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55
NetDiagnoser: Troubleshooting network unreachabilities using endtoend probes and routing data
 IN CONEXT
, 2007
"... The distributed nature of the Internet makes it difficult for a single service provider to troubleshoot the disruptions experienced by its customers. We propose NetDiagnoser, a troubleshooting algorithm to identify the location of failures in an internetwork environment. First, we adapt the wellknow ..."
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Cited by 48 (4 self)
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The distributed nature of the Internet makes it difficult for a single service provider to troubleshoot the disruptions experienced by its customers. We propose NetDiagnoser, a troubleshooting algorithm to identify the location of failures in an internetwork environment. First, we adapt the wellknown Boolean tomography technique to work in this environment. Then, we significantly extend this technique to improve the diagnosis accuracy in the presence of multiple link failures, logical failures (for instance, misconfigurations of route export filters), and incomplete topology inference. In particular, NetDiagnoser takes advantage of rerouted paths, routing messages collected at one provider’s network and Looking Glass servers. We evaluate each feature of NetDiagnoser separately using CBGP simulations on realistic topologies. Our results show that NetDiagnoser can successfully identify a small set of links, which almost always includes the actually failed/misconfigured links.
NetQuest: A Flexible Framework for LargeScale Network Measurement
, 2006
"... In this paper, we present NetQuest, a flexible framework for largescale network measurement. We apply Bayesian experimental design to select active measurements that maximize the amount of information we gain about the network path properties subject to given resource constraints. We then apply netw ..."
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Cited by 40 (2 self)
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In this paper, we present NetQuest, a flexible framework for largescale network measurement. We apply Bayesian experimental design to select active measurements that maximize the amount of information we gain about the network path properties subject to given resource constraints. We then apply network inference techniques to reconstruct the properties of interest based on the partial, indirect observations we get through these measurements. By casting network measurement in a general Bayesian decision theoretic framework, we achieve flexibility. Our framework can support a variety of design requirements, including (i) differentiated design for providing better resolution to certain parts of the network, (ii) augmented design for conducting additional measurements given existing observations, and (iii) joint design for supporting multiple users who are interested in different parts of the network. Our framework is also scalable and can design measurement experiments that span thousands of routers and end hosts. We develop a toolkit that realizes the framework on PlanetLab. We conduct extensive evaluation using both real traces and synthetic data. Our results show that the approach can accurately estimate networkwide and individual path properties by only monitoring within 210 % of paths. We also demonstrate its effectiveness in providing differentiated monitoring, supporting continuous monitoring, and satisfying the requirements of multiple users.
Every Microsecond Counts: Tracking FineGrain Latencies with a Lossy Difference Aggregator
"... Many network applications have stringent endtoend latency requirements, including VoIP and interactive video conferencing, automated trading, and highperformance computing—where even microsecond variations may be intolerable. The resulting finegrain measurement demands cannot be met effectively ..."
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Cited by 33 (11 self)
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Many network applications have stringent endtoend latency requirements, including VoIP and interactive video conferencing, automated trading, and highperformance computing—where even microsecond variations may be intolerable. The resulting finegrain measurement demands cannot be met effectively by existing technologies, such as SNMP, NetFlow, or active probing. We propose instrumenting routers with a hashbased primitive that we call a Lossy Difference Aggregator (LDA) to measure latencies down to tens of microseconds and losses as infrequent as one in a million. Such measurement can be viewed abstractly as what we refer to as a coordinated streaming problem, which is fundamentally harder than standard streaming problems due to the need to coordinate values between nodes. We describe a compact data structure that efficiently computes the average and standard deviation of latency and loss rate in a coordinated streaming environment. Our theoretical results translate to an efficient hardware implementation at 40 Gbps using less than 1 % of a typical 65nm 400MHz networking ASIC. When compared to Poissonspaced active probing with similar overheads, our LDA mechanism delivers orders of magnitude smaller relative error; active probing requires 50–60 times as much bandwidth to deliver similar levels of accuracy.
