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On the Bias of Traceroute Sampling; or, Power-law Degree Distributions in Regular Graphs  [PDF]
Dimitris Achlioptas,Aaron Clauset,David Kempe,Cristopher Moore
Mathematics , 2005,
Abstract: Understanding the structure of the Internet graph is a crucial step for building accurate network models and designing efficient algorithms for Internet applications. Yet, obtaining its graph structure is a surprisingly difficult task, as edges cannot be explicitly queried. Instead, empirical studies rely on traceroutes to build what are essentially single-source, all-destinations, shortest-path trees. These trees only sample a fraction of the network's edges, and a recent paper by Lakhina et al. found empirically that the resuting sample is intrinsically biased. For instance, the observed degree distribution under traceroute sampling exhibits a power law even when the underlying degree distribution is Poisson. In this paper, we study the bias of traceroute sampling systematically, and, for a very general class of underlying degree distributions, calculate the likely observed distributions explicitly. To do this, we use a continuous-time realization of the process of exposing the BFS tree of a random graph with a given degree distribution, calculate the expected degree distribution of the tree, and show that it is sharply concentrated. As example applications of our machinery, we show how traceroute sampling finds power-law degree distributions in both delta-regular and Poisson-distributed random graphs. Thus, our work puts the observations of Lakhina et al. on a rigorous footing, and extends them to nearly arbitrary degree distributions.
Network Inference from TraceRoute Measurements: Internet Topology `Species'  [PDF]
Fabien Viger,Alain Barrat,Luca Dall'Asta,Cun-Hui Zhang,Eric D. Kolaczyk
Physics , 2005, DOI: 10.1103/PhysRevE.75.056111
Abstract: Internet mapping projects generally consist in sampling the network from a limited set of sources by using traceroute probes. This methodology, akin to the merging of spanning trees from the different sources to a set of destinations, leads necessarily to a partial, incomplete map of the Internet. Accordingly, determination of Internet topology characteristics from such sampled maps is in part a problem of statistical inference. Our contribution begins with the observation that the inference of many of the most basic topological quantities -- including network size and degree characteristics -- from traceroute measurements is in fact a version of the so-called `species problem' in statistics. This observation has important implications, since species problems are often quite challenging. We focus here on the most fundamental example of a traceroute internet species: the number of nodes in a network. Specifically, we characterize the difficulty of estimating this quantity through a set of analytical arguments, we use statistical subsampling principles to derive two proposed estimators, and we illustrate the performance of these estimators on networks with various topological characteristics.
Bias reduction in traceroute sampling: towards a more accurate map of the Internet  [PDF]
Abraham D. Flaxman,Juan Vera
Physics , 2007, DOI: 10.1007/978-3-540-77004-6_1
Abstract: Traceroute sampling is an important technique in exploring the internet router graph and the autonomous system graph. Although it is one of the primary techniques used in calculating statistics about the internet, it can introduce bias that corrupts these estimates. This paper reports on a theoretical and experimental investigation of a new technique to reduce the bias of traceroute sampling when estimating the degree distribution. We develop a new estimator for the degree of a node in a traceroute-sampled graph; validate the estimator theoretically in Erdos-Renyi graphs and, through computer experiments, for a wider range of graphs; and apply it to produce a new picture of the degree distribution of the autonomous system graph.
Traceroute sampling makes random graphs appear to have power law degree distributions  [PDF]
Aaron Clauset,Cristopher Moore
Physics , 2003, DOI: 10.1103/PhysRevLett.94.018701
Abstract: The topology of the Internet has typically been measured by sampling traceroutes, which are roughly shortest paths from sources to destinations. The resulting measurements have been used to infer that the Internet's degree distribution is scale-free; however, many of these measurements have relied on sampling traceroutes from a small number of sources. It was recently argued that sampling in this way can introduce a fundamental bias in the degree distribution, for instance, causing random (Erdos-Renyi) graphs to appear to have power law degree distributions. We explain this phenomenon analytically using differential equations to model the growth of a breadth-first tree in a random graph G(n,p=c/n) of average degree c, and show that sampling from a single source gives an apparent power law degree distribution P(k) ~ 1/k for k < c.
Detection, Understanding, and Prevention of Traceroute Measurement Artifacts  [PDF]
Fabien Viger,Brice Augustin,Xavier Cuvellier,Clemence Magnien,Matthieu Latapy,Timur Friedman,Renata Teixeira
Computer Science , 2009,
Abstract: Traceroute is widely used: from the diagnosis of network problems to the assemblage of internet maps. Unfortu- nately, there are a number of problems with traceroute methodology, which lead to the inference of erroneous routes. This paper studies particular structures arising in nearly all traceroute measurements. We characterize them as "loops", "cycles", and "diamonds". We iden- tify load balancing as a possible cause for the appear- ance of false loops, cycles and diamonds, i.e., artifacts that do not represent the internet topology. We pro- vide a new publicly-available traceroute, called Paris traceroute, which, by controlling the packet header con- tents, provides a truer picture of the actual routes that packets follow. We performed measurements, from the perspective of a single source tracing towards multiple destinations, and Paris traceroute allowed us to show that many of the particular structures we observe are indeed traceroute measurement artifacts.
