Abstract
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.
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Du, PH., Pham, HD., Nguyen, NH. (2017). An Efficient Parallel Method for Performing Concurrent Operations on Social Networks. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_15
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DOI: https://doi.org/10.1007/978-3-319-67074-4_15
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