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Frontiers of Computer Science

Front. Comput. Sci.    2018, Vol. 12 Issue (6) : 1076-1089     https://doi.org/10.1007/s11704-016-6109-y
RESEARCH ARTICLE |
IncPregel: an incremental graph parallel computation model
Qiang LIU1, Xiaoshe DONG1, Heng CHEN1(), Yinfeng WANG2
1. School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
2. Shenzhen Institute of Information Technology, Shenzhen 518172, China
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Abstract

Large-scale graph computation is often required in a variety of emerging applications such as social network computation and Web services. Such graphs are typically large and frequently updated with minor changes. However, re-computing an entire graphwhen a fewvertices or edges are updated is often prohibitively expensive. To reduce the cost of such updates, this study proposes an incremental graph computation model called IncPregel, which leverages the nonafter- effect property of the first-order Markov chain and provides incremental programming abstractions to avoid redundant computation and message communication. This is accomplished by employing an efficient and fine-grained reuse mechanism. We implemented this model on Hama, a popular open source framework based on Pregel, to construct an incremental graph processing system called IncHama. IncHama automatically detects changes in input in order to recognize “changed vertices” and to exchange reusable data by means of shuffling. The evaluation results on large-scale graphs show that, compared with Hama, IncHama is 1.1–2.7 times faster and can reduce communication messages by more than 50% when the incremental edges increase in number from 0.1 to 100k.

Keywords graph computation      Pregel      cloud computing     
Corresponding Authors: Heng CHEN   
Just Accepted Date: 08 November 2016   Online First Date: 20 December 2017    Issue Date: 04 December 2018
 Cite this article:   
Qiang LIU,Xiaoshe DONG,Heng CHEN, et al. IncPregel: an incremental graph parallel computation model[J]. Front. Comput. Sci., 2018, 12(6): 1076-1089.
 URL:  
http://journal.hep.com.cn/fcs/EN/10.1007/s11704-016-6109-y
http://journal.hep.com.cn/fcs/EN/Y2018/V12/I6/1076
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Qiang LIU
Xiaoshe DONG
Heng CHEN
Yinfeng WANG
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