Analysis of OD Flows (Raw Data)

In a recent paper, Structural Analysis of Network Traffic Flows, we analyzed the set of Origin Destination traffic flows from the Sprint-Europe and Abilene backbone networks. This report presents the complete set of results from analyzing data from both networks. The results in this report are specific to the Sprint-1 and Abilene datasets studied in the above paper. The following results are presented here: 1 Rows of Principal Matrix (V) 2 1.1 Sprint-1 Dataset ................................ 2 1.2 Abilene Dataset.................................. 9 2 Set of Eigenflows 14 2.1 Sprint-1 Dataset.................................. 14 2.2 Abilene Dataset................................... 21 3 Classifying Eigenflows 26 3.1 Sprint-1 Dataset.................................. 26 3.2 Abilene Datase.................................... 44Centre National de la Recherche Scientifique (CNRS) France; Sprint Labs; Office of Naval Research (N000140310043); National Science Foundation (ANI-9986397, CCR-0325701

Measuring Transmission Opportunities in 802.11 Links

We propose a powerful MAC/PHY cross-layer approach to measuring IEEE 802.11 transmission opportunities in WLAN networks on a per-link basis. Our estimator can operate at a single station and it is able to: 1) classify losses caused by noise, collisions, and hidden nodes; and 2) distinguish between these losses and the unfairness caused by both exposed nodes and channel capture. Our estimator provides quantitative measures of the different causes of lost transmission opportunities, requiring only local measures at the 802.11 transmitter and no modification to the 802.11 protocol or in other stations. Our approach is suited to implementation on commodity hardware, and we demonstrate our prototype implementation via experimental assessments. We finally show how our estimator can help the WLAN station to improve its local performance

Can User-Level Probing Detect and Diagnose Common Home-WLAN Pathologies?

Common WLAN pathologies include low signal-to-noise ratio, congestion, hidden terminals or interference from non-802.11 devices and phenomena. Prior work has focused on the detection and diagnosis of such problems using layer-2 information from 802.11 devices and special-purpose access points and monitors, which may not be generally available. Here, we investigate a userlevel approach: is it possible to detect and diagnose 802.11 pathologies with strictly user-level active probing, without any cooperation from, and without any visibility in, layer-2 devices? In this paper, we present preliminary but promising results indicating that such diagnostics are feasible

Self Organization of Interfering 802.11 Wireless Access Networks

The increased popularity of IEEE 802.11 WLANs has led to dense deployments in urban areas. Such high density leads to sub-optimal performance unless the interfering networks learn how to optimally share the spectrum. This paper proposes a set of novel fully distributed algorithms that allow (i) multiple interfering 802.11 WLANs to select their operating frequency in a way that minimizes global interference, and (ii) clients to choose their Access Point so that the bandwidth of all interfering networks is shared optimally. The proposed algorithms rely on Gibbs' sampler and optimize global network performance based on local information. They do not require explicit coordination among the wireless devices. We establish the mathematical properties of the proposed algorithms and study their performance using analytical, event-driven simulations. Our results strongly motivate the need for self-organization strategies in wireless access networks. We discuss implementation requirements and show that significant benefits can be gained even within incremental deployments and in the presence of non-cooperating wireless clients

Measurement and Analysis of Single-Hop Delay on an IP Backbone Network

We measure and analyze the single-hop packet delay through operational routers in the Sprint Internet protocol (IP) backbone network. After presenting our delay measurements through a single router for OC-3 and OC-12 link speeds, we propose a methodology to identify the factors contributing to single-hop delay. In addition to packet processing, transmission, and queueing delay at the output link, we observe the presence of very large delays that cannot be explained within the context of a first-in first-out output queue model. We isolate and analyze these outliers. Results indicate that there is very little queueing taking place in Sprint’s backbone. As link speeds increase, transmission delay decreases and the dominant part of single-hop delay is packet processing time. We show that if a packet is received and transmitted on the same linecard, it experiences less than 20 s of delay. If the packet is transmitted across the switch fabric, its delay doubles in magnitude. We observe that processing due to IP options results in single-hop delays in the order of milliseconds. Milliseconds of delay may also be experienced by packets that do not carry IP options. We attribute those delays to router idiosyncratic behavior that affects less than 1% of the packets. Finally, we show that the queueing delay distribution is long-tailed and can be approximated with aWeibull distribution with the scale parameter a = 0.5 and the shape parameter b = 0.6 to 0.82

Provisioning IP Backbone Networks Based on Measurements

The theme of this thesis is the enhancement of current IP backbone provisioning practices in the presence of additional network measurements. Current practices are heavily dependent on the intuition of the human operators. Traffic variability, scalability issues, lack of monitoring information, and complex interactions between inter- and intra-domain routing protocols result in network management techniques that usually rely on trial and error. In contrast with reductionist approaches, we demonstrate the benefits of using different types of monitoring information in the formalisation of different network provisioning tasks, and provide a methodological framework for their analysis. We use four main sources of network monitoring information: (i) GPS-synchronised packet traces listing every packet traversing a monitored unidirectional link, (ii) BGP routing table dumps, (iii) SNMP information collected since 1999, and (iv) topological information. Combining the above sources of information, and analysing them at the appropriate time scale, we demonstrate the benefits of additional measurements on three specific network provisioning tasks. First, we measure and analyse delay as experienced by packets while traversing a single router inside the network. We show that packets experience minimal queueing delay and that delay through the network is dominated by the propagation delay. Our results hold when network link utilisation stays moderate. However, links are likely to experience short-lived congestion episodes as a result of link or equipment failures. Our second network provisioning task regards the off-loading of congested links by the re-direction of high-volume flows. We propose a methodology for the identification of those flows traversing a link that contribute significant amounts of traffic consistently over time. Persistent link overload can only be resolved through additional provisioning. Our third task focuses on the prediction of where and when future provisioning will be required in the backbone. We obtain accurate predictions for at least six months in the future