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Local Update Algorithms for Random Graphs [chapter]

Philippe Duchon, Romaric Duvignau
2014 Lecture Notes in Computer Science  
We describe and analyze several algorithms for the maintenance task; the most elaborate of our algorithms are asymptotically optimal.  ...  We study the problem of maintaining a given distribution of random graphs under an arbitrary sequence of vertex insertions and deletions.  ...  The problem of locally updating k-out graphs can be reformulated as follows: given a random uniform k-out graph G with n vertices, find a randomized procedure in order to insert (resp. delete) a vertex  ... 
doi:10.1007/978-3-642-54423-1_32 fatcat:4tpprwnxyrefpfyhpprnl2coum

Experimental analysis of dynamic all pairs shortest path algorithms

Camil Demetrescu, Giuseppe F. Italiano
2006 ACM Transactions on Algorithms  
We present the results of an extensive computational study on dynamic algorithms for all pairs shortest path problems.  ...  on random, real-world and hard instances.  ...  We are indebted to the anonymous referees for many useful comments.  ... 
doi:10.1145/1198513.1198519 fatcat:37uw7pjvrnbedmaczknnkk5n4q

Average update times for fully-dynamic all-pairs shortest paths

Tobias Friedrich, Nils Hebbinghaus
2011 Discrete Applied Mathematics  
For a random update we show that the expected time per update is bounded by O(n 4/3+ε ) for all ε > 0. If the graph is outside the critical window, we prove even smaller bounds.  ...  We study the fully-dynamic all pairs shortest path problem for graphs with arbitrary nonnegative edge weights.  ...  Acknowledgements Thanks are due to Daniel Johannsen, Frank Neumann, and Yuval Peres for various helpful discussions.  ... 
doi:10.1016/j.dam.2011.02.007 fatcat:uxqljdpy3fexxokix7pode35rq

Average Update Times for Fully-Dynamic All-Pairs Shortest Paths [chapter]

Tobias Friedrich, Nils Hebbinghaus
2008 Lecture Notes in Computer Science  
For a random update we show that the expected time per update is bounded by O(n 4/3+ε ) for all ε > 0.  ...  We study the fully-dynamic all pairs shortest path problem for graphs with arbitrary non-negative edge weights.  ...  Acknowledgements Thanks are due to Daniel Johannsen, Frank Neumann, and Yuval Peres for various helpful discussions.  ... 
doi:10.1007/978-3-540-92182-0_61 fatcat:vowyqjlnh5at7mdfdzldqqecw4

Approximate Personalized PageRank on Dynamic Graphs [article]

Hongyang Zhang, Peter Lofgren, Ashish Goel
2017 arXiv   pre-print
For Reverse Push, we prove that for an arbitrary directed graph in a random edge model, or for an arbitrary undirected graph, given a uniformly random target node t, the cost to maintain a PPR vector to  ...  For Forward Push, we show that on an arbitrary undirected graph, given a uniformly random start node s, the cost to maintain a PPR vector from s of degree-normalized error ε as k edges are updated is O  ...  Acknowledgement Research supported by the DARPA GRAPHS program via grant FA9550-12-1-0411, and by NSF grant 1447697.  ... 
arXiv:1603.07796v2 fatcat:ukzfz7o4knfezicmksqaz5b6ju

Approximate Personalized PageRank on Dynamic Graphs

Hongyang Zhang, Peter Lofgren, Ashish Goel
2016 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16  
For Reverse Push, we prove that for an arbitrary directed graph in a random edge model, or for an arbitrary undirected graph, given a uniformly random target node t, the cost to maintain a PPR vector to  ...  For Forward Push, we show that on an arbitrary undirected graph, given a uniformly random start node s, the cost to maintain a PPR vector from s of degree-normalized error ε as k edges are updated is O  ...  Research supported by the DARPA GRAPHS program via grant FA9550-12-1-0411, and by NSF grant 1447697. REFERENCES  ... 
doi:10.1145/2939672.2939804 dblp:conf/kdd/ZhangLG16 fatcat:fcc2qgip3vgufjztbuuje7z5ze

A fast adaptive layout algorithm for undirected graphs (extended abstract and system demonstration) [chapter]

Arne Frick, Andreas Ludwig, Heiko Mehldau
1995 Lecture Notes in Computer Science  
We present a randomized adaptive layout algorithm for nicely drawing undirected graphs that is based on the spring-embedder paradigm and contains several new heuristics to improve the convergence, including  ...  We give empirical data for the running time of the algorithm and the quality of the computed layouts.  ...  Conclusions In this paper, we have presented an adaptive algorithm to compute a layout for undirected graphs based on local temperatures.  ... 
doi:10.1007/3-540-58950-3_393 fatcat:f4kbc6dukfbktn4rnm2mdhdr4y

A Local Updating Algorithm for Personalized PageRank via Chebyshev Polynomials [article]

Esteban Bautista, Matthieu Latapy
2021 arXiv   pre-print
To address this limitation, this work proposes a novel distributed algorithm to locally update personalized PageRank vectors when the graph topology changes.  ...  In particular, the algorithm has the following advantages: (i) it has faster convergence speed than state-of-the-art alternatives for local PageRank updating; and (ii) it can update the solution of recent  ...  Gonçalves for helpful discussions.  ... 
arXiv:2110.02538v1 fatcat:2rkseaasovbsznopbhoem6p2ou

