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Large-scale graph computation is central to applications ranging from language processing to social networks. However, natural graphs tend to have skewed power-law distributions where a small subset of the vertices have a large number of neighbors. Existing graph-parallel systems suffer from load imbalance, high communication cost, or suboptimal and complex processing. In this paper we present GraphA,...
This paper presents SMARTPARTITION, an efficient approach to partition large-scala natural graphs [5]. We design a new partitioning algorithm which can perceive graph layout locality to improve the performance of graph computation. Experimental results demonstrate that SMARTPARTITION can achieve significant reduction in ingress time and execution time for both real-world and synthetic graph datasets.
Skyline queries have played an increasingly important role in many applications such as web mining, multi-preference analysis and decision making. Most existing studies mainly focus on centralized systems, and skyline query processing in distributed environments is still an emerging and challenging topic. In this paper we propose SkyStorm, a delay-bounded skyline computing approach by exploiting the...
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