Gianluca Iannaccone

RouteBricks: exploiting parallelism to scale software routers

We revisit the problem of scaling software routers, motivated by recent advances in server technology that enable high-speed parallel processing--a feature router workloads appear ideally suited to exploit. We propose a software router architecture that parallelizes router functionality both across multiple servers and across multiple cores within a single server. By carefully exploiting parallelism at every opportunity, we demonstrate a 35Gbps parallel router prototype; this router capacity can be linearly scaled through the use of additional servers. Our prototype router is fully programmable using the familiar Click/Linux environment and is built entirely from off-the-shelf, general-purpose server hardware.

Characterization of failures in an IP backbone

We analyze IS-IS routing updates from sprints IP network to characterize failures that affect IP connectivity. Failures are first classified based on probable causes such as maintenance activities, router-related and optical layer problems. Key temporal and spatial characteristics of each class are analyzed and, when appropriate, parameterized using well-known distributions. Our results indicate that 20% of all failures is due to planned maintenance activities. Of the unplanned failures, almost 30% are shared by multiple links and can be attributed to router-related and optical equipment-related problems, while 70% affect a single link at a time. Our classification of failures according to different causes reveals the nature and extent of failures in todays IP backbones. Furthermore, our characterization of the different classes can be used to develop a probabilistic failure model, which is important for various traffic engineering problems.

Characterization of failures in an operational IP backbone network

As the Internet evolves into a ubiquitous communication infrastructure and supports increasingly important services, its dependability in the presence of various failures becomes critical. In this paper, we analyze IS-IS routing updates from the Sprint IP backbone network to characterize failures that affect IP connectivity. Failures are first classified based on patterns observed at the IP-layer; in some cases, it is possible to further infer their probable causes, such as maintenance activities, router-related and optical layer problems. Key temporal and spatial characteristics of each class are analyzed and, when appropriate, parameterized using well-known distributions. Our results indicate that 20% of all failures happen during a period of scheduled maintenance activities. Of the unplanned failures, almost 30% are shared by multiple links and are most likely due to router-related and optical equipment-related problems, respectively, while 70% affect a single link at a time. Our classification of failures reveals the nature and extent of failures in the Sprint IP backbone. Furthermore, our characterization of the different classes provides a probabilistic failure model, which can be used to generate realistic failure scenarios, as input to various network design and traffic engineering problems.

Feasibility of IP restoration in a tier 1 backbone

Large IP networks usually combine protection and restoration mechanisms at various layers of the protocol stack to minimize service disruption in the event of failures. Sprint has chosen an IP-based restoration approach for building a highly available tier 1 IP backbone. This article describes the design principles of Sprints network that makes IP-based restoration an effective and cost-efficient approach. The effectiveness of IP-based restoration is evaluated by analyzing network failure characteristics, and measuring disruptions in service availability during controlled failure experiments in the backbone. Current trends for improving the performance of IP-based restoration are also discussed.

Detection and identification of network anomalies using sketch subspaces

Network anomaly detection using dimensionality reduction techniques has received much recent attention in the literature. For example, previous work has aggregated netflow records into origin-destination (OD) flows, yielding a much smaller set of dimensions which can then be mined to uncover anomalies. However, this approach can only identify which OD flow is anomalous, not the particular IP flow(s) responsible for the anomaly. In this paper we show how one can use random aggregations of IP flows (i.e., sketches) to enable more precise identification of the underlying causes of anomalies. We show how to combine traffic sketches with a subspace method to (1) detect anomalies with high accuracy and (2) identify the IP flows(s) that are responsible for the anomaly. Our method has detection rates comparable to previous methods and detects many more anomalies than prior work, taking us a step closer towards a robust on-line system for anomaly detection and identification.

Green WLANs: On-Demand WLAN Infrastructures

Enterprise wireless local area networks (WLANs) that consist of a high-density of hundreds to thousands of access points (APs) are being deployed rapidly in corporate offices and university campuses. The primary purpose of these deployments is to satisfy user demands for high bandwidth, mobility, and reliability. However, our recent study of two such WLANs showed that these networks are rarely used at their peak capacity, and the majority of their resources are frequently idle. In this paper, we bring to attention that a large fraction of idle WLAN resources results in significant energy losses. Thousands of WLANs world-wide collectively compound this problem, while raising serious concerns about the energy losses that will occur in the future. In response to this compelling problem, we propose the adoption of resource on-demand (RoD) strategies for WLANs. RoD strategies power on or off WLAN APs dynamically, based on the volume and location of user demand. As a specific solution, we propose SEAR, a practical and elegant RoD strategy for high-density WLANs. We implement SEAR on two wireless networks to show that SEAR is easy to integrate in current WLANs, while it ensures no adverse impact on end-user connectivity and performance. In our experiments, SEAR reduces power consumption to 46%. Using our results we discuss several interesting problems that open future directions of research in RoD WLANs.

Impact of link failures on VoIP performance

We use active and passive traffic measurements to identify the issues involved in the deployment of a voice service over a tier-1 IP backbone network. Our findings indicate that no specific handling of voice packets (i.e. QoS differentiation) is needed in the current backbone but new protocols and mechanisms need to be introduced to provide a better protection against link failures. We discover that link failures may be followed by long periods of routing instability, during which packets can be dropped because forwarded along invalid paths. We also identify the need for a new family of quality of service mechanisms based on fast protection of traffic and high availability of the service rather than performance in terms of delay and loss.

Network topologies: inference, modeling, and generation

Accurate measurement, inference and modeling techniques are fundamental to Internet topology research. Spatial analysis of the Internet is needed to develop network planning, optimal routing algorithms, and failure detection measures. A first step toward achieving such goals is the availability of network topologies at different levels of granularity, facilitating realistic simulations of new Internet systems. The main objective of this survey is to familiarize the reader with research on network topology over the past decade. We study techniques for inference, modeling, and generation of the Internet topology at both the router and administrative levels. We also compare the mathematical models assigned to various topologies and the generation tools based on them. We conclude with a look at emerging areas of research and potential future research directions.

A cost comparison of datacenter network architectures

There is a growing body of research exploring new network architectures for the data center. These proposals all seek to improve the scalability and cost-effectiveness of current data center networks, but adopt very different approaches to doing so. For example, some proposals build networks entirely out of switches while others do so using a combination of switches and servers. How do these different network architectures compare? For that matter, by what metrics should we even begin to compare these architectures? Understanding the tradeoffs between different approaches is important both for operators making deployment decisions and to guide future research. In this paper, we take a first step toward understanding the tradeoffs between different data center network architectures. We use high-level models of different classes of data center networks and compare them on cost using both current and predicted trends in cost and power consumption.

Modeling Internet backbone traffic at the flow level

Our goal is to design a traffic model for noncongested Internet backbone links, which is simple enough to be used in network operation, while being as general as possible. The proposed solution is to model the traffic at the flow level by a Poisson shot-noise process. In our model, a flow is a generic notion that must be able to capture the characteristics of any kind of data stream. We analyze the accuracy of the model with real traffic traces collected on the Sprint Internet protocol (IP) backbone network. Despite its simplicity, our model provides a good approximation of the real traffic observed in the backbone and of its variation. Finally, we discuss the application of our model to network design and dimensioning.