79 research outputs found

    Shortest Path versus Multi-Hub Routing in Networks with Uncertain Demand

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    We study a class of robust network design problems motivated by the need to scale core networks to meet increasingly dynamic capacity demands. Past work has focused on designing the network to support all hose matrices (all matrices not exceeding marginal bounds at the nodes). This model may be too conservative if additional information on traffic patterns is available. Another extreme is the fixed demand model, where one designs the network to support peak point-to-point demands. We introduce a capped hose model to explore a broader range of traffic matrices which includes the above two as special cases. It is known that optimal designs for the hose model are always determined by single-hub routing, and for the fixed- demand model are based on shortest-path routing. We shed light on the wider space of capped hose matrices in order to see which traffic models are more shortest path-like as opposed to hub-like. To address the space in between, we use hierarchical multi-hub routing templates, a generalization of hub and tree routing. In particular, we show that by adding peak capacities into the hose model, the single-hub tree-routing template is no longer cost-effective. This initiates the study of a class of robust network design (RND) problems restricted to these templates. Our empirical analysis is based on a heuristic for this new hierarchical RND problem. We also propose that it is possible to define a routing indicator that accounts for the strengths of the marginals and peak demands and use this information to choose the appropriate routing template. We benchmark our approach against other well-known routing templates, using representative carrier networks and a variety of different capped hose traffic demands, parameterized by the relative importance of their marginals as opposed to their point-to-point peak demands

    Robust network design under polyhedral traffic uncertainty

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    Ankara : The Department of Industrial Engineering and The Institute of Engineering and Science of Bilkent Univ., 2007.Thesis (Ph.D.) -- Bilkent University, 2007.Includes bibliographical references leaves 160-166.In this thesis, we study the design of networks robust to changes in demand estimates. We consider the case where the set of feasible demands is defined by an arbitrary polyhedron. Our motivation is to determine link capacity or routing configurations, which remain feasible for any realization in the corresponding demand polyhedron. We consider three well-known problems under polyhedral demand uncertainty all of which are posed as semi-infinite mixed integer programming problems. We develop explicit, compact formulations for all three problems as well as alternative formulations and exact solution methods. The first problem arises in the Virtual Private Network (VPN) design field. We present compact linear mixed-integer programming formulations for the problem with the classical hose traffic model and for a new, less conservative, robust variant relying on accessible traffic statistics. Although we can solve these formulations for medium-to-large instances in reasonable times using off-the-shelf MIP solvers, we develop a combined branch-and-price and cutting plane algorithm to handle larger instances. We also provide an extensive discussion of our numerical results. Next, we study the Open Shortest Path First (OSPF) routing enhanced with traffic engineering tools under general demand uncertainty with the motivation to discuss if OSPF could be made comparable to the general unconstrained routing (MPLS) when it is provided with a less restrictive operating environment. To the best of our knowledge, these two routing mechanisms are compared for the first time under such a general setting. We provide compact formulations for both routing types and show that MPLS routing for polyhedral demands can be computed in polynomial time. Moreover, we present a specialized branchand-price algorithm strengthened with the inclusion of cuts as an exact solution tool. Subsequently, we compare the new and more flexible OSPF routing with MPLS as well as the traditional OSPF on several network instances. We observe that the management tools we use in OSPF make it significantly better than the generic OSPF. Moreover, we show that OSPF performance can get closer to that of MPLS in some cases. Finally, we consider the Network Loading Problem (NLP) under a polyhedral uncertainty description of traffic demands. After giving a compact multicommodity formulation of the problem, we prove an unexpected decomposition property obtained from projecting out the flow variables, considerably simplifying the resulting polyhedral analysis and computations by doing away with metric inequalities, an attendant feature of most successful algorithms on NLP. Under the hose model of feasible demands, we study the polyhedral aspects of NLP, used as the basis of an efficient branch-and-cut algorithm supported by a simple heuristic for generating upper bounds. We provide the results of extensive computational experiments on well-known network design instances.Altın, AyşegülPh.D

    Routing algorithm for provisioning symmetric virtual private networks in the hose model

