Conference Paper

# iREX: Inter-Domain Resource Exchange Architecture

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## Abstract

This paper introduces the inter-domain Resource Exchange (iREX) architecture for the automated deployment of fault tolerant end to end (E2E) inter-domain (ID) quality of service (QoS) policy among resource user and resource provider Internet Service Providers (ISPs). iREX uses economics and fully distributed mechanisms to empower domains to self-manage the deployment of E2E ID QoS policy. In iREX, resource user domains select and reserve ID QoS resources to form E2E ID QoS policy while resource provider domains provide information about available ID QoS resources and support the deployment of policies. iREX promotes accountability by enabling the establishment of bilateral agreements between a resource user ISP and all resource provider ISPs, and promotes congestion- avoidance by enabling a distributed resource selection process that selects the least congested ID deployment path. With iREX, domains cooperate to deploy ID QoS policy while maintaining their autonomy at all times. Simulation results show that iREX blocks fewer reservations and causes less congestion than the existing method, and that iREX is able to recover from faults.

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... This problem arises in an inter-domain resource market in which multiple service providers offer network resources (capacity) to enable Internet traffic with specific Quality of Service (QoS) constraints, see for example Yahaya and Suda [88] and Yahaya, Harks, and Suda [90]. In such a market, each service provider advertises prices for resources that he wants to sell. ...
... In this regard, a novel inter-domain resource exchange architecture (iREX) for the automated deployment of Internet traffic with QoS requirements has been proposed by Yahaya and Suda [88,89] and Yahaya, Harks, and Suda [90]. The iREX architecture is based on the "Posted Price Competition" economic model in which providers independently choose prices that are publicly communicated to resource consumers on a take-it-or-leave-it basis, see Abbink [1] for an introduction to this economic model. ...
... The routing of a demand along paths is fixed by establishing a contract between the source domain and all domains along the chosen paths. According to Yahaya and Suda [88,89], we assume that providers determine prices according to predefined load dependent price functions. Such prices, however, are only valid for a predefined demand size (bundle size), that is, routing flow of bundle size prompts an update of arc prices. ...
... Another method to deploy E2E ID QoS policy has been suggested by the inter-domain Resource Exchange architecture (iREX) [4] [5]. iREX facilitates an ID economic market to trade ID QoS resources with three basic functionalities: 1) network resource information evaluation and dissemination, 2) network resource trading, and 3) network resource reputation score maintenance. ...
... [4] and [5], we have shown that one of the benefits of the iREX architecture is that it increases network efficiency by deploying ID QoS policy based on the current least congested path, resulting in less network congestion and less request blocking when compared to the current SLA method. ...
Conference Paper
Abstract, The inter-domain Resource Exchange (iREX) ar-chitecture uses economic market mechanisms to automate the deployment of end to end (E2E) inter-domain (ID) quality of service (QoS) policy among resource consumer and resource provider Internet Service Providers (ISPs). Previous simulation results have shown that iREX allows more coexisting ID policy deployments with less network congestion when compared to the existing method. In this paper we explore iREX's network load distribution efficiency limits by comparing iREX's performance to a lower bound for network congestion. We present an ana-lytical model of iREX in terms of a min-cost flow problem, and numerical results of efficiency loss between iREX simulations and derived optimal solutions based on multi-commodity flow optimization models. Our results show that for nominal to high traffic loads of 50% or more, iREX deviates a maximum of approximately 30% from the derived lower bound, while the current method deviates a maximum of 350%. Index Terms, inter-domain; QoS policy; resource allocation and management; network control by pricing; economics.
... "UBP" refers to Utilization Based Pricing of link bandwidth. The notion of UBP have been used in several research projects [2][9] ...
... "UBP" refers to Utilization Based Pricing of link bandwidth. The notion of UBP have been used in several research projects [2][9] to achieve load-balancing. Price of link bandwidth is defined by a linear function of bandwidth utilization on a link, p = c 2 * B rsv / B cap (p: price, c 2 : const, B rsv : bandwidth already reserved by overlay networks on a link, B cap : bandwidth capacity on a link). ...
Conference Paper
In recent years, the notion of service overlay networks has been proposed as a promising solution for providing end-to-end QoS without changing the current Internet architecture. A major issue in deploying service overlay networks is determining how to allocate resources (such as link bandwidth) on a substrate network to overlay networks, while satisfying the end-to-end QoS requirements of applications running on each overlay network. This paper introduces the Market-based Cooperative Resource Allocation (MaCRA) architecture that achieves fair and efficient resource allocation in a decentralized manner. In MaCRA, resources on a substrate network are priced, and each overlay network provider creates an overlay network on a minimum cost basis to meet its application QoS requirements. MaCRA also allows each overlay network provider to trade their current resources with other overlay network providers when resources on a substrate network are not available or expensive. Simulation results demonstrate that MaCRA achieves fairness and efficiency in allocating resources for overlay networks when compared to existing mechanisms.
