of those flows. Previously proposed approaches incur high monitoring overheads, consume significant switch resources, or have long detection times. We make two proposals for elephant flow detection. First, in the Mahout framework, we suggest that such flows be detected by observing the end hosts' socket buffers, which provide efficient visibility of flow behavior. Second, in the DevoFlow framework, we add efficient stats-collection mechanisms to network switches. Using simulations and experiments, we show that these frameworks reduce traffic engineering overheads by at least an order of magnitude while still providing near-optimal performance

    Conception et optimisation robuste des réseaux de télécommunications

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    Les réseaux de communication devenant de plus en plus présents dans nos activités quotidiennes, l'interruption ou une une dégradation significative des services fournis par le réseau deviennent de moins en moins tolérables. Une conception robuste des réseaux de communication, anticipant les pannes éventuelles d'équipements ou les variations du trafic, devient donc de plus en plus nécessaire. Cette thèse traite de plusieurs problèmes de conception et de planification robustes. Nous étudions tout d'abord le problème de la conception et du dimensionnement d'une topologie de communication résiliente et proposons un modèle de conception intégrant les coûts et contraintes des équipements ainsi que de nombreuses contraintes opérationnelles (nœuds potentiels, capacités modulaires, délais de communication). Un algorithme exact et deux approximations sont proposés pour résoudre ce problème. Les résultats numériques montrent que des économies substantielles peuvent être effectuées en intégrant les coûts d'équipements dans la phase amont de la conception. Les variations sur les volumes de trafic sont devenus un des problèmes majeurs auxquels sont confrontés les opérateurs. Il devient ainsi nécessaire d'intégrer explicitement l'incertitude sur la demande en trafic dans les problèmes de planification. Nous étudions deux problèmes d'optimisation robuste du routage : (1) le problème de conception des VPN dans le cadre du modèle hose et (2) le problème d'optimisation des métriques de routage IGP avec incertitude sur la demande. Nous formulons des modèles mathématiques de chacun de ces problèmes et proposons des heuristiques basées sur des techniques de recherche locale pour les résoudre.With communication networks getting more and more present in our daily activities, network outages or even significant degradations of the quality of service become less and less tolerable. This calls for a robust design of communication networks anticipating possible failures or shifts in the expected traffic demands. This thesis addresses several robust design and planning problems arising in the telecommunication area. We first address the problem of designing and dimensioning a survivable network topology. We propose a novel network design model integrating all equipment costs and constraints and including several operational constraints (potential nodes, modular capacities, delay constraints). One exact and two heuristic algorithms are proposed to solve this problem. Numerical results show that significant cost-savings can be achieved when equipment costs are taken into account in the early stages of the design process. The variation in traffic volumes has become one of the most important problems faced by network operators. Designing a network using a single ``busy hour'' traffic matrix more and more strains credibility due to the high volatility of traffic patterns. Thus, there is a need to incorporate demand uncertainty into the network routing problems explicitly. We study two robust route optimization problems: (1) the problem of VPN design under the hose model of demand uncertainty and (2) the problem of link weight optimization under demand uncertainty. We establish mathematical models for both problems and propose efficient approximation algorithms based on local-search techniques to solve them

    Planning Wireless Cellular Networks of Future: Outlook, Challenges and Opportunities

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    Cell planning (CP) is the most important phase in the life cycle of a cellular system as it determines the operational expenditure, capital expenditure, as well as the long-term performance of the system. Therefore, it is not surprising that CP problems have been studied extensively for the past three decades for all four generations of cellular systems. However, the fact that small cells, a major component of future networks, are anticipated to be deployed in an impromptu fashion makes CP for future networks vis-a-vis 5G a conundrum. Furthermore, in emerging cellular systems that incorporate a variety of different cell sizes and types, heterogeneous networks (HetNets), energy efficiency, self-organizing network features, control and data plane split architectures (CDSA), massive multiple input multiple out (MIMO), coordinated multipoint (CoMP), cloud radio access network, and millimetre-wave-based cells plus the need to support Internet of Things (IoT) and device-to-device (D2D) communication require a major paradigm shift in the way cellular networks have been planned in the past. The objective of this paper is to characterize this paradigm shift by concisely reviewing past developments, analyzing the state-of-the-art challenges, and identifying future trends, challenges, and opportunities in CP in the wake of 5G. More specifically, in this paper, we investigate the problem of planning future cellular networks in detail. To this end, we first provide a brief tutorial on the CP process to identify the peculiarities that make CP one of the most challenging problems in wireless communications. This tutorial is followed by a concise recap of past research in CP. We then review key findings from recent studies that have attempted to address the aforementioned challenges in planning emerging networks. Finally, we discuss the range of technical factors that need to be taken into account while planning future networks and the promising research directions that necessitates the paradigm shift to do so
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