Internet routing research has long been hindered by obstacles to executing the wide class of experiments necessary to characterize problems and opportunities, and evaluate candidate solutions. Prior works proposed a platform that would provide experiments with control of an Internet-connected AS. However, because BGP does not natively support multiplexing or the requisite security policies for building such a platform, prior works were ultimately unable to realize this vision.

We examine the current state of user network performance and opportunities to improve it from the vantage point of Facebook, a global content provider. Facebook serves over 2 billion users distributed around the world using a network of PoPs and interconnections spread across 6 continents. In this paper, we execute a large-scale, 10-day measurement study of metrics at the TCP and HTTP layers for production user traffic at all of Facebook's PoPs worldwide, collecting performance measurements for hundreds of trillions of sampled HTTP sessions. We discuss our approach to collecting and analyzing measurements, including a novel approach to characterizing user achievable goodput from the server side. We find that most user sessions have MinRTT less than 39ms and can support HD video. We investigate if it is possible to improve performance by incorporating performance information into Facebook's routing decisions; we find that default routing by Facebook is largely optimal. To our knowledge, our measurement study is the first characterization of user performance on today's Internet from the vantage point of a global content provider.

Large content providers build points of presence around the world, each connected to tens or hundreds of networks. Ideally, this connectivity lets providers better serve users, but providers cannot obtain enough capacity on some preferred peering paths to handle peak traffic demands. These capacity constraints, coupled with volatile traffic and performance and the limitations of the 20 year old BGP protocol, make it difficult to best use this connectivity.

The Internet suffers from well-known performance, reliability, and security problems. However, proposed improvements have seen little adoption due to the difficulties of Internet-wide deployment. We observe that, instead of trying to solve these problems in the general case, it may be possible to make substantial progress by focusing on solutions tailored to the paths between popular content providers and their clients, which carry a large share of Internet traffic.

The design space for large, multipath datacenter networks is large and complex, and no one design fits all purposes. Network architects must trade off many criteria to design cost-effective, reliable, and maintainable networks, and typically cannot explore much of the design space. We present Condor, our approach to enabling a rapid, efficient design cycle. Condor allows architects to express their requirements as constraints via a Topology Description Language (TDL), rather than having to directly specify network structures. Condor then uses constraint-based synthesis to rapidly generate candidate topologies, which can be analyzed against multiple criteria. We show that TDL supports concise descriptions of topologies such as fat-trees, BCube, and DCell; that we can generate known and novel variants of fat-trees with simple changes to a TDL file; and that we can synthesize large topologies in tens of seconds. We also show that Condor supports the daunting task of designing multi-phase network expansions that can be carried out on live networks.

Internet routing suffers from persistent and transient failures, circuitous routes, oscillations, and prefix hijacks. A major impediment to progress is the lack of ways to conduct impactful interdomain research. Most research is based either on passive observation of existing routes, keeping researchers from assessing how the Internet will respond to route or policy changes; or simulations, which are restricted by limitations in our understanding of topology and policy.

BGP severely constrains how networks can deliver traffic over the Internet. Today's networks can only forward traffic based on the destination IP prefix, by selecting among routes offered by their immediate neighbors. We believe Software Defined Networking (SDN) could revolutionize wide-area traffic delivery, by offering direct control over packet-processing rules that match on multiple header fields and perform a variety of actions. Internet exchange points (IXPs) are a compelling place to start, given their central role in interconnecting many networks and their growing importance in bringing popular content closer to end users.

BGP severely constrains how networks can deliver traffic over the Internet. Today's networks can only forward traffic based on the destination IP prefix, by selecting among routes offered by their immediate neighbors. We believe Software Defined Networking (SDN) could revolutionize wide-area traffic delivery, by offering direct control over packet-processing rules that match on multiple header fields and perform a variety of actions. Internet exchange points (IXPs) are a compelling place to start, given their central role in interconnecting many networks and their growing importance in bringing popular content closer to end users. To realize a Software Defined IXP (an "SDX"), we need new programming abstractions that allow participating networks to create and run these applications and a runtime that both behaves correctly when interacting with BGP and ensures that applications do not interfere with each other. We must also ensure that the system scales, both in rule-table size and computational overhead. In this demo, we show how we tackle these challenges demonstrating the flexibility and scalability of our SDX platform. The paper also appears in the main program.

Gang migration refers to the simultaneous live migration of multiple Virtual Machines (VMs) from one set of physical machines to another in response to events such as load spikes and imminent failures. Gang migration generates a large volume of network traffic and can overload the core network links and switches in a data center. In this paper, we present an approach to reduce the network overhead of gang migration using global deduplication (GMGD). GMGD identifies and eliminates the retransmission of duplicate memory pages among VMs running on multiple physical machines in the cluster. We describe the design, implementation and evaluation of a GMGD prototype using QEMU/KVM VMs. Evaluations on a 30-node Gigabit Ethernet cluster having 10GigE core links shows that GMGD can reduce the network traffic on core links by up to 65% and the total migration time of VMs by up to 42% when compared to the default migration technique in QEMU/KVM. Furthermore, GMGD has a smaller adverse performance impact on network-bound applications.

With the emergence of cloud computing, users are increasingly using storage services of cloud providers to satisfy their storage needs. However, these cloud providers are not 100% reliable, resulting in periodic service outages. End users require a solution that minimizes the impact of cloud service outages and optimizes the chances of successfully retrieving stored objects in cases of provider failures. In this paper, we propose to build a federated cloud agent, enabling end users to simultaneously deploy storage objects to multiple cloud service providers, based on their unit storage costs and failure probabilities. We study two service provider failure models: the first case assumes that at most one service provider fails at any given time, and the second case assumes that cloud service providers may fail independently with certain probabilities. We cast both scenarios as constrained optimization problems to minimize the overall storage cost while enhancing the chances of recovering all the storage objects in case of service outages. In the experiments, we evaluated the proposed optimal storage schemes against a fixed server deployment strategy and find our schemes can achieve good recovery ratios, while incurring minimal storage costs.