Pegah Sattari

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Network tomography infers internal network characteristics by sending and collecting probe packets from the network edge. Traditional tomographic techniques for general topologies typically use a mesh of multicast trees and/or unicast paths to cover the entire graph, which is suboptimal from the point of view of bandwidth efciency and estimation accuracy.(More)
Traceback schemes aim at identifying the source(s) of a sequence of packets and the nodes these packets traversed. This is useful for tracing the sources of high volume traffic, e.g., in Distributed Denial-of-Service (DDoS) attacks. In this paper, we are particularly interested in Probabilistic Packet Marking (PPM) schemes, where(More)
Our goal is to infer the topology of a network when (i) we can send probes between sources and receivers at the edge of the network and (ii) intermediate nodes can perform simple network coding operations, i.e., additions. Our key intuition is that network coding introduces topology-dependent correlation in the observations at the receivers, which can be(More)
In this paper, we combine network coding and tomographic techniques for topology inference. Our goal is to infer the topology of a network by sending probes between a given set of multiple sources and multiple receivers and by having intermediate nodes perform network coding operations. We combine and extend two ideas that have been developed independently.(More)
Loss tomography aims at inferring the loss rate of links in a network from end-to-end measurements. Previous work has developed optimal maximum likelihood estimators (MLEs) for link loss rates in a single-source multicast tree. However, only sub-optimal algorithms have been developed for multiple-source loss tomography. In this paper, we revisit(More)
Traceback schemes aim at identifying the source(s) of a sequence of packets and the nodes these packets have traversed. We are particularly interested in algebraic traceback, which encodes the IDs of nodes on a single path as coefficients of a polynomial in a finite field, and determines the polynomial by evaluating it at different points. So far, algebraic(More)
Traceback schemes aim at identifying the source(s) of a sequence of packets and the nodes these packets traversed. This is useful for tracing the sources of high volume traffic, e.g., in Distributed Denial-of-Service (DDoS) attacks. In this paper, we are interested in Probabilistic Packet Marking (PPM) schemes, in which intermediate nodes probabilistically(More)
We consider the problem of inferring the topology of a network with M sources and N receivers (an M-by- N network), by sending probes between the sources and receivers. Prior work has shown that this problem can be decomposed into two parts: first, infer smaller subnetwork components (1-by- N's or 2-by-2's) and then merge them to identify the M-by- N(More)
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