Abstract
Rapid growth in social networks (SNs) presents a unique scalability challenge for SN operators because of the massive amounts of data distribution among large number of concurrent online users. A request from any user may trigger hundreds of server activities to generate a customized page and which has already become a huge burden. Based on the theoretical model and analytical study considering realistic network scenarios, this article proposes a hybrid P2P-based architecture called PAIDD. PAIDD fulfills effective data distribution primarily through P2P connectivity and social graph among users but with the help of central servers. To increase system efficiency, PAIDD performs optimized content prefetching based on social interactions among users. PAIDD chooses interaction as the criteria because user’s interaction graph is measured to be much smaller than the social graph. Our experiments confirm that PAIDD ensures satisfactory user experience without incurring extensive overhead on clients’ network. More importantly, PAIDD can effectively achieve one order of magnitude of load reduction at central servers.
Similar content being viewed by others
References
de Turck F, Vanhastel S, Volckaert B, et al. A generic middleware-based platform for scalable cluster computing. Future Gener Comput Syst, 2002, 18: 549–560
Tang S J, Yuan J, Mao X F, et al. Relationship classification in large scale online social networks and its impact on information propagation. In: Proceedings of 30th IEEE International Conference on Computer Communications, Shanghai, 2011. 2291–2299
Aron M, Sanders D, Druschel P, et al. Scalable content-aware request distribution in cluster-based networks servers. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference, San Diego, 2000. 323–336
Kevin L, Marco G, Jason K. Social selection and peer influence in an online social network. Proc Nat Acad Sci USA, 2012, 109: 68–72
Marcel S, Duy Q V, Shashank K, et al. The dynamics of health behavior sentiments on a large online social network. EPJ Data Sci, 2013, 2: 4
Rhea S, Geels D, Roscoe T, et al. Handling churn in a DHT. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference, Boston, 2004. 127–140
Godfrey P, Shenker S, Stoica I. Minimizing churn in distributed systems. SIGCOMM Comput Commun Rev, 2006, 36: 147–158
Mondal M, Viswanath B, Clement A, et al. Limiting large-scale crawls of social networking sites. In: Proceedings of the ACM SIGCOMM 2011 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, Toronto, 2011. 398–399
Deng Y. RISC: a resilient interconnection network for scalable cluster storage systems. J Syst Architect, 2008, 54: 70–80
Buchegger S, Datta A. A case for P2P infrastructure for social networks: opportunities and challenges. In: Proceedings of 6th International Conference on Wireless On-demand Network Systems and Services, Snowbird, 2009. 161–168
Abbas S M A, Pouwelse J A, Epema D H J, et al. A gossip-based distributed social networking system. In: Proceedings of 18th IEEE International Workshops on Enableing Technologies: Infrastructures for Collaborative Enterprises, Groningen, 2009. 93–98
Wilson C, Boe B, Sala A, et al. User interactions in social networks and their implications. In: Proceedings of 4th ACM European Conference on Computer Systems, Nuremburg, 2009. 205–218
Benevenuto F, Rodrigues T, Cha M, et al. Characterizing user behavior in online social networks. In: Proceedings of 9th ACM SIGCOMM Conference on Internet Measurement, Chicago, 2009. 49–62
Ford B, Srisuresh P, Kegel D. Peer-to-peer communication across network address translators. In: USENIX Annual Technical Conference, Anaheim, 2005. 179–192
Saikat G, Paul F. Characterization and measurement of TCP traversal through NATs and firewalls. In: Proceedings of 5th ACM SIGCOMM Conference on Internet Measurement, New Orleans, 2005. 199–211
Ganjam A, Zhang H. Connectivity restrictions in overlay multicast. In: Proceedings of 14th International Workshop on Network and Operating Systems Support for Digital Audio and Video, Kinsale County Cork, 2004. 54–59
Shami K, Magoni D, Chang H, et al. Impacts of peer characteristics on P2P TV networks scalability. In: Proceedings of 28th IEEE International Conference on Computer Communications, Rio de Janeiro, 2009. 2736–2740
Jared W, Sugih J. Inet-3.0: Internet Topology Generator. Technical Report CSE-TR-456-02, EECS Department, University of Michigan. 2002
Hernandez J M, Kleiberg T, Wang H, et al. A Qualitative Comparison of Power Law Generators. Technical Report 20061115, Delft University of Technology. 2006
Schroeder S. 20 ways to aggregate your social networking profiles. Mashable, 2007. http://mashable.com/2007/07/17/social-network-aggregators/
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shuang, K., Su, S. PAIDD: a hybrid P2P-based architecture for improving data distribution in social networks. Sci. China Inf. Sci. 57, 1–11 (2014). https://doi.org/10.1007/s11432-014-5084-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11432-014-5084-x