Accelerating PageRank using Partition-Centric Processing [article]

Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
2018 arXiv   pre-print
We also show that unlike other GAS based implementations, PCPM is able to further reduce main memory traffic by taking advantage of intelligent node labeling that enhances locality.  ...  PageRank is a fundamental link analysis algorithm that also functions as a key representative of the performance of Sparse Matrix-Vector (SpMV) multiplication.  ...  low locality graphs.  ... 
arXiv:1709.07122v4 fatcat:qhvgp5akcnekvf3f75de2q4hmm

Scale-Free Graph Processing on a NUMA Machine

Tanuj Kr Aasawat, Tahsin Reza, Matei Ripeanu
2018 2018 IEEE/ACM 8th Workshop on Irregular Applications: Architectures and Algorithms (IA3)  
Graphs incur highly irregular memory accesses which leads to poor data locality, load imbalance, and data-dependent parallelism.  ...  This poses the opportunity to transfer the know-how and design of distributed graph processing to develop shared-memory graph processing solutions optimized for NUMA systems (which is surprisingly little-explored  ...  Acknowledgments I would like to sincerely thank my advisor, Professor Matei Ripeanu for giving me  ... 
doi:10.1109/ia3.2018.00011 dblp:conf/sc/AasawatRR18 fatcat:lf2x2xyik5b2vnf3am2duzxwju

Engineering Shortest Path Algorithms [chapter]

Camil Demetrescu, Giuseppe F. Italiano
2004 Lecture Notes in Computer Science  
In this paper, we report on our own experience in studying a fundamental problem on graphs: all pairs shortest paths.  ...  In particular, we discuss the interplay between theory and practice in engineering a simple variant of Dijkstra's shortest path algorithm.  ...  in designing asymptotically fast update algorithms for the dynamic version of the problem.  ... 
doi:10.1007/978-3-540-24838-5_14 fatcat:uggagxe7gfcchbumfusicft2jy

Within network learning on big graphs using secondary memory-based random walk kernels [chapter]

Jianyi Lin, Marco Mesiti, Matteo Re, Giorgio Valentini
2016 Studies in Computational Intelligence  
In this contribution we present the application of a novel graph kernel, transductive and secondary memory-based network learning algorithm able to effectively tackle the aforementioned limitations.  ...  To our knowledge this is the first time a graph kernel learning method is applied to a so large biological network.  ...  of the random walk resolved at the i th node of the graph, and can be viewed as a "local" version of (1): by updating all the nodes i of the graph, 1 ≤ i ≤ n, we update the probability vector p t+1 exactly  ... 
doi:10.1007/978-3-319-50901-3_19 fatcat:ukd4z5rxrnexnakq5donmf5ln4

Belief-propagation-guided Monte-Carlo sampling

Aurélien Decelle, Florent Krzakala
2014 Physical Review B  
This appoach is best adapted for locally tree like graphs, it is therefore tested on the hard cases of spin-glass models for random graphs demonstrating its state-of-the art status in those cases.  ...  A Monte-Carlo algorithm for discrete statistical models that combines the full power of the Belief Propagation algorithm with the advantages of a detailed-balanced heat bath approach is presented.  ...  This approach is best adapted for locally tree-like graphs and we therefore tested it on random graphs for hard models such as spin-glasses, demonstrating its state-of-the art status in those cases.  ... 
doi:10.1103/physrevb.89.214421 fatcat:hczmh7ovmvakpa52f25onlwfae

Parallel Local Graph Clustering [article]

Julian Shun, Farbod Roosta-Khorasani, Kimon Fountoulakis, Michael W. Mahoney
2019 arXiv   pre-print
Motivated partly by this, so-called local algorithms for graph clustering have received significant interest due to the fact that they can find good clusters in a graph with work proportional to the size  ...  for real-world graphs of interest.  ...  We thank the Intel Labs Academic Research Office for the Parallel Algorithms for Non-Numeric Computing Program for providing the machine for our experiments.  ... 
arXiv:1604.07515v3 fatcat:3tjrutygj5ebjpbnasqy63xhpa

Simulating Large-scale Dynamic Random Graphs in OMNeT++

Kristjan Jonsson, Ymir Vigfusson, Olafur Helgason
2012 Proceedings of the Fifth International Conference on Simulation Tools and Techniques  
We present a set of components for the OMNeT++ discrete event simulator which enable efficient modeling of large-scale random graphs that capture real-world properties, e.g. scalefree networks and small-world  ...  The complexities of the network are abstracted into a single component while enabling detailed end-system modeling in a realistic connectivity graph.  ...  ACKNOWLEDGEMENTS The authors thank Karl Palmskog for his input to this project as well as review of the manuscript. We also like to thank the anonymous reviewers for their valuable comments.  ... 
doi:10.4108/icst.simutools.2012.247732 dblp:conf/simutools/JonssonVH12 fatcat:bqypcuqdmbd4rjmd7iey5bxf6y
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