Traffic shaping, including pacing and rate limiting, is fundamental to the correct and efficient operation of both datacenter and wide area networks. Sample use cases include policy-based bandwidth allocation to flow aggregates, rate-based congestion control algorithms, and packet pacing to avoid bursty transmissions that can overwhelm router buffers. Driven by the need to scale to millions of flows and to apply complex policies, traffic shaping is moving from network switches into the end hosts, typically implemented in software in the kernel networking stack.

We present the design of Espresso, Google's SDN-based Internet peering edge routing infrastructure. This architecture grew out of a need to exponentially scale the Internet edge cost-effectively and to enable application-aware routing at Internet-peering scale. Espresso utilizes commodity switches and host-based routing/packet processing to implement a novel fine-grained traffic engineering capability. Overall, Espresso provides Google a scalable peering edge that is programmable, reliable, and integrated with global traffic systems. Espresso also greatly accelerated deployment of new networking features at our peering edge. Espresso has been in production for two years and serves over 22% of Google's total traffic to the Internet.

Online service providers aim to provide good performance for an increasingly diverse set of applications and services. One of the most effective ways to improve service performance is to replicate the service closer to the end users. Replication alone, however, has its limits: while operators can replicate static content, wide-scale replication of dynamic content is not always feasible or cost effective. To improve the latency of such services many operators turn to Internet traffic engineering. In this paper, we study the benefits of performing replica-to-end-user mappings in conjunction with active Internet traffic engineering. We present the design of PECAN, a system that controls both the selection of replicas ("content routing") and the routes between the clients and their associated replicas ("network routing"). We emulate a replicated service that can perform both content and network routing by deploying PECAN on a distributed testbed. In our testbed, we see that jointly performing content and network routing can reduce round-trip latency by 4.3% on average over performing content routing alone (potentially reducing service response times by tens of milliseconds or more) and that most of these gains can be realized with no more than five alternate routes at each replica.

Designers of content distribution networks (CDNs) often need to determine how changes to infrastructure deployment and configuration affect service response times when they deploy a new data center, change ISP peering, or change the mapping of clients to servers. Today, the designers use coarse, back-of-the-envelope calculations or costly field deployments; they need better ways to evaluate the effects of such hypothetical “what-if” questions before the actual deployments. This paper presents What-If Scenario Evaluator (WISE), a tool that predicts the effects of possible configuration and deployment changes in content distribution networks. WISE makes three contributions: 1) an algorithm that uses traces from existing deployments to learn causality among factors that affect service response time distributions; 2) an algorithm that uses the learned causal structure to estimate a dataset that is representative of the hypothetical scenario that a designer may wish to evaluate, and uses these datasets to predict hypothetical response-time distributions; 3) a scenario specification language that allows a network designer to easily express hypothetical deployment scenarios without being cognizant of the dependencies between variables that affect service response times. Our evaluation, both in a controlled setting and in a real-world field deployment on a large, global CDN, shows that WISE can quickly and accurately predict service response-time distributions for many practical what-if scenarios.

The Internet was designed to always find a route if there is a policy-compliant path. However, in many cases, connectivity is disrupted despite the existence of an underlying valid path. The research community has focused on short-term outages that occur during route convergence. There has been less progress on addressing avoidable long-lasting outages. Our measurements show that long-lasting events contribute significantly to overall unavailability.

ISPs are increasingly selling "tiered" contracts, which offer Internet connectivity to wholesale customers in bundles, at rates based on the cost of the links that the traffic in the bundle is traversing. Although providers have already begun to implement and deploy tiered pricing contracts, little is known about how to structure them. While contracts that sell connectivity on finer granularities improve market efficiency, they are also more costly for ISPs to implement and more difficult for customers to understand. Our goal is to analyze whether current tiered pricing practices in the wholesale transit market yield optimal profits for ISPs and whether better bundling strategies might exist. In the process, we deliver two contributions: 1) we develop a novel way of mapping traffic and topology data to a demand and cost model, and 2) we fit this model on three large real-world networks: an European transit ISP, a content distribution network, and an academic research network, and run counterfactuals to evaluate the effects of different bundling strategies. Our results show that the common ISP practice of structuring tiered contracts according to the cost of carrying the traffic flows (e.g., offering a discount for traffic that is local) can be suboptimal and that dividing contracts based on both traffic demand and the cost of carrying it into only three or four tiers yields near-optimal profit for the ISP.

No abstract available.

Motivated by increased concern over energy consumption in moderndatacenters,wepropose anew,distributedcomputingplatform calledNanoDataCenters(NaDa). NaDausesISP-controlledhome gateways to provide computing and storage services and adopts a managed peer-to-peer model to form a distributed data center infrastructure. To evaluate the potential for energy savings in NaDa platform we pick Video-on-Demand (VoD) services. We develop an energy consumption model for VoD in traditional and in NaDa data centers and evaluate this model using a large set of empirical VoD access data. We find that even under the most pessimistic scenarios, NaDa saves at least 20 % to 30 % of the energy compared to traditional data centers. These savings stem from energypreserving properties inherent to NaDa such as the reuse of already committed baseline power on underutilized gateways, the avoidance of cooling costs, and the reduction of network energy consumption as a result of demand and service co-localization in NaDa. Categories andSubject Descriptors

We describe Trellis, a platform for hosting virtual networks on shared commodity hardware. Trellis allows each virtual network to define its own topology, control protocols, and forwarding tables, while amortizing costs by sharing the physical infrastructure. Trellis synthesizes two container-based virtualization technologies, VServer and NetNS, as well as a new tunneling mechanism, EGRE, into a coherent platform that enables high-speed virtual networks. We describe the design and implementation of Trellis and evaluate its packet-forwarding rates relative to other virtualization technologies and native kernel forwarding performance.

Today's Internet's routing paths are inefficient with respect to both connectivity and the market for interconnection. The former manifests itself via needlessly long paths, de-peering, etc. The latter arises because of a primitive market structure that results in unfulfilled demand and unused capacity. Today's networks make pairwise, myopic interconnection decisions based on business considerations that may not mirror considerations of the edge networks (or end systems) that would benefit from the existence of a particular interconnection. These bilateral contracts are also complex and difficult to enforce.

Designers of content distribution networks often need to determine how changes to infrastructure deployment and configuration affect service response times when they deploy a new data center, change ISP peering, or change the mapping of clients to servers. Today, the designers use coarse, back-of-the-envelope calculations, or costly field deployments; they need better ways to evaluate the effects of such hypothetical "what-if" questions before the actual deployments. This paper presents What-If Scenario Evaluator (WISE), a tool that predicts the effects of possible configuration and deployment changes in content distribution networks. WISE makes three contributions: (1) an algorithm that uses traces from existing deployments to learn causality among factors that affect service response-time distributions; (2) an algorithm that uses the learned causal structure to estimate a dataset that is representative of the hypothetical scenario that a designer may wish to evaluate, and uses these datasets to predict future response-time distributions; (3) a scenario specification language that allows a network designer to easily express hypothetical deployment scenarios without being cognizant of the dependencies between variables that affect service response times. Our evaluation, both in a controlled setting and in a real-world field deployment at a large, global CDN, shows that WISE can quickly and accurately predict service response-time distributions for many practical What-If scenarios.

This paper describes a BGP-session multiplexer called BGP-Mux, which provides stable, on-demand access to global BGP route feeds. This gateway allows arbitrary and eventransientclientBGP connectionstobeprovisionedand