Detecting dynamic communities in opportunistic networks

2009 1st International Conference on Ubiquitous and Future Networks, ICUFN 2009

Volumn , Issue , 2009, Pages 159-164

  Xu, Kuang ^a   Yang, Guang Hua ^a   Li, Victor O K ^a   Chan, Shu Yan ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Algorithm; Community detection; Message forwarding; Opportunistic network

Indexed keywords

COMMUNITY DETECTION; COMMUNITY DETECTION ALGORITHMS; HUMAN MOBILITY; MESSAGE FORWARDING; MOBILE ENTITIES; MOBILE ENVIRONMENTS; NON-TRIVIAL; OPPORTUNISTIC NETWORK; OPPORTUNISTIC NETWORKS; RANDOM WALK ON GRAPH; REAL-WORLD;

ALGORITHMS;

WIRELESS NETWORKS;

EID: 70449095763     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICUFN.2009.5174304     Document Type: Conference Paper

References (33)

1. L. Ana and A. Jain. Robust data clustering. Computer Vision and Pattern Recognition, 2:II-128-133, June 2003.
2. A. Arenas et al. Synchronization reveals topological scales in complex networks. Physical Review Letters, 96(11), March 2006.
3. L. Backstrom et al. Group formation in large social networks: membership, growth, and evolution. In Proc. of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 44-54. ACM, 2006.
4. T. Y. Berger-Wolf and J. Saia. A framework for analysis of dynamic social networks. In Proc. of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 523-528. ACM, 2006.
5. D. Chakrabarti, R. Kumar, and A. Tomkins. Evolutionary clustering. In Proc. of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 554-560. ACM, 2006.
6. A. K. Chandra et al. The electrical resistance of a graph captures its commute and cover times. Computational Complexity, 6(4):312-340, December 1996.
7. Y. Chi et al. Structural and temporal analysis of the blogosphere through community factorization. In Proc. of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 163-172. ACM, 2007.
8. A. Clauset. Finding local community structure in networks. Physical Review E, 72:026132, 2005.
9. E. Daly and M. Haahr. Social network analysis for routing in disconnected delay-tolerant manets. In The ACM International Symposium on Mobile Ad Hoc Networking and Computing, Montréal, QC, Canada, 2007. ACM.
10. L. Danon et al. Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, September 2005.
11. N. Eagle and A. Pentland. Reality mining: sensing complex social systems. Personal and Ubiquitous Computing, 10(4):255-268, May 2006.
12. G. Flake, S. Lawrence, C. Giles, and F. Coetzee. Self-organization and identification of web communities. IEEE Computer, 35(3):66-70, Mar 2002.
13. M. S. Granovetter. The strength of weak ties. The American Journal of Sociology, 78(6):1360-1380, 1973.
14. P. Hui, J. Crowcroft, and E. Yoneki. Bubble rap: social-based forwarding in delay tolerant networks. In The ACM International Symposium on Mobile Ad Hoc Networking and Computing, Hong Kong, China, 2008. ACM.
15. P. Hui, E. Yoneki, S.-Y. Chan, and J. Crowcroft. Distributed community detection in delay tolerant networks. In The ACM International Workshop on Mobility in the Evolving Internet Architecture, Kyoto, Japan, 2007.
16. A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: a review. ACM Computing Surveys, 31(3):264-323, 1999.
17. S. Jain, K. Fall, and R. Patra. Routing in a delay tolerant network. In Proc. of the 2004 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), pages 145-158. ACM, 2004.
18. D. J. Klein. Graph geometry, graph metrics and wiener. MATCH: Communications in Mathematical and in Computer Chemistry, 35:7-27, 1997.
19. G. Kossinets and D. J. Watts. Empirical analysis of an evolving social network. Science, 311:88-90, January 2006.
20. L. Lovász. Random walks on graphs: a survey. Combinatorics: Paul Erdocombining double acute accents is Eighty, 2:1-46, 1993.
21. R. Merris. Laplacian matrices of graphs: a survey. Linear Algebra and its Applications, 197-198:143-176, 1994.
22. M. E. J. Newman. Detecting community structure in networks. The European Physical Journal B, 38(2):321-330, March 2004.
23. M. E. J. Newman. Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74:036104, 2006.
24. M. E. J. Newman. Modularity and community structure in networks. Proceedings of the National Academy of Sciences (USA), 103:8577, 2006.
25. M. E. J. Newman and M. Girvan. Finding and evaluating community structure in networks. Physical Review E, 69, February 2004.
26. G. Palla et al. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043):814-818, 2005.
27. A. Scherrer, P. Borgnat, E. Fleury, J.-L. Guillaume, and C. Robardet. Description and simulation of dynamic mobility networks. Comput. Netw., 52(15):2842-2858, 2008.
28. W.-K. Sung. Phylogenetic tree reconstruction: distance based. http://www.comp.nus.edu.sg/ bioinfo/, 2003, lecture notes.
29. C. Tantipathananandh, T. Berger-Wolf, and D. Kempe. A framework for community identification in dynamic social networks. In Proc. of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 717-726. ACM, 2007.
30. P. Uetz et al. A comprehensive analysis of proteincprotein interactions in saccharomyces cerevisiae. Nature, 403:623-627, February 2000.
31. F. Vega-Redondo. Complex social networks. Econometric Society Monographs. Cambridge University Press, January 2007.
32. W. J. Xiao and I. Gutman. Resistance distance and laplacian spectrum. Theoretical Chemistry Accounts: Theory, Computation, and Modeling, 110:284-289, 2003.
33. K. Xu, P. Hui, V. O.-K. Li, J. Crowcroft, V. Latora, and P. Lio. Impact of altruism on opportunistic communications. In The First International Conference on Ubiquitous and Future Networks, Hong Kong, China, June 2009. IEEE.