8,236 research outputs found
Connectivity measures for internet topologies.
The topology of the Internet has initially been modelled as an undirected graph, where vertices correspond to so-called Autonomous Systems (ASs),and edges correspond to physical links between pairs of ASs. However, in order to capture the impact of routing policies, it has recently become apparent that one needs to classify the edges according to the existing economic relationships (customer-provider, peer-to-peer or siblings) between the ASs. This leads to a directed graph model in which traffic can be sent only along so-called valley-free paths. Four different algorithms have been proposed in the literature for inferring AS relationships using publicly available data from routing tables. We investigate the differences in the graph models produced by these algorithms, focussing on connectivity measures. To this aim, we compute the maximum number of vertex-disjoint valley-free paths between ASs as well as the size of a minimum cut separating a pair of ASs. Although these problems are solvable in polynomial time for ordinary graphs, they are NP-hard in our setting. We formulate the two problems as integer programs, and we propose a number of exact algorithms for solving them. For the problem of finding the maximum number of vertex-disjoint paths, we discuss two algorithms; the first one is a branch-and-price algorithm based on the IP formulation, and the second algorithm is a non LP based branch-and-bound algorithm. For the problem of finding minimum cuts we use a branch-and-cut algo rithm, based on the IP formulation of this problem. Using these algorithms, we obtain exact solutions for both problems in reasonable time. It turns out that there is a large gap in terms of the connectivity measures between the undirected and directed models. This finding supports our conclusion that economic relationships need to be taken into account when building a topology of the Internet.Research; Internet;
Catalog Matching with Astrometric Correction and its Application to the Hubble Legacy Archive
Object cross-identification in multiple observations is often complicated by
the uncertainties in their astrometric calibration. Due to the lack of standard
reference objects, an image with a small field of view can have significantly
larger errors in its absolute positioning than the relative precision of the
detected sources within. We present a new general solution for the relative
astrometry that quickly refines the World Coordinate System of overlapping
fields. The efficiency is obtained through the use of infinitesimal 3-D
rotations on the celestial sphere, which do not involve trigonometric
functions. They also enable an analytic solution to an important step in making
the astrometric corrections. In cases with many overlapping images, the correct
identification of detections that match together across different images is
difficult to determine. We describe a new greedy Bayesian approach for
selecting the best object matches across a large number of overlapping images.
The methods are developed and demonstrated on the Hubble Legacy Archive, one of
the most challenging data sets today. We describe a novel catalog compiled from
many Hubble Space Telescope observations, where the detections are combined
into a searchable collection of matches that link the individual detections.
The matches provide descriptions of astronomical objects involving multiple
wavelengths and epochs. High relative positional accuracy of objects is
achieved across the Hubble images, often sub-pixel precision in the order of
just a few milli-arcseconds. The result is a reliable set of high-quality
associations that are publicly available online.Comment: 9 pages, 9 figures, accepted for publication in the Astrophysical
Journa
Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches
We implemented three recently proposed approaches to the identification of
overlapping and hierarchical substructures in graphs and applied the
corresponding algorithms to a network of 492 information-science papers coupled
via their cited sources. The thematic substructures obtained and overlaps
produced by the three hierarchical cluster algorithms were compared to a
content-based categorisation, which we based on the interpretation of titles
and keywords. We defined sets of papers dealing with three topics located on
different levels of aggregation: h-index, webometrics, and bibliometrics. We
identified these topics with branches in the dendrograms produced by the three
cluster algorithms and compared the overlapping topics they detected with one
another and with the three pre-defined paper sets. We discuss the advantages
and drawbacks of applying the three approaches to paper networks in research
fields.Comment: 18 pages, 9 figure
Scheduling MapReduce Jobs under Multi-Round Precedences
We consider non-preemptive scheduling of MapReduce jobs with multiple tasks
in the practical scenario where each job requires several map-reduce rounds. We
seek to minimize the average weighted completion time and consider scheduling
on identical and unrelated parallel processors. For identical processors, we
present LP-based O(1)-approximation algorithms. For unrelated processors, the
approximation ratio naturally depends on the maximum number of rounds of any
job. Since the number of rounds per job in typical MapReduce algorithms is a
small constant, our scheduling algorithms achieve a small approximation ratio
in practice. For the single-round case, we substantially improve on previously
best known approximation guarantees for both identical and unrelated
processors. Moreover, we conduct an experimental analysis and compare the
performance of our algorithms against a fast heuristic and a lower bound on the
optimal solution, thus demonstrating their promising practical performance
Bi-Criteria and Approximation Algorithms for Restricted Matchings
In this work we study approximation algorithms for the \textit{Bounded Color
Matching} problem (a.k.a. Restricted Matching problem) which is defined as
follows: given a graph in which each edge has a color and a profit
, we want to compute a maximum (cardinality or profit)
matching in which no more than edges of color are
present. This kind of problems, beside the theoretical interest on its own
right, emerges in multi-fiber optical networking systems, where we interpret
each unique wavelength that can travel through the fiber as a color class and
we would like to establish communication between pairs of systems. We study
approximation and bi-criteria algorithms for this problem which are based on
linear programming techniques and, in particular, on polyhedral
characterizations of the natural linear formulation of the problem. In our
setting, we allow violations of the bounds and we model our problem as a
bi-criteria problem: we have two objectives to optimize namely (a) to maximize
the profit (maximum matching) while (b) minimizing the violation of the color
bounds. We prove how we can "beat" the integrality gap of the natural linear
programming formulation of the problem by allowing only a slight violation of
the color bounds. In particular, our main result is \textit{constant}
approximation bounds for both criteria of the corresponding bi-criteria
optimization problem
Spanning trees with few branch vertices
A branch vertex in a tree is a vertex of degree at least three. We prove
that, for all , every connected graph on vertices with minimum
degree at least contains a spanning tree having at most
branch vertices. Asymptotically, this is best possible and solves, in less
general form, a problem of Flandrin, Kaiser, Ku\u{z}el, Li and Ryj\'a\u{c}ek,
which was originally motivated by an optimization problem in the design of
optical networks.Comment: 20 pages, 2 figures, to appear in SIAM J. of Discrete Mat
Hamilton cycles in dense vertex-transitive graphs
A famous conjecture of Lov\'asz states that every connected vertex-transitive
graph contains a Hamilton path. In this article we confirm the conjecture in
the case that the graph is dense and sufficiently large. In fact, we show that
such graphs contain a Hamilton cycle and moreover we provide a polynomial time
algorithm for finding such a cycle.Comment: 26 pages, 3 figures; referees' comments incorporated; accepted for
publication in Journal of Combinatorial Theory, series
Relative volume of separable bipartite states
Every choice of an orthonormal frame in the d-dimensional Hilbert space of a
system corresponds to one set of all mutually commuting density matrices or,
equivalently, a classical statistical state space of the system; the quantum
state space itself can thus be profitably viewed as an SU(d) orbit of classical
state spaces, one for each orthonormal frame. We exploit this connection to
study the relative volume of separable states of a bipartite quantum system.
While the two-qubit case is studied in considerable analytic detail, for higher
dimensional systems we fall back on Monte Carlo. Several new insights seem to
emerge from our study.Comment: Essentially the published versio
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