Abstract
As the rapid growth of online social networks (OSNs), inter-server communications are becoming an obstacle to scaling the storage systems of OSNs. To address the problem, network partitioning and data replication are two commonly used approaches. In this paper, we exploit the combination of both approaches simultaneously and propose a data placement scheme based on overlapping communities detection. The principle behind the proposed scheme is to co-locate frequently interactive users together as long as it brings positive traffic reduction and satisfies load constraint. We conduct trace-driven experiments and the results show that our scheme significantly reduces the inter-server communications as well as preserving good load balancing.
J. Zhou—This work is supported by National Natural Science Foundation of China (No. 61502328, No. 61572337), Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No. 15KJB520032, No. 14KJB520034), Joint Innovation Funding of Jiangsu Province (No. BY2014059-02).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The hadoop distributed file system. In: MSST, pp. 1–10 (2010)
Lakshman, A., Malik, P.: Cassandra: a decentralized structured storage system. Oper. Syst. Rev. 44(2), 35–40 (2010)
Karypis, G., Kumar, V.: A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J. Sci. Comput. 20, 359–392 (1998)
Chen, H., Jin, H., Jin, N., Gu, T.: Minimizing inter-server communications by exploiting self-similarity in online social networks. In: ICNP, pp. 1–10 (2012)
Pujol, J.M., Erramilli, V., Siganos, G., Yang, X., Laoutaris, N., Chhabra, P., Rodriguez, P.: The little engine(s) that could: scaling online social networks. IEEE/ACM Trans. Netw. 20(4), 1162–1175 (2012)
Liu, G., Shen, H., Chandler, H.: Selective data replication for online social networks with distributed datacenters. In: ICNP, pp. 1–10 (2013)
Zhou, J., Fan, J., Wang, J., Cheng, B., Jia, J.: Towards traffic minimization for data placement in online social networks. Concurrency and Computation: Practice and Experience, May 2016
Wilson, C., Sala, A., Puttaswamy, K.P.N., Zhao, B.Y.: Beyond social graphs: user interactions in online social networks and their implications. ACM Trans. Web 6, 17:1–17:31 (2012)
Gjoka, M., Kurant, M., Butts, C.T., Markopoulou, A.: Walking in facebook: a case study of unbiased sampling of OSNs. In: INFOCOM, pp. 2498–2506 (2010)
Jiang, J., Wilson, C., Wang, X., Sha, W., Huang, P., Dai, Y., Zhao, B.Y.: Understanding latent interactions in online social networks. ACM Trans. Web 7, 18 (2013)
Benevenuto, F., Rodrigues, T., Cha, M., Almeida, V.A.F.: Characterizing user behavior in online social networks. In: IMC, pp. 49–62 (2009)
Tran, D.A., Nguyen, K., Pham, C.: S-clone: socially-aware data replication for social networks. Comput. Netw. 56, 2001–2013 (2012)
Yu, B., Pan, J.: Location-aware associated data placement for geo-distributed data-intensive applications. In: INFOCOM, pp. 603–611 (2015)
Tran, D.A., Zhang, T.: S-PUT: an EA-based framework for socially aware data partitioning. Comput. Netw. 75, 504–518 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Zhou, J., Fan, J., Cheng, B., Jia, J. (2016). Optimizing Inter-server Communications by Exploiting Overlapping Communities in Online Social Networks. In: Carretero, J., Garcia-Blas, J., Ko, R., Mueller, P., Nakano, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10048. Springer, Cham. https://doi.org/10.1007/978-3-319-49583-5_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-49583-5_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-49582-8
Online ISBN: 978-3-319-49583-5
eBook Packages: Computer ScienceComputer Science (R0)