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An Efficient Parallel Method for Performing Concurrent Operations on Social Networks

机译:一种有效的并行方法,用于在社交网络上执行并发操作

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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运营的方法。在这里,我们专注于社交网络成员之间的指示,未加权关系。然后可以将其被称为指向的未加权图。利用如此大规模的动态社交网络,我们面临着在动态添加或移除边缘的同时进行并发操作的问题,而可以要求确定两个成员之间的关系。为了解决这一挑战,我们提出了一种基于(i)的有效的并行方法,利用适当的数据结构,(ii)优化更新动作和(iii)通过减少搜索空间和计算来提高查询处理的性能。平行螺纹。我们的方法由Sigmod竞赛2016年的数据集验证,并与其他解决方案相比,使用良好的实验结果进行快速数据集收集。

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