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An Efficient Parallel Method for Performing Concurrent Operations on Social Networks

机译:在社交网络上执行并行操作的高效并行方法

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This paper presents our approach to optimize the concurrent operations on a large-scale social network. Here, we focus on the directed, unweighted relationships among members in a social network. It can then be illustrated as a directed, unweighted graph. With such a large-scale dynamic social network, we face the problem of having concurrent operations from adding or removing edges dynamically while one may ask to determine the relationship between two members. To solve this challenge, we propose an efficient parallel method based on (i) utilizing an appropriate data structure, (ii) optimizing the updating actions and (iii) improving the performance of query processing by both reducing the searching space and computing in multi-threaded parallel. Our method was validated by the datasets from SigMod Contest 2016 and SNAP DataSet Collections with the good experimental results compared to other solutions.
机译:本文介绍了我们在大型社交网络上优化并发操作的方法。在这里,我们专注于社交网络中成员之间的定向,非加权关系。然后可以将其显示为有向图,未加权图。有了如此大规模的动态社交网络,我们面临着动态地添加或删除边的同时操作的问题,而人们可能会要求确定两个成员之间的关系。为解决这一挑战,我们提出了一种有效的并行方法,该方法基于(i)利用适当的数据结构,(ii)优化更新操作,(iii)通过减少搜索空间和多级计算来提高查询处理的性能。螺纹平行。与其他解决方案相比,我们的方法已通过SigMod竞赛2016和SNAP数据集的数据集进行了验证,并具有良好的实验结果。

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