Abstract
Online social networks have reshaped how multimedia contents are generated, distributed, and consumed on today's Internet. Given the massive number of user-generated contents shared in online social networks, users are moving to directly access these contents in their preferred social network services. It is intriguing to study the service provision of social contents for global users with satisfactory quality of experience. In this article, we conduct large-scale measurement of a real-world online social network system to study the social content propagation. We have observed important propagation patterns, including social locality, geographical locality, and temporal locality. Motivated by the measurement insights, we propose a propagation-based social-aware delivery framework using a hybrid edge-cloud and peer-assisted architecture. We also design replication strategies for the architecture based on three propagation predictors designed by jointly considering user, content, and context information. In particular, we design a propagation region predictor and a global audience predictor to guide how the edge-cloud servers backup the contents, and a local audience predictor to guide how peers cache the contents for their friends. Our trace-driven experiments further demonstrate the effectiveness and superiority of our design.
- Adhikari, V., Jain, S., Chen, Y., and Zhang, Z. 2011. Reverse engineering the YouTube video delivery cloud. In Proceedings of the IEEE Hot Topics in Media Delivery Workshop.Google Scholar
- Adhikari, V., Jain, S., and Zhang, Z. 2011. Where do you tube? Uncovering YouTube server selection strategy. In Proceedings of the IEEE International Conference on Computer Communications and Networks (ICCCN).Google Scholar
- Benevenuto, F., Rodrigues, T., Cha, M., and Almeida, V. 2009. Characterizing user behavior in online social networks. In Proceedings of the Internet Measurement Conference ACM (IMC). Google Scholar
Digital Library
- Cha, M., Mislove, A., and Gummadi, K. P. 2009. A measurement-driven analysis of information propagation in the Flickr social network. In Proceedings of the ACM WWW. Google Scholar
Digital Library
- Cheng, X., Dale, C., and Liu, J. 2008. Statistics and social network of, YouTube videos. In Proceedings of the IEEE Workshop on Quality of Service (WQoS).Google Scholar
- Cheng, X. and Liu, J. 2009. NetTube: Exploring social networks for peer-to-peer short video sharing. In Proceedings of the IEEE INFOCOM.Google Scholar
- Cheng, X. and Liu, J. 2011. Load-balanced migration of social media to content clouds. In Proceedings of the ACM NOSSDAV. Google Scholar
Digital Library
- Dodds, P. and Watts, D. 2005. A generalized model of social and biological contagion. J. Theor. Biol. 232, 4, 587--604.Google Scholar
Cross Ref
- Domingos, P. and Richardson, M. 2001. Mining the network value of customers. In Proceedings of the ACM SIGKDD on Knowledge Discovery and Data Mining. Google Scholar
Digital Library
- Fehr, E. and Fischbacher, U. 2002. Why social preferences matter--The impact of non-selfish motives on competition, cooperation and incentives. Econ. J. 112, 478, C1--C33.Google Scholar
Cross Ref
- Foresee. 2012. http://www.foreseeresults.com.Google Scholar
- Hartline, J., Mirrokni, V., and Sundararajan, M. 2008. Optimal marketing strategies over social networks. In Proceedings of the ACM WWW. Google Scholar
Digital Library
- Huffaker, B., Fomenkov, M., Plummer, D., Moore, D., and Claffy, K. 2002. Distance metrics in the internet. In Proceedings of the IEEE International Telecommunications Symposium (ITS).Google Scholar
- Kangasharju, J., Roberts, J., and Ross, K. 2002. Object replication strategies in content distribution networks. Comput. Commun. 25, 4, 376--383. Google Scholar
Digital Library
- Kempe, D., Kleinberg, J., and Tardos, É. 2003. Maximizing the spread of influence through a social network. In Proceedings of the ACM SIGKDD. Google Scholar
Digital Library
- Krishnamurthy B., Gill P., and Arlitt, M. 2008. A few chirps About Twitter. In Proceedings of the ACM Workshop on Social Networks (WOSN). Google Scholar
Digital Library
- Kwak, H., Lee, C., Park, H., and Moon, S. 2010. What is Twitter, a social network or a news media? In Proceedings of the ACM WWW. Google Scholar
Digital Library
- Li, H., Wang, H., and Liu, J. 2012. Video sharing in online social network: Measurement and analysis. In Proceedings of the ACM NOSSDAV. Google Scholar
Digital Library
- Liu, Y., Guo, Y., and Liang, C. 2008. A survey on peer-to-peer video streaming systems. Peer-to-peer Netw. Appl. 1, 1, 18--28.Google Scholar
