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[19]Isabelle Stanton and Gabriel Kliot.Streaming graph partitioning for large distributed graphs.In Pro- ceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining KDD).2012. [20]Charalampos Tsourakakis,Christos Gkantsidis,Bozidar Radunovic,and Milan Voinovic.Fennel:Stream- ing graph partitioning for massive scale graphs.In Proceedings of the 7th ACM International Conference on Web Search and Data Mining (WSDM),2014. [21]Lu Wang,Yanghua Xiao,Bin Shao,and Haixun Wang.How to partition a billion-node graph.In Pro- ceedings of the International Conference on Data Engineering (ICDE),2014. 9References [1] Lada A Adamic and Bernardo A Huberman. Zipf’s law and the internet. Glottometrics, 3(1):143–150, 2002. [2] Paolo Boldi and Sebastiano Vigna. The webgraph framework I: compression techniques. In Proceedings of the 13th international conference on World Wide Web (WWW), 2004. [3] Andrei Broder, Ravi Kumar, Farzin Maghoul, Prabhakar Raghavan, Sridhar Rajagopalan, Raymie Stata, Andrew Tomkins, and Janet Wiener. Graph structure in the web. Computer networks, 33(1):309–320, 2000. [4] Rong Chen, Jiaxin Shi, Yanzhe Chen, Haibing Guan, and Haibo Chen. Powerlyra: Differentiated graph computation and partitioning on skewed graphs. Technical Report IPADSTR-2013-001, Institute of Par￾allel and Distributed Systems, Shanghai Jiao Tong University, 2013. [5] Aaron Clauset, Cosma Rohilla Shalizi, and Mark EJ Newman. Power-law distributions in empirical data. SIAM review, 51(4):661–703, 2009. [6] Timothy A Davis and Yifan Hu. The University of Florida sparse matrix collection. ACM Transactions on Mathematical Software, 38(1):1, 2011. [7] Joseph E Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson, and Carlos Guestrin. Powergraph: Dis￾tributed graph-parallel computation on natural graphs. In Proceedings of the 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2012. [8] Joseph E. Gonzalez, Reynold S. Xin, Ankur Dave, Daniel Crankshaw, Michael J. Franklin, and Ion Stoica. GraphX: Graph processing in a distributed dataflow framework. In Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2014. [9] Nilesh Jain, Guangdeng Liao, and Theodore L Willke. Graphbuilder: scalable graph etl framework. In Proceedings of the First International Workshop on Graph Data Management Experiences and Systems, 2013. [10] George Karypis and Vipin Kumar. Multilevel graph partitioning schemes. In Proceedings of the Interna￾tional Conference on Parallel Processing (ICPP), 1995. [11] Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon. What is twitter, a social network or a news media. In Proceedings of the 19th international conference on World Wide Web (WWW), 2010. [12] Aapo Kyrola, Guy E. Blelloch, and Carlos Guestrin. Graphchi: Large-scale graph computation on just a PC. In Proceedings of the 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2012. [13] Jure Leskovec. Stanford large network dataset collection. URL http://snap. stanford. edu/data/index. html, 2011. [14] Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Heller￾stein. GraphLab: A new framework for parallel machine learning. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2010. [15] Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Heller￾stein. Distributed graphlab: A framework for machine learning in the cloud. In Proceedings of the International Conference on Very Large Data Bases (VLDB), 2012. [16] Grzegorz Malewicz, Matthew H Austern, Aart JC Bik, James C Dehnert, Ilan Horn, Naty Leiser, and Grzegorz Czajkowski. Pregel: a system for large-scale graph processing. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2010. [17] Alan Mislove, Massimiliano Marcon, Krishna P Gummadi, Peter Druschel, and Bobby Bhattacharjee. Measurement and analysis of online social networks. In Proceedings of the 7th ACM SIGCOMM confer￾ence on Internet Measurement, 2007. [18] Martin Raab and Angelika Steger. balls into binsa simple and tight analysis. In Randomization and Approximation Techniques in Computer Science, pages 159–170. Springer, 1998. [19] Isabelle Stanton and Gabriel Kliot. Streaming graph partitioning for large distributed graphs. In Pro￾ceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012. [20] Charalampos Tsourakakis, Christos Gkantsidis, Bozidar Radunovic, and Milan Vojnovic. Fennel: Stream￾ing graph partitioning for massive scale graphs. In Proceedings of the 7th ACM International Conference on Web Search and Data Mining (WSDM), 2014. [21] Lu Wang, Yanghua Xiao, Bin Shao, and Haixun Wang. How to partition a billion-node graph. In Pro￾ceedings of the International Conference on Data Engineering (ICDE), 2014. 9