... For the same reasons, the current design of iREX is also limited to a single peer selected " most desirable " path when deploying reservations. While we have shown in [2] that, in the worse case, iREX's fault tolerance mechanism can recover from resource failure in less than 1.2 seconds, this deployment re-routing mechanism is limited to the available alternate resources at the time of failure. Deploying policy with redundancy is a prevention measure that works to minimize the traffic that needs to be re-routed during a failure – further increasing deployment reliability. ...
... While a peak for the L3 topology of 16% may seem a little large, this may be offset by a 6% decrease in congestion shown by the Congestion metric in Fig. 6 at the same peak (i.e. at 20% traffic load). To add another numerical perpective we quote our work in [2] where we showed that the average control packet overhead for an iREX deployment was 5 and 8 for the vBNS and L3 topologies respectively; therefore, an increase of 16% would mean about 10 control packets per MPO deployment of a 4.8mb/sec bundle of traffic in the L3 topology. ...
Conference Paper
The inter-domain Resource Exchange (iREX) architecture uses economic market mechanisms to automate the deployment of end-to-end (E2E) inter-domain (ID) quality of service (QoS) policy among resource consumer and resource provider Internet Service Providers (ISPs). In iREX, each policy reservation is deployed on a single E2E ID path made up of the most "desirable" (i.e. cheapest and least congested) ISP resources. To accommodate ISPs that prefer redundancy when deploying ID QoS policy, in this paper we introduce an extension to the iREX architecture that gives an originating ISP a multi- path option (MPO) when deploying a reservation. MPO takes an initiating ISP's preference for redundancy and provides information about the available path options to achieve this preference in a distributed manner. Our simulation results show that while providing redundancy to the originating ISP using MPO does increase its resource costs in accordance to an ISP's preference, it only marginally increases overhead, and does not affect overall network performance - in fact the use of MPO lowers congestion.
... This results in a Multiple sinks, multiple sources variant of the Multicommodity Minimal Cost Flow Problem, which will be discussed in Section 2.3. In more recent applications the problem is used to solve container shipment problems by Krile [12], where Yahaya and Sunda [13], [14] used it to model internet traffic routing. ...
Article
The Internet is a gigantic distributed system where the end-to-end (E2E) quality-of-service (QoS) plays an important role. Yet the current inter-domain routing protocol, namely, the Border Gateway Protocol (BGP), cannot provide E2E QoS guarantees. The main reason is that an autonomous system (AS) can only receive guarantees from its first-hop ASes via service level agreements (SLAs). But beyond the first-hop, QoS along the path from a source AS to a destination AS is not within the source AS's control regime. This makes it difficult to provide high quality-of-experience services to many Internet users even when many content providers are willing to pay for such high quality E2E guarantees. In this paper, we investigate the feasibility of providing high QoS-guaranteed E2E transit services by utilizing a (small) set of ASes/IXPs to serve as "brokers" to provide supervision, control and resource negotiation. Finding an optimal set of ASes as brokers can be formulated as a Maximum Coverage with B—dominating path Guarantee (MCBG) problem, and we show that it is in fact NP-hard. To address this problem, we design a $(\frac{1-e^{-1}}{2})$ approximation algorithm and also an efficient heuristic algorithm when additional constraints (e.g., the path length) are considered. We further analyze the APX-hardness of the MCBG problem to reveal the existence of the best approximation ratio. Based on the current Internet topology, we demonstrate that it is indeed feasible to provide high QoS guarantees for most E2E connections with only a small broker set: with only 0.19%, 1.9% or 6.8% ASes/IXPs serving as brokers, 53.13%, 85.41% or 99.29% of all global E2E connections can receive high QoSguaranteed services. Finally, we provide an economic model to study the behaviours of ASes when cooperating our brokerage scheme with the BGP protocol, and show that there are incentives to form and maintain such a brokerage coalition.
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Despite its importance, end-to-end Quality-of-Service (QoS) is still an open problem mostly because of the inter-domain segment since for the access (end-user/operator) the problem has solutions for a diversity of commercially deployed architectures. The root problem lies in the coordination complexity: operators need to coordinate the traffic services they can offer, from service choice to cooperation models. We propose a framework that allows operators to agree on a useful set of services using machine-to-machine negotiation. This consensual service set dynamically balances users' demand, effort of deployment (like cost) and local business policies — ultimately obeying economics. By having the same set of services throughout the Internet, end-to-end QoS greatly reduces to an intra-domain QoS problem. We discuss the problem using a top-down approach: from formulating a multi-dimensional, iterative multi-objective optimization problem to a design proposal based on gossip protocols.
Chapter
IntroductionDynamic FactorsNetwork FunctionsRepresentative Adaptation TechniquesDiscussionConclusion References
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