On the complexity of deciding whether the distinguishing chromatic number of a graph is at most two  [PDF]
Elaine M. Eschen,Chinh T. Hoang,R. Sritharan,Lorna Stewart
Computer Science , 2009,
Abstract: In an article [3] published recently in this journal, it was shown that when k >= 3, the problem of deciding whether the distinguishing chromatic number of a graph is at most k is NP-hard. We consider the problem when k = 2. In regards to the issue of solvability in polynomial time, we show that the problem is at least as hard as graph automorphism but no harder than graph isomorphism.
Deciding the Bell number for hereditary graph properties  [PDF]
Aistis Atminas,Andrew Collins,Jan Foniok,Vadim V. Lozin
Mathematics , 2014,
Abstract: The paper [J. Balogh, B. Bollob\'{a}s, D. Weinreich, A jump to the Bell number for hereditary graph properties, J. Combin. Theory Ser. B 95 (2005) 29--48] identifies a jump in the speed of hereditary graph properties to the Bell number $B_n$ and provides a partial characterisation of the family of minimal classes whose speed is at least $B_n$. In the present paper, we give a complete characterisation of this family. Since this family is infinite, the decidability of the problem of determining if the speed of a hereditary property is above or below the Bell number is questionable. We answer this question positively by showing that there exists an algorithm which, given a finite set $\mathcal{F}$ of graphs, decides whether the speed of the class of graphs containing no induced subgraphs from the set $\mathcal{F}$ is above or below the Bell number. For properties defined by infinitely many minimal forbidden induced subgraphs, the speed is known to be above the Bell number.
Average Degree in Graph Powers  [PDF]
Matt DeVos,Jessica McDonald,Diego Scheide
Mathematics , 2010,
Abstract: The kth power of a simple graph G, denoted G^k, is the graph with vertex set V(G) where two vertices are adjacent if they are within distance k in G. We are interested in finding lower bounds on the average degree of G^k. Here we prove that if G is connected with minimum degree d > 2 and |V(G)| > (8/3)d, then G^4 has average degree at least (7/3)d. We also prove that if G is a connected d-regular graph on n vertices with diameter at least 3k+3, then the average degree of G^{3k+2} is at least (2k+1)(d+1) - k(k+1) (d+1)^2/n - 1. Both of these results are shown to be essentially best possible; the second is best possible even when n/d is arbitrarily large.
Graph Minors and Minimum Degree  [PDF]
Ga?per Fijav?,David R. Wood
Mathematics , 2008,
Abstract: Let $\mathcal{D}_k$ be the class of graphs for which every minor has minimum degree at most $k$. Then $\mathcal{D}_k$ is closed under taking minors. By the Robertson-Seymour graph minor theorem, $\mathcal{D}_k$ is characterised by a finite family of minor-minimal forbidden graphs, which we denote by $\widehat{\mathcal{D}}_k$. This paper discusses $\widehat{\mathcal{D}}_k$ and related topics. We obtain four main results: We prove that every $(k+1)$-regular graph with less than ${4/3}(k+2)$ vertices is in $\widehat{\mathcal{D}}_k$, and this bound is best possible. We characterise the graphs in $\widehat{\mathcal{D}}_{k+1}$ that can be obtained from a graph in $\widehat{\mathcal{D}}_k$ by adding one new vertex. For $k\leq 3$ every graph in $\widehat{\mathcal{D}}_k$ is $(k+1)$-connected, but for large $k$, we exhibit graphs in $\widehat{\mathcal{D}}_k$ with connectivity 1. In fact, we construct graphs in $\mathcal{D}_k$ with arbitrary block structure. We characterise the complete multipartite graphs in $\widehat{\mathcal{D}}_k$, and prove analogous characterisations with minimum degree replaced by connectivity, treewidth, or pathwidth.
On fractional realizations of graph degree sequences  [PDF]
Michael D. Barrus
Mathematics , 2013,
Abstract: We introduce fractional realizations of a graph degree sequence and a closely associated convex polytope. Simple graph realizations correspond to a subset of the vertices of this polytope. We describe properties of the polytope vertices and characterize degree sequences for which each polytope vertex corresponds to a simple graph realization. These include the degree sequences of pseudo-split graphs, and we characterize their realizations both in terms of forbidden subgraphs and graph structure.
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