圖算法相關的論文

圖算法的一些論文

###0. 最普通的模型ios

  • MapReduce
  • Pregel
  • PowerGraph
  • GraphLab
  • GraphX
  • Giraph
  • GraphChi

###1. 改進的模型 主要針對的問題:vertex/edge-centric 收斂的慢,局部性信息丟失嚴重
Zhou Y, Liu L, Lee K, et al. GraphTwist: fast iterative graph computation with two-tier optimizations[J]. Proceedings of the Vldb Endowment, 2015, 8(11):1262-1273.
http://www.cc.gatech.edu/~lingliu/papers/2015/VLDB15-GraphTwist.pdfweb

Simmhan Y, Kumbhare A, Wickramaarachchi C, et al. GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics[J]. 2013, 8632:451-462.
http://www-scf.usc.edu/~kumbhare/pubs/simmhan-europar-2014-camera-ready.pdf算法

Yuan P, Zhang W, Xie C, et al. Fast Iterative Graph Computation: A Path Centric Approach[C]// High Performance Computing, Networking, Storage and Analysis, SC14: International Conference for. IEEE, 2015:401-412.
http://www.cc.gatech.edu/~lingliu/papers/2014/graphdb-sc14.pdfapp

Yan D, Cheng J, Lu Y, et al. Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs[C]// VLDB Endowment. 2014.
http://www.cse.ust.hk/faculty/wilfred/paper/vldb14b.pdfdom

Erwig M. The graph Voronoi diagram with applications[J]. Networks, 2015, 36(3):156-163.
http://web.engr.oregonstate.edu/~erwig/papers/GraphVoronoi_Networks00.pdfurl

###2. 改進的模型 爲解決label-diffusion (value propagation)太慢.net

###3. 改進的模型 爲解決圖劃分和負載不均衡
Avery Ching, Sergey Edunov, Maja Kabiljo, Dionysios Logothetis, Sambavi Muthukrishnan, One Trillion Edges: Graph Processing at Facebook-Scale. Proceedings of the VLDB Endowment, Vol. 8, No. 12, (2015)
http://www.vldb.org/pvldb/vol8/p1804-ching.pdfscala

Xin, R. S., Crankshaw, D., Dave, A., Gonzalez, J. E., Franklin, M. J., & Stoica, I. GraphX: Unifying Data-Parallel and Graph-Parallel Analytics. arXiv preprint arXiv:1402.2394. (2014)
http://arxiv.org/pdf/1402.2394code

Martella, Claudio et al. Spinner: scalable graph partitioning for the cloud. arXiv, (2014).
http://arxiv.org/pdf/1404.3861v1.pdform

Khayyat, Zuhair, et al. Mizan: a system for dynamic load balancing in large-scale graph processing. Proceedings of the 8th ACM European Conference on Computer Systems. ACM, (2013).
http://www.cs.cornell.edu/~djwill/pubs/mizan.pdf

Salihoglu, Semih, & Jennifer Widom. Gps: A graph processing system. Proceedings of the 25th International Conference on Scientific and Statistical Database Management. ACM, (2013).
http://ilpubs.stanford.edu:8090/1039/7/gps_ssdbm.pdf

Tian, Y., Balmin, A., Corsten, S. A., Tatikonda, S., & McPherson, J. From Think Like a Vertex to Think Like a Graph. Proceedings of the VLDB Endowment, 7(3). (2013)
http://researcher.ibm.com/researcher/files/us-ytian/giraph++.pdf

Schelter, S., Ewen, S., Tzoumas, K., & Markl, V. All roads lead to Rome: optimistic recovery for distributed iterative data processing. In Proceedings of the 22nd ACM international conference on Conference on information & knowledge management (pp. 1919-1928). ACM. (2013, October).
http://stratosphere.eu/assets/papers/optimistic.pdf

Ewen, S., Tzoumas, K., Kaufmann, M., & Markl, V. Spinning fast iterative data flows. Proceedings of the VLDB Endowment, 5(11), 1268-1279. (2012).
http://arxiv.org/pdf/1208.0088.pdf?origin=publication_detail

Malewicz, Grzegorz, et al. Pregel: a system for large-scale graph processing. Proceedings of the 2010 ACM SIGMOD International Conference on Management of data. ACM, (2010).
http://static.cs.brown.edu/courses/csci2270/papers/pregel.pdf

Valiant, Leslie G. A bridging model for parallel computation. Communications of the ACM 33.8 : 103-111. (1990).
http://web.mit.edu/6.976/www/handout/valiant2.pdf

Hong, Sungpack, et al. Green-Marl: a DSL for easy and efficient graph analysis. ACM SIGARCH Computer Architecture News. Vol. 40. No. 1. ACM, (2012).
http://www.cl.cam.ac.uk/~ey204/teaching/ACS/R202_2012_2013/papers/S7_Network_Structure/papers/hong_asplos_2012.pdf

Salihoglu, Semih, and Jennifer Widom. Optimizing Graph Algorithms on Pregel-like Systems. (2014).
http://ilpubs.stanford.edu:8090/1077/3/p535-salihoglu.pdf

Salihoglu, Semih, and Jennifer Widom. HelP: High-level Primitives For Large-Scale Graph Processing.
http://ilpubs.stanford.edu:8090/1085/2/primitives_tr_sig_alternate.pdf

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