Cross Ref
- Luo, J., Zhang, Q., Tang, Y., and Yang, S. 2009. A trace-driven approach to evaluate the scalability of P2P-based video-on-demand service. IEEE Trans. Parallel Distrib. Syst. 20, 1, 59--70. Google Scholar
Digital Library
- Melville, P., Mooney, R., and Nagarajan, R. 2002. Content-boosted collaborative filtering for improved recommendations. In Proceedings of the National Conference on Artificial Intelligence. Google Scholar
Digital Library
- Mislove, A. 2012. Rethinking Web content distribution in the social media era. In Proceedings of the NSF Workshop on Social Networks and Mobility in the Cloud.Google Scholar
- Mislove, A., Marcon, M., Gummadi, K., Druschel, P., and Bhattacharjee, B. 2007. Measurement and analysis of online social networks. In Proceedings of the ACM Internet Measurement Conference (IMC). Google Scholar
Digital Library
- Mislove, A., Viswanath, B., Gummadi, K., and Druschel, P. 2010. You are who you know: Inferring user profiles in online social networks. In Proceedings of the ACM WSDM Conference. Google Scholar
Digital Library
- Nguyen, K., Pham, C., Tran, D., and Zhang, F. 2011. Preserving social locality in data replication for social networks. In Proceedings of the IEEE ICDCS Workshop on Simplifying Complex Networks for Practitioners. Google Scholar
Digital Library
- Peng, G. 2004. CDN: Content distribution network. Arxiv preprint cs/0411069.Google Scholar
- Pujol, J. M., Erramilli, V., Siganos, G., Yang, X., Laoutaris, N., Chhabra, P., and Rodriguez, P. 2010. The little engine(s) that Could: Scaling online social networks. SIGCOMM Comput. Commun. Rev. 40, 375--386. Google Scholar
Digital Library
- Scellato, S., Mascolo, C., Musolesi, M., and Latora, V. 2010. Distance matters: Geo-social metrics for online social networks. In Proceedings of the Conference on Online Social Networks. USENIX Association. Google Scholar
Digital Library
- Tencent Weibo. 2013. http://t.qq.com.Google Scholar
- Tran, D. A., Nguyen, K., and Pham, C. 2012. S-CLONE: Socially-aware data replication for social Networks. Comput. Netw. 56, 7, 2001--2013. Google Scholar
Digital Library
- Wang, Z., Sun, L., Chen, X., Zhu, W., Liu, J., Chen, M., and Yang, S. 2012. Propagation-based social-aware replication for social video contents. In Proceedings of the ACM Multimedia. Google Scholar
Digital Library
- Wang, Z., Sun, L., Wu, C., and Yang, S. 2012. Guiding Internet-scale video service deployment using microblog-based prediction. In Proceedings of the IEEE INFOCOM Mini-Conference.Google Scholar
- Wiki. 2013. Clustering/Coefficient. http://en.wikipedia.org/wiki/.Google Scholar
- Wu, Y., Wu, C., Li, B., Zhang, L., Li, Z., and Lau, F. C. 2012. Scaling social media applications into geo-distributed clouds. In Proceedings of the IEEE INFOCOM.Google Scholar
- Xu, D., Kulkarni, S., Rosenberg, C., and Chai, H. 2006. Analysis of a CDN--P2P hybrid architecture for cost-effective streaming media distribution. Multimedia Syst. 11, 4, 383--399.Google Scholar
Digital Library
- YouTube. 2013. http://www.youtube.com/t/press_statistics.Google Scholar
- Zhu, W., Luo, C., Wang, J., and Li, S. 2011. Multimedia cloud computing. IEEE Signal Proces. Mag. 28, 3, 59--69.Google Scholar
Cross Ref
Index Terms
Propagation-based social-aware multimedia content distribution
Recommendations
Social media distribution: a data-driven approach
ICIMCS '15: Proceedings of the 7th International Conference on Internet Multimedia Computing and ServiceThe Internet has recently witnessed the convergence of online social network services and online video services: users import videos from content sharing sites, and propagate them along the social connections by re-sharing them. Such social behaviors ...
Propagation-based social-aware replication for social video contents
MM '12: Proceedings of the 20th ACM international conference on MultimediaOnline social network has reshaped the way how video contents are generated, distributed and consumed on today's Internet. Given the massive number of videos generated and shared in online social networks, it has been popular for users to directly ...
A Context-Aware Trust-Oriented Influencers Finding in Online Social Networks
ICWS '15: Proceedings of the 2015 IEEE International Conference on Web ServicesOnline Social Networks (OSNs) have been used as the means for a variety of applications, like employment system, e-Commerce and CRM system. In these applications, social influence acts as a significant role, affecting people's decision-making. However, ...






Comments