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BLADYG: A Novel Block-Centric Framework for the Analysis of Large Dynamic Graphs
| Content Provider | ACM Digital Library |
|---|---|
| Author | Montresor, Alberto Velegrakis, Yannis Aridhi, Sabeur |
| Abstract | Recently, distributed processing of large dynamic graphs has become very popular, especially in certain domains such as social network analysis, Web graph analysis and spatial network analysis. In this context, many distributed/parallel graph processing systems have been proposed, such as Pregel, GraphLab, and Trinity. These systems can be divided into two categories: (1) vertex-centric and (2) block-centric approaches. In vertex-centric approaches, each vertex corresponds to a process, and message are exchanged among vertices. In block-centric approaches, the unit of computation is a block, a connected subgraph of the graph, and message exchanges occur among blocks. In this paper, we are considering the issues of scale and dynamism in the case of block-centric approaches. We present BLADYG, a block-centric framework that addresses the issue of dynamism in large-scale graphs. We present an implementation of BLADYG on top of AKKA framework. We experimentally evaluate the performance of the proposed framework. |
| Starting Page | 39 |
| Ending Page | 42 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450343503 |
| DOI | 10.1145/2915516.2915525 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-05-31 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Dynamic graphs Akka framework Distributed graph processing |
| Content Type | Text |
| Resource Type | Article |
