206 research outputs found

    Distributed Approximation Algorithms for Weighted Shortest Paths

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    A distributed network is modeled by a graph having nn nodes (processors) and diameter DD. We study the time complexity of approximating {\em weighted} (undirected) shortest paths on distributed networks with a O(logn)O(\log n) {\em bandwidth restriction} on edges (the standard synchronous \congest model). The question whether approximation algorithms help speed up the shortest paths (more precisely distance computation) was raised since at least 2004 by Elkin (SIGACT News 2004). The unweighted case of this problem is well-understood while its weighted counterpart is fundamental problem in the area of distributed approximation algorithms and remains widely open. We present new algorithms for computing both single-source shortest paths (\sssp) and all-pairs shortest paths (\apsp) in the weighted case. Our main result is an algorithm for \sssp. Previous results are the classic O(n)O(n)-time Bellman-Ford algorithm and an O~(n1/2+1/2k+D)\tilde O(n^{1/2+1/2k}+D)-time (8klog(k+1)1)(8k\lceil \log (k+1) \rceil -1)-approximation algorithm, for any integer k1k\geq 1, which follows from the result of Lenzen and Patt-Shamir (STOC 2013). (Note that Lenzen and Patt-Shamir in fact solve a harder problem, and we use O~()\tilde O(\cdot) to hide the O(\poly\log n) term.) We present an O~(n1/2D1/4+D)\tilde O(n^{1/2}D^{1/4}+D)-time (1+o(1))(1+o(1))-approximation algorithm for \sssp. This algorithm is {\em sublinear-time} as long as DD is sublinear, thus yielding a sublinear-time algorithm with almost optimal solution. When DD is small, our running time matches the lower bound of Ω~(n1/2+D)\tilde \Omega(n^{1/2}+D) by Das Sarma et al. (SICOMP 2012), which holds even when D=Θ(logn)D=\Theta(\log n), up to a \poly\log n factor.Comment: Full version of STOC 201

    Maintenance of Strongly Connected Component in Shared-memory Graph

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    In this paper, we present an on-line fully dynamic algorithm for maintaining strongly connected component of a directed graph in a shared memory architecture. The edges and vertices are added or deleted concurrently by fixed number of threads. To the best of our knowledge, this is the first work to propose using linearizable concurrent directed graph and is build using both ordered and unordered list-based set. We provide an empirical comparison against sequential and coarse-grained. The results show our algorithm's throughput is increased between 3 to 6x depending on different workload distributions and applications. We believe that there are huge applications in the on-line graph. Finally, we show how the algorithm can be extended to community detection in on-line graph.Comment: 29 pages, 4 figures, Accepted in the Conference NETYS-201

    Are Italian research assessment exercises size-biased?

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    Research assessment exercises have enjoyed ever-increasing popularity in many countries in recent years, both as a method to guide public funds allocation and as a validation tool for adopted research support policies. Italy’s most recently completed evaluation effort (VQR 2011–14) required each university to submit to the Ministry for Education, University, and Research (MIUR) 2 research products per author (3 in the case of other research institutions), chosen in such a way that the same product is not assigned to two authors belonging to the same institution. This constraint suggests that larger institutions, where collaborations among colleagues may be more frequent, could suffer a size-related bias in their evaluation scores. To validate our claim, we investigate the outcome of artificially splitting Sapienza University of Rome, one of the largest universities in Europe, in a number of separate partitions, according to several criteria, noting significant score increases for several partitioning scenarios

    SENinja: A symbolic execution plugin for Binary Ninja

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    Symbolic execution is a program analysis technique that aims to automatically identify interesting inputs for an application, using them to generate program executions covering different parts of the code. It is widely used in the context of vulnerability discovery and reverse engineering. In this paper we present SENINJA, a symbolic execution plugin for the BINARYNINJA disassembler. The tool allows the user to perform symbolic execution analyses directly within the user interface of the disassembler, and can be used to support a variety of reverse engineering tasks

    Decremental All-Pairs ALL Shortest Paths and Betweenness Centrality

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    We consider the all pairs all shortest paths (APASP) problem, which maintains the shortest path dag rooted at every vertex in a directed graph G=(V,E) with positive edge weights. For this problem we present a decremental algorithm (that supports the deletion of a vertex, or weight increases on edges incident to a vertex). Our algorithm runs in amortized O(\vstar^2 \cdot \log n) time per update, where n=|V|, and \vstar bounds the number of edges that lie on shortest paths through any given vertex. Our APASP algorithm can be used for the decremental computation of betweenness centrality (BC), a graph parameter that is widely used in the analysis of large complex networks. No nontrivial decremental algorithm for either problem was known prior to our work. Our method is a generalization of the decremental algorithm of Demetrescu and Italiano [DI04] for unique shortest paths, and for graphs with \vstar =O(n), we match the bound in [DI04]. Thus for graphs with a constant number of shortest paths between any pair of vertices, our algorithm maintains APASP and BC scores in amortized time O(n^2 \log n) under decremental updates, regardless of the number of edges in the graph.Comment: An extended abstract of this paper will appear in Proc. ISAAC 201

