Providing guaranteed QoS in the hose-modeled VPN

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

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

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

Cicada: Predictive Guarantees for Cloud Network Bandwidth

In cloud-computing systems, network-bandwidth guarantees have been shown to improve predictability of application performance and cost. Most previous work on cloud-bandwidth guarantees has assumed that cloud tenants know what bandwidth guarantees they want. However, application bandwidth demands can be complex and time-varying, and many tenants might lack sufficient information to request a bandwidth guarantee that is well-matched to their needs. A tenant's lack of accurate knowledge about its future bandwidth demands can lead to over-provisioning (and thus reduced cost-efficiency) or under-provisioning (and thus poor user experience in latency-sensitive user-facing applications). We analyze traffic traces gathered over six months from an HP Cloud Services datacenter, finding that application bandwidth consumption is both time-varying and spatially inhomogeneous. This variability makes it hard to predict requirements. To solve this problem, we develop a prediction algorithm usable by a cloud provider to suggest an appropriate bandwidth guarantee to a tenant. The key idea in the prediction algorithm is to treat a set of previously observed traffic matrices as "experts" and learn online the best weighted linear combination of these experts to make its prediction. With tenant VM placement using these predictive guarantees, we find that the inter-rack network utilization in certain datacenter topologies can be more than doubled

Design Issues of Reserved Delivery Subnetworks

In this proposal, we introduce the reserved delivery subnetwork (RDS), a mechanism that can al-low information service providers to deliver more consistent service to their customers without perflow resource reservation. In addition to service performance improvements, reserved delivery sub-networks can also provide protection against network resource attacks. Many applications such asweb content delivery services and virtual private networks can benefit from reserved delivery sub-networks. We address a number of issues with the deployment of RDSs. First, we formulate theconfiguration problem of an RDS as a minimum concave cost network flow problem, where the perunit flow cost decreases as the current flow increases. An approximation heuristic is presented andstudied to solve this configuration problem. Second, we extend our study to the configuration prob-lem of RDSs with multiple sources. We also investigate the configuration problem for subnetworksthat allow load redistribution and load balancing among the sources. In addition, we plan to studyhow to use RDS proxies to regulate the flow of traffic to end users, so as to minimize network delay

Robust network design under polyhedral traffic uncertainty

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

The Robust Network Loading Problem under Hose Demand Uncertainty: Formulation, Polyhedral Analysis, and Computations

Cataloged from PDF version of article.We consider the network loading problem (NLP) under a polyhedral uncertainty description of traffic demands. After giving a compact multicommodity flow formulation of the problem, we state a decomposition property obtained from projecting out the flow variables. This property considerably simplifies the resulting polyhedral analysis and computations by doing away with metric inequalities. Then we focus on a specific choice of the uncertainty description, called the “hose model,” which specifies aggregate traffic upper bounds for selected endpoints of the network. We study the polyhedral aspects of the NLP under hose demand uncertainty and use the results as the basis of an efficient branch-and-cut algorithm. The results of extensive computational experiments on well-known network design instances are reported