Abstract
With the increasing popularity and rapid development of Online Social Networks (OSNs), OSNs not only bring fundamental changes to information and communication technologies, but also make an extensive and profound impact on all aspects of our social life. Efficient content discovery is a fundamental challenge for large-scale distributed OSNs. However, the similarity between social networks and online social networks leads us to believe that the existing social theories are useful for improving the performance of social content discovery in online social networks. In this article, we propose an interest-aware social-like peer-to-peer (IASLP) model for social content discovery in OSNs by mimicking ten different social theories and strategies. In the IASLP network, network nodes with similar interests can meet, help each other, and co-operate autonomously to identify useful contents. The presented model has been evaluated and simulated in a dynamic environment with an evolving network. The experimental results show that the recall of IASLP is 20% higher than the existing method SESD while the overhead is 10% lower. The IASLP can generate higher flexibility and adaptability and achieve better performance than the existing methods.
- Albert-László Barabási and Réka Albert. 1999. Emergence of scaling in random networks. Science, 286, 509--512.Google Scholar
Cross Ref
- Paolo Bellavista, Carlo Giannelli, Luca Iannario, Laurent-Walter Giox, and Claudio Venezia. 2014. Peer-to-peer content sharing based on social identities and relationships. IEEE Internet Comput. 18, 55--63.Google Scholar
Cross Ref
- Ranjita Bhagwan, Stefan Savage, and Geoffrey M. Voelker. 2003. Understanding Availability. Lecture Notes in Computer Science 2735, 256--267.Google Scholar
Cross Ref
- Shihabur Rahman Chowdhury, Arup Raton Roy, Maheen Shaikh, and Khuzaima Daudjee. 2014. A taxonomy of decentralized online social networks. Peer-to-Peer Netw. Appl. 8, 367--383.Google Scholar
Cross Ref
- Nelson Cowan, Lara D. Nugent, Emily M. Elliott, Igor Ponomarev, and J. Scott Saults. 1999. The role of attention in the development of short-term memory: Age differences in the verbal span of apprehension. Child Development, 70, 1082--1097.Google Scholar
Cross Ref
- Arturo Crespo and Hector Garcia-Molina. 2002. Routing indices for peer-to-peer systems. In Proceedings of the 22nd International Conference on Distributed Systems. 23--32. Google Scholar
Digital Library
- K. M. Fisher and Joseph I. Lipson. 1985. Information processing interpretation of errors in college science learning. Instructional Science, 14, 49--74.Google Scholar
Cross Ref
- Barbara Guidi, Marco Conti, and Laura Ricci. 2013. P2P architectures for distributed online social networks. In Proceedings of the 2013 International Conference on High Performance Computing and Simulation (HPCS’13), 678--681.Google Scholar
Cross Ref
- Barbara Guidi, Tobias Amft, Andrea De Salve, Kalman Graffi, and Laura Ricci. 2016. DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks. Peer-to-Peer Netw. Appl. 9, 1177--1194.Google Scholar
Cross Ref
- Krishna P. Gummadi, Richard J. Dunn, Stefan Saroiu, Steven D. Gribble, Henry M. Levy, and John Zahorjan. 2003. Measurement, modeling and analysis of a peer-to-peer file-sharing workload. ACM SIGOPS Oper. Syst. Rev., 37, 5, 314--329. Google Scholar
Digital Library
- Xiao Han, Angel Cuevas, Noel Crespi, Ruben Cuevas, and Xiaodi Huang. 2014. On exploiting social relationship and personal background for content discovery in P2P networks. Future Generation Computer Systems, 40, 17--29. Google Scholar
Digital Library
- Chih-Lin Hu, Yi-Hsun Chang, and Kuo-Fu Huang. 2014. Searching with feature similarity in unstructured peer-to-peer networks. In Proceedings of the 7th International Conference on Ubi-Media Computing and Workshops (U-MEDIA’14). 65--71. Google Scholar
Digital Library
- Sam Joseph. 2002. NeuroGrid: Semantically routing queries in peer-to-peer networks. In Proceedings of the International Workshop on Web Engineering and International Workshop on Peer-to-Peer Computing (NETWORKING’02). 202--214. Google Scholar
Digital Library
- Vana Kalogeraki, Dimitrios Gunopulos, and D. Zeinalipour-Yazti. 2002. A local search mechanism for peer-to-peer networks. In Proceedings of the 11th International Conference on Information and Knowledge Management (CIKM’02). 300--307. Google Scholar
Digital Library
- Jon M. Kleinberg. 2000. Navigation in a small world. Nature, 406, 845--845.Google Scholar
