Title: BLADYG: A Graph Processing Framework for Large Dynamic Graphs,
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.