Compressive sensing over graphs
 in Proc. IEEE INFOCOM
, 2011
"... Abstract—In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are interested in recovering sparse vectors representing the properties of the edges from a graph. Unlike existing ..."
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Cited by 32 (3 self)
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Abstract—In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are interested in recovering sparse vectors representing the properties of the edges from a graph. Unlike existing compressive sensing results, the collective additive measurements we are allowed to take must follow connected paths over the underlying graph. For a sufficiently connected graph with n nodes, it is shown that, using O(k log(n)) path measurements, we are able to recover any ksparse link vector (with no more than k nonzero elements), even though the measurements have to follow the graph path constraints. We mainly show that the computationally efficient 1 minimization can provide theoretical guarantees for inferring such ksparse vectors with O(k log(n)) path measurements from the graph. I.
Network exception handlers: Hostnetwork control in enterprise networks
 In SIGCOMM
, 2008
"... Enterprise network architecture and management have followed the Internet’s design principles despite different requirements and characteristics: enterprise hosts are administered by a single authority, which intrinsically assigns different values to traffic from different business applications. We ..."
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Cited by 21 (3 self)
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Enterprise network architecture and management have followed the Internet’s design principles despite different requirements and characteristics: enterprise hosts are administered by a single authority, which intrinsically assigns different values to traffic from different business applications. We advocate a new approach where hosts are no longer relegated to the network’s periphery, but actively participate in networkrelated decisions. To enable host participation, network information, such as dynamic network topology and perlink characteristics and costs, is exposed to the hosts, and network administrators specify conditions on the propagated network information that trigger actions to be performed while a condition holds. The combination of a condition and its actions embodies the concept of the network exception handler, defined analogous to a program exception handler. Conceptually, network exception handlers execute on hosts with actions parameterized by network and host state. Network exception handlers allow hosts to participate in network management, traffic engineering and other operational decisions by explicitly controlling host traffic under predefined conditions. This flexibility improves overall performance by allowing efficient use of network resources. We outline several sample network exception handlers, present an architecture to support them, and evaluate them using data collected from our own enterprise network.
Network Loss Inference with Second Order Statistics of EndtoEnd Flows
, 2007
"... We address the problem of calculating link loss rates from endtoend measurements. Contrary to existing works that use only the average endtoend loss rates or strict temporal correlations between probes, we exploit secondorder moments of endtoend flows. We first prove that the variances of lin ..."
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Cited by 21 (3 self)
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We address the problem of calculating link loss rates from endtoend measurements. Contrary to existing works that use only the average endtoend loss rates or strict temporal correlations between probes, we exploit secondorder moments of endtoend flows. We first prove that the variances of link loss rates can be uniquely calculated from the covariances of the measured endtoend loss rates in any realistic topology. After calculating the link variances, we remove the uncongested links with small variances from the firstorder moment equations to obtain a full rank linear system of equations, from which we can calculate precisely the loss rates of the remaining congested links. This operation is possible because losses due to congestion occur in bursts and hence the loss rates of congested links have high variances. On the contrary, most links on the Internet are uncongested, and hence the averages and variances of their loss rates are virtually zero. Our proposed solution uses only regular unicast probes and thus is applicable in today’s Internet. It is accurate and scalable, as shown in our simulations and experiments on PlanetLab.
Sparse Recovery with Graph Constraints: Fundamental Limits and Measurement Construction
, 2012
"... ... with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgraph. We provide explicit measurement constructions for several special graphs. A general measurement construction algorithm is also proposed and evaluated. For any given gra ..."
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Cited by 14 (3 self)
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... with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgraph. We provide explicit measurement constructions for several special graphs. A general measurement construction algorithm is also proposed and evaluated. For any given graph G with n nodes, we derive order optimal upper bounds of the minimum number of measurements needed to recoverany ksparse vector over G (M G k,n). Our study suggests that M G k,n may serve as a graph connectivity metric.