- Nicolas Kourtellis, Jeremy Blackburn, Cristian Borcea, and Adriana Iamnitchi. 2015. Special issue on foundations of social computing: Enabling social applications via decentralized social data management. ACM Trans. Internet Technol. 15, 1--26. Google Scholar
Digital Library
- Jan-Erik Lönnqvist and Juha V. A. Itkonen. 2016. Homogeneity of personal values and personality traits in Facebook social networks. J. Res. Personality, 60, 24--35.Google Scholar
Cross Ref
- Andrea Lancichinetti, Santo Fortunato, and Janos Kertész. 2009. Detecting the overlapping and hierarchical community structure in complex networks. New J. Phys. 11, 033015.Google Scholar
Cross Ref
- Hao Liao, Kuo-Chan Huang, and Hung-Chang Hsiao. 2010. Small-world social relationship awareness in unstructured peer-to-peer networks. In Proceedings of the 16th IEEE International Conference on Parallel and Distributed Systems (ICPADS’10). 770--775. Google Scholar
Digital Library
- Fengkun Liu and Hong Joo Lee. 2010. Use of social network information to enhance collaborative filtering performance. Expert Syst. with Applications, 37, 4772--4778. Google Scholar
Digital Library
- Lu Liu, Nick Antonopoulos, Stephen Mackin, Jie Xu, and Duncan Russell. 2009. Efficient resource discovery in self-organized unstructured peer-to-peer networks. Concurrency Computation Practice and Experience, 21, 159--183. Google Scholar
Digital Library
- Lu Liu, Nick Antonopoulos, Minghui Zheng, Yongzhao Zhan, and Zhijun Ding. 2016. A socioecological model for advanced service discovery in machine-to-machine communication networks. ACM Transt. Embed.Comput. Syst. 15, 2, 38, 2016. Google Scholar
Digital Library
- Virginia Lo, Dayi Zhou, Yuhong Liu, Chris Gauthier Dickey, and Jun Li. 2005. Scalable supernode selection in peer-to-peer overlay networks. In Proceedings of the 2nd International Workshop on Hot Topics in Peer-to-Peer Systems (HOT-P2P’05). 18--27. Google Scholar
Digital Library
- Dionisis Margaris, Costas Vassilakis, and Panagiotis Georgiadis. 2017. Query personalization using social network information and collaborative filtering techniques. Future Generation Computer Systems 78, 440--450.Google Scholar
Cross Ref
- Christopher McCarty. 2002. Structure in personal networks. J. Social Structure, 3, 20.Google Scholar
- Theodore M. Newcomb. 1975. Social Psychology: The Study of Human Interaction (2nd ed.). Revised Routledge and Kegan Paul, London.Google Scholar
- M. E. J. Newman. 2002. Assortative mixing in networks. Phys. Rev. Lett., 89, 208701.Google Scholar
Cross Ref
- M. E. J. Newman. 2004. Fast algorithm for detecting community structure in networks. Phys. Rev. E, 69, 066133.Google Scholar
Cross Ref
- Thomas Paul, Antonino Famulari, and Thorsten Strufe. 2014. A survey on decentralized online social networks. Comput. Netw., 75, Part A, 437--452. Google Scholar
Digital Library
- Matei Ripeanu. 2001. Peer-to-peer architecture case study: Gnutella network. In Proceedings of the 1st International Conference on Peer-to-Peer Computing (P2P’01). 99--100. Google Scholar
Digital Library
- Ion Stoica, Robert Morris, David Karger, M. Frans Kaashoek, and Hari Balakrishnan. 2001. Chord: A scalable peer-to-peer lookup service for internet applications. In Proceedings of ACM SIGCOMM 2001 -- Applications, Technologies, Architectures, and Protocols for Computers Communications. 149--160. Google Scholar
Digital Library
- The Open Directory Project. 2016. Retrieved January 19, 2016 from http://www.dmoz.org/.Google Scholar
- Gerd Waloszek. 2002. Personal Networks. SAP AG, Product Design Center.Google Scholar
- Duncan J. Watts and Steven H. Strogatz. 1998. Collective dynamics of “small-world” networks. Nature, 393, 440--442.Google Scholar
Cross Ref
- Duncan J. Watts, Peter Sheridan Dodds, and M. E. J. Newman. 2002. Identity and search in social networks. Science, 296, 1302--1305.Google Scholar
Cross Ref
- Barry Wellman. 1997. An electronic group is virtually a social network. Culture of the Internet, 4, 179--205.Google Scholar
- Wikipedia. 2013. Olfactory fatigue. Retrieved from https://en.wikipedia.org/wiki/Olfactory_fatigue.Google Scholar
- Bo Yuan, Lu Liu, and Nick Antonopoulos. 2016. Efficient service discovery in decentralized online social networks. In Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, ACM, 73--78. Google Scholar
Digital Library
Index Terms
Interest-Aware Content Discovery in Peer-to-Peer Social Networks
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