    Which Conference Is That? A Case Study in Computer Science

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    Conferences play a major role in some disciplines such as computer science and are often used in research quality evaluation exercises. Differently from journals and books, for which ISSN and ISBN codes provide unambiguous keys, recognizing the conference series in which a paper was published is a rather complex endeavor: There is no unique code assigned to conferences, and the way their names are written may greatly vary across years and catalogs. In this article, we propose a technique for the entity resolution of conferences based on the analysis of different semantic parts of their names. We present the results of an investigation of our technique on a dataset of 42,395 distinct computer science conference names excerpted from the DBLP computer science repository,1 which we automatically link to different authority files. With suitable data cleaning, the precision of our record linkage algorithm can be as high as 94%. A comparison with results obtainable using state-of-the-art general-purpose record linkage algorithms rounds off the article, showing that our ad hoc solution largely outperforms them in terms of the quality of the results

    Thermal signal propagation in soils in Romania: conductive and non-conductive processes

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    Temperature data recorded in 2002 and 2003 at 10 stations out of the 70 available in the Romanian automatic weather stations network are presented and analyzed in terms of the heat transfer from air to underground. The air temperature at 2 m, the soil temperatures at 0, 5, 10, 20, 50 and 100 cm below the surface as well as rain fall and snow cover thickness have been monitored. The selected locations sample various climate environments in Romania. Preliminary analytical modelling shows that soil temperatures track air temperature variations at certain locations and, consequently, the heat transfer is by conduction, while at other stations processes such as soil freezing and/or solar radiation heating play an important part in the heat flux balance at the air/soil interface. However, the propagation of the annual thermal signal in the uppermost one meter of soil is mainly by conduction; the inferred thermal diffusivity for 8 stations with continuous time series at all depth levels ranges from 3 to 10×10<sup>−7</sup> m<sup>2</sup> s<sup>−1</sup>

    Sparse Fault-Tolerant BFS Trees

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    This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph TT of the given network GG such that subsequent to the failure of a single edge or vertex, the surviving part TT' of TT still contains a BFS spanning tree for (the surviving part of) GG. Our main results are as follows. We present an algorithm that for every nn-vertex graph GG and source node ss constructs a (single edge failure) FT-BFS tree rooted at ss with O(n \cdot \min\{\Depth(s), \sqrt{n}\}) edges, where \Depth(s) is the depth of the BFS tree rooted at ss. This result is complemented by a matching lower bound, showing that there exist nn-vertex graphs with a source node ss for which any edge (or vertex) FT-BFS tree rooted at ss has Ω(n3/2)\Omega(n^{3/2}) edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source sSs\in S for some subset of sources SVS\subseteq V. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every nn-vertex graph and source set SVS \subseteq V of size σ\sigma constructs a (single failure) FT-MBFS tree T(S)T^*(S) from each source siSs_i \in S, with O(σn3/2)O(\sqrt{\sigma} \cdot n^{3/2}) edges, and on the other hand there exist nn-vertex graphs with source sets SVS \subseteq V of cardinality σ\sigma, on which any FT-MBFS tree from SS has Ω(σn3/2)\Omega(\sqrt{\sigma}\cdot n^{3/2}) edges. Finally, we propose an O(logn)O(\log n) approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no Ω(logn)\Omega(\log n) approximation algorithm for these problems under standard complexity assumptions

    Efficient Computation of Distance Labeling for Decremental Updates in Large Dynamic Graphs

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    Since today's real-world graphs, such as social network graphs, are evolving all the time, it is of great importance to perform graph computations and analysis in these dynamic graphs. Due to the fact that many applications such as social network link analysis with the existence of inactive users need to handle failed links or nodes, decremental computation and maintenance for graphs is considered a challenging problem. Shortest path computation is one of the most fundamental operations for managing and analyzing large graphs. A number of indexing methods have been proposed to answer distance queries in static graphs. Unfortunately, there is little work on answering such queries for dynamic graphs. In this paper, we focus on the problem of computing the shortest path distance in dynamic graphs, particularly on decremental updates (i.e., edge deletions). We propose maintenance algorithms based on distance labeling, which can handle decremental updates efficiently. By exploiting properties of distance labeling in original graphs, we are able to efficiently maintain distance labeling for new graphs. We experimentally evaluate our algorithms using eleven real-world large graphs and confirm the effectiveness and efficiency of our approach. More specifically, our method can speed up index re-computation by up to an order of magnitude compared with the state-of-the-art method, Pruned Landmark Labeling (PLL)

    Speeding up shortest path algorithms

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    Given an arbitrary, non-negatively weighted, directed graph G=(V,E)G=(V,E) we present an algorithm that computes all pairs shortest paths in time O(mn+mlgn+nTψ(m,n))\mathcal{O}(m^* n + m \lg n + nT_\psi(m^*, n)), where mm^* is the number of different edges contained in shortest paths and Tψ(m,n)T_\psi(m^*, n) is a running time of an algorithm to solve a single-source shortest path problem (SSSP). This is a substantial improvement over a trivial nn times application of ψ\psi that runs in O(nTψ(m,n))\mathcal{O}(nT_\psi(m,n)). In our algorithm we use ψ\psi as a black box and hence any improvement on ψ\psi results also in improvement of our algorithm. Furthermore, a combination of our method, Johnson's reweighting technique and topological sorting results in an O(mn+mlgn)\mathcal{O}(m^*n + m \lg n) all-pairs shortest path algorithm for arbitrarily-weighted directed acyclic graphs. In addition, we also point out a connection between the complexity of a certain sorting problem defined on shortest paths and SSSP.Comment: 10 page
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