A unique “nonnegative” solution to an underdetermined system: from vectors to matrices
 IEEE Transactions on Signal Processing
, 2011
"... Abstract—This paper investigates the uniqueness of a nonnegative vector solution and the uniqueness of a positive semidefinite matrix solution to underdetermined linear systems. A vector solution is the unique solution to an underdetermined linear system only if the measurement matrix has a rowspa ..."
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Cited by 13 (0 self)
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Abstract—This paper investigates the uniqueness of a nonnegative vector solution and the uniqueness of a positive semidefinite matrix solution to underdetermined linear systems. A vector solution is the unique solution to an underdetermined linear system only if the measurement matrix has a rowspan intersecting the positive orthant. Focusing on two types of binary measurement matrices, Bernoulli 01 matrices and adjacency matrices of general expander graphs, we show that, in both cases, the support size of a unique nonnegative solution can grow linearly, namely O(n), with the problem dimension n. We also provide closedform characterizations of the ratio of this support size to the signal dimension. For the matrix case, we show that under a necessary and sufficient condition for the linear compressed observations operator, there will be a unique positive semidefinite matrix solution to the compressed linear observations. We further show that a randomly generated Gaussian linear compressed observations operator will satisfy this condition with overwhelmingly high probability. I.
Modelbased identification of dominant congested links
 in Proc. ACM SIGCOMM IMC
, 2003
"... Abstract—In this paper, we propose a modelbased approach that uses periodic end–end probes to identify whether a “dominant congested link ” exists along an end–end path. Informally, a dominant congested link refers to a link that incurs the most losses and significant queuing delays along the path. ..."
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Cited by 12 (0 self)
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Abstract—In this paper, we propose a modelbased approach that uses periodic end–end probes to identify whether a “dominant congested link ” exists along an end–end path. Informally, a dominant congested link refers to a link that incurs the most losses and significant queuing delays along the path. We begin by providing a formal yet intuitive definition of dominant congested link and present two simple hypothesis tests to identify whether such a link exists. We then present a novel modelbased approach for dominant congested link identification that is based on interpreting probe loss as an unobserved (virtual) delay. We develop parameter inference algorithms for hidden Markov model (HMM) and Markov model with a hidden dimension (MMHD) to infer this virtual delay. Our validation using ns simulation and Internet experiments demonstrate that this approach can correctly identify a dominant congested link with only a small amount of probe data. We further provide an upper bound on the maximum queuing delay of the dominant congested link once we identify that such a link exists. Index Terms—Bottleneck link, dominant congested link, end–end inference, hidden Markov model (HMM), Markov model with a hidden dimension (MMHD), network inference, network management, path characteristics. I.
Not all microseconds are equal: Finegrained perflow measurements with reference latency interpolation
 In ACM SIGCOMM
, 2010
"... ABSTRACT New applications such as algorithmic trading and highperformance computing require extremely low latency (in microseconds). Network operators today lack sufficient finegrain measurement tools to detect, localize and repair performance anomalies and delay spikes that cause application SLA ..."
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Cited by 11 (4 self)
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ABSTRACT New applications such as algorithmic trading and highperformance computing require extremely low latency (in microseconds). Network operators today lack sufficient finegrain measurement tools to detect, localize and repair performance anomalies and delay spikes that cause application SLA violations. A recently proposed solution called LDA provides a scalable way to obtain latency, but only provides aggregate measurements. However, debugging applicationspecific problems requires perflow measurements, since different flows may exhibit significantly different characteristics even when they are traversing the same link. To enable finegrained perflow measurements in routers, we propose a new scalable architecture called reference latency interpolation (RLI) that is based on our observation that packets potentially belonging to different flows that are closely spaced to each other exhibit similar delay properties. In our evaluation using simulations over real traces, we show that RLI achieves a median relative error of 12% and one to two orders of magnitude higher accuracy than previous perflow measurement solutions with small overhead.