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    A virtual private network (VPN) is a private data network where remote sites are connected over a shared provider network. In order to provide secure communications between customer sites, predetermined paths are used to forward data packets. To support quality of service (QoS), bandwidth has to be reserved on these paths. Then, finding appropriate paths in order to optimize the bandwidth used becomes an important problem. In this paper, we study the routing problem of VPNs under the hose model, where VPN endpoints specify the maximum bandwidth they need in sending and receiving data. Some previous works considered the problem under the assumption that all links have infinite capacities. We remove this constraint in our studies and develop enhancement to existing algorithms. Our simulation results show that our algorithm works very well in networks where link capacities are tight. © 2005 IEEE.published_or_final_versio

    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

    Providing guaranteed QoS in the hose-modeled VPN

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    With the development of the Internet, Internet service providers (ISPs) are required to offer revenue-generating and value-added services instead of only providing bandwidth and access services. Virtual Private Network (VPN) is one of the most important value-added services for ISPs. The classical VPN service is provided by implementing layer 2 technologies, either Frame Relay (FR) or Asynchronous Transfer Mode (ATM). With FR or ATM, virtual circuits are created before data delivery. Since the bandwidth and buffers are reserved, the QoS requirements can be naturally guaranteed. In the past few years, layer 3 VPN technologies are widely deployed due to the desirable performance in terms of flexibility, scalability and simplicity. Layer 3 VPNs are built upon IP tunnels, e.g., by using PPTP, L2TP or IPSec. Since IP is best-of-effort in nature, the QoS requirement cannot be guaranteed in layer 3 VPNs. Actually, layer 3 VPN service can only provide secure connectivity, i.e., protecting and authenticating IP packets between gateways or hosts in a VPN. Without doubt, with more applications on voice, audio and video being used in the Internet, the provision of QoS is one of the most important parts of the emerging services provided by ISPs. An intriguing question is: Is it possible to obtain the best of both layer 2 and 3 VPN? Is it possible to provide guaranteed or predictable QoS, as in layer 2 VPNs, while maintaining the flexibility and simplicity in layer 3 VPN? This question is the starting point of this study. The recently proposed hose model for VPN possesses desirable properties in terms of flexibility, scalability and multiplexing gain. However, the classic fair bandwidth allocation schemes and weighted fair queuing schemes raise the issue of low overall utilization in this model. A new fluid model for provider-provisioned virtual private network (PPVPN) is proposed in this dissertation. Based on the proposed model, an idealized fluid bandwidth allocation scheme is developed. This scheme is proven, analytically, to have the following properties: 1) maximize the overall throughput of the VPN without compromising fairness; 2) provide a mechanism that enables the VPN customers to allocate the bandwidth according to their requirements by assigning different weights to different hose flows, and thus obtain the predictable QoS performance; and 3) improve the overall throughput of the ISPs\u27 network. To approximate the idealized fluid scheme in the real world, the 2-dimensional deficit round robin (2-D DRR and 2-D DRR+) schemes are proposed. The integration of the proposed schemes with the best-effort traffic within the framework of virtual-router-based VPN is also investigated. The 2-D DRR and 2-D DER-+ schemes can be extended to multi-dimensional schemes to be employed in those applications which require a hierarchical scheduling architecture. To enhance the scalability, a more scalable non-per-flow-based scheme for output queued switches is developed as well, and the integration of this scheme within the framework of the MPLS VPN and applications for multicasting traffics is discussed. The performance and properties of these schemes are analyzed

    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

    Capacity-efficient and Uncertainty-resilient Backbone Network Planning with Hose

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    Bandwidth requirements for protected vpns in the hose model

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    Provisioning virtual private networks under traffic uncertainty

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    We investigate a network design problem under traffic uncertainty that arises when provisioning Virtual Private Networks (VPNs): given a set of terminals that must communicate with one another, and a set of possible traffic matrices, sufficient capacity has to be reserved on the links of the large underlying public network to support all possible traffic matrices while minimizing the total reservation cost. The problem admits several versions depending on the desired topology of the reserved links, and the nature of the traffic data uncertainty. We present compact linear mixed-integer programming formulations for the problem with the classical hose traffic model and for a less conservative robust variant relying on the traffic statistics that are often available. These flow-based formulations allow us to solve optimally medium-to-large instances with commercial MIP solvers. We also propose a combined branch-and-price and cutting-plane algorithm to tackle larger instances. Computational results obtained for several classes of instances are reported and discussed. © 2006 Wiley Periodicals, Inc
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