This paper presents Meta's Production Wide Area Network (WAN) Entitlement solution used by thousands of Meta's services to share the network safely and efficiently. We first introduce the Network Entitlement problem, i.e., how to share WAN bandwidth across services with flexibility and SLO guarantees. We present a new abstraction entitlement contract, which is stable, simple, and operationally friendly. The contract defines services' network quota and is set up between the network team and services teams to govern their obligations. Our framework includes two key parts: (1) an entitlement granting system that establishes an agile contract while achieving network efficiency and meeting long-term SLO guarantees, and (2) a large-scale distributed run-time enforcement system that enforces the contract on the production traffic. We demonstrate its effectiveness through extensive simulations and real-world end-to-end tests. The system has been deployed and operated for over two years in production. We hope that our years of experience provide a new angle to viewing WAN network sharing in production and will inspire follow-up research.

Network verification has been recently proposed to detect network misconfigurations. Existing work focuses on the reachability. This paper proposes a framework that verifies the Service Level Agreement (SLA) compliance of the network using static verification. This work proposes a quantitative model and a set of algorithms for verifying performance properties of a network with switches and middleboxes, i.e., service chains. We develop SLA-Verifier and evaluate its efficiency using simulation on real-world data and testbed experiments. To improve the SLA violation detection accuracy, our system uses verification results to optimize online monitoring.

Poor visibility into the network hampers progress in a number of important research areas, from network troubleshooting to Internet topology and performance mapping. This persistent, well-known problem has served as motivation for numerous proposals to build or extend existing Internet measurement platforms by recruiting larger, more diverse vantage points. Capturing the edge of the network, however, remains an elusive goal. We argue that at its root the problem is one of incentives. Today's measurement platforms build on the assumption that the goals of experimenters and those hosting the platform are the same. As much of the Internet growth occurs in residential broadband networks, this assumption no longer holds. We present a measurement experimentation platform that reaches the network edge by explicitly aligning the objectives of the experimenters with those of the users hosting the platform. Dasu-our current prototype-is designed to support both network measurement experimentation and broadband characterization. Dasu has been publicly available since July 2010 and has been installed by over 100 000 users with a heterogeneous set of connections spreading across 2431 autonomous systems (ASs) and 166 countries. We discuss some of the challenges we faced building and using a platform for the Internet's edge, describe its design and implementation, and illustrate the unique perspective its current deployment brings to Internet measurement.

Characterizing the flow of Internet traffic is important in a wide range of contexts, from network engineering and application design to understanding the network impact of consumer demand and business relationships. Despite the growing interest, the nearly impossible task of collecting large-scale, Internet-wide traffic data has severely constrained the focus of traffic-related studies.

Content Delivery Networks (CDNs) rely on the Domain Name System (DNS) for replica server selection. DNS-based server selection builds on the assumption that, in the absence of information about the client's actual network location, the location of a client's DNS resolver provides a good approximation. The recent growth of remote DNS services breaks this assumption and can negatively impact client's web performance.

The Domain Name System (DNS) is a fundamental component of today's Internet. Recent years have seen radical changes to DNS with increases in usage of remote DNS and public DNS services such as OpenDNS. Given the close relationship between DNS and Content Delivery Networks (CDNs) and the pervasive use of CDNs by many popular applications including web browsing and real-time entertainment services, it is important to understand the impact of remote and public DNS services on users' overall experience on the Web. This work presents a tool, namehelp, which comparatively evaluates DNS services in terms of the web performance they provide, and implements an end-host solution to address the performance impact of remote DNS on CDNs. The demonstration will show the functionality of namehelp with online results for its performance improvements.

A thorough understanding of the network impact of emerging large-scale distributed systems -- where traffic flows and what it costs -- must encompass users' behavior, the traffic they generate and the topology over which that traffic flows. In the case of BitTorrent, however, previous studies have been limited by narrow perspectives that restrict such analysis.

Evaluating and characterizing access ISPs is critical to consumers shopping for alternative services and governments surveying the availability of broadband services to their citizens. We present Dasu, a service for crowdsourcing ISP characterization to the edge of the network. Dasu is implemented as an extension to a popular BitTorrent client and has been available since July 2010. While the prototype uses BitTorrent as its host application, its design is agnostic to the particular host application. The demo showcases our current implementation using both a prerecorded execution trace and a live run.

Network positioning systems provide an important service to large- scale P2P systems, potentially enabling clients to achieve higher performance, reduce cross-ISP traffic and improve the robustness of the system to failures. Because traces representative of this environment are generally unavailable, and there is no platform suited for experimentation at the appropriate scale, network positioning systems have been commonly imple- mented and evaluated in simulation and on research testbeds. The performance of network positioning remains an open question for large deployments at the edges of the network. This paper evaluates how four key classes of network po- sitioning systems fare when deployed at scale and measured in P2P systems where they are used. Using 2 billion network measurements gathered from more than 43,000 IP addresses probing over 8 million other IPs worldwide, we show that network positioning exhibits noticeably worse performance than previously reported in studies conducted on research testbeds. To explain this result, we identify several key properties of this environment that call into question fundamental assumptions driving network positioning research.