The Community for Technology Leaders
RSS Icon
Issue No.03 - March (2013 vol.24)
pp: 601-613
Eva Jaho , National and Kapodistrian University of Athens, Athens
Merkourios Karaliopoulos , National and Kapodistrian University of Athens, Athens
Ioannis Stavrakakis , National and Kapodistrian University of Athens, Athens
This paper explores how the degree of similarity within a social group can dictate the behavior of the individual nodes, so as to best tradeoff the individual with the social benefit. More specifically, we investigate the impact of social similarity on the effectiveness of content placement and dissemination. We consider three schemes that represent well the spectrum of behavior-shaped content storage strategies: the selfish, the self-aware cooperative, and the optimally altruistic ones. Our study shows that when the social group is tight (high degree of similarity), the optimally altruistic behavior yields the best performance for both the entire group (by definition) and the individual nodes (contrary to typical expectations). When the group is made up of members with almost no similarity, altruism or cooperation cannot bring much benefit to either the group or the individuals and thus, selfish behavior emerges as the preferable choice due to its simplicity. Notably, from a theoretical point of view, our “similarity favors cooperation” argument is inline with sociological interpretations of human altruistic behavior. On a more practical note, the self-aware cooperative behavior could be adopted as an easy to implement distributed alternative to the optimally altruistic one; it has close to the optimal performance for tight social groups and the additional advantage of not allowing mistreatment of any node, i.e., its induced content retrieval cost is always smaller than the cost of the selfish strategy.
Measurement, Games, Aggregates, Shape, Humans, Social network services, Computational complexity, social groups, Content replication, cooperation, similarity
Eva Jaho, Merkourios Karaliopoulos, Ioannis Stavrakakis, "Social Similarity Favors Cooperation: The Distributed Content Replication Case", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 3, pp. 601-613, March 2013, doi:10.1109/TPDS.2012.166
[1] T. Antala, H. Ohtsuki, J. Wakeley, P.D. Taylor, and M.A. Nowak, "Evolution of Cooperation by Phenotypic Similarity," Proc. Nat'l Academy of Sciences, vol. 106, no. 21, pp. 8597-8600, May 2009.
[2] T. Basar and G. Olsder, Dynamic Noncooperative Game Theory, second ed. Soc. for Industrial and Applied Math., 1999.
[3] C. Boldrini, M. Conti, and A. Passarella, "Design and Performance Evaluation of ContentPlace, a Social-Aware Data Dissemination System for Opportunistic Networks," Computer Networks, vol. 54, no. 4, pp. 589-604, Mar. 2010.
[4] S. Borst, V. Gupta, and A. Walid, "Distributed Caching Algorithms for Content Distribution Networks," Proc. ACM INFOCOM, pp. 1478-1486, 2010.
[5] I. Carreras, D. Tacconi, and A. Bassoli, "Social Opportunistic Computing: Design for Autonomic User-Centric Systems," Autonomic Communication, pp. 211-229, Springer, 2009.
[6] M. Cha, H. Haddadi, F. Benevenuto, and K.P. Gummadi, "Measuring User Influence in Twitter: The Million Follower Fallacy," Proc. Fourth Int'l AAAI Conf. Weblogs and Social Media (ICWSM), 2010.
[7] W. Chu, "Optimal File Allocation in a Multiple Computer System," IEEE Trans. Computers, vol. C-18, no. 10, pp. 885-889, Oct. 1969.
[8] L. Cosmides and J. Tooby, "Neurocognitive Adaptations Designed for Social Exchange," Handbook of Evolutionary Psychology, D.M. Buss, ed., pp. 584-627, Wiley, 2005.
[9] O. Curry and R.I. Dunbar, "Why Birds of a Feather Flock Together: The Effects of Similarity on Altruism," to be published,
[10] M. Denuit and S. Van Bellegem, "On the Stop-Loss and Total Variation Distances between Random Sums," Statistics and Probability Letters, vol. 53, no. 2, pp. 153-165, June 2001.
[11] Y. Gil and V. Ratnakar, "Trusting Information Sources one Citizen at a Time," Proc. First Int'l Semantic Web Conf. The Semantic Web, pp. 162-176, 2002.
[12] M. Hefeeda and O. Saleh, "Traffic Modeling and Proportional Partial Caching for Peer-to-Peer Systems," IEEE/ACM Trans. Networking, vol. 16, no. 6, pp. 1447-1460, Dec. 2008.
[13] E. Jaho, M. Karaliopoulos, and I. Stavrakakis, "ISCoDe: A Framework for Interest Similarity-Based Community Detection in Social Networks," Proc. Third Int'l Workshop Network Science for Comm. Networks, 2011.
[14] E. Jaho, M. Karaliopoulos, and I. Stavrakakis, "Supplemental Material for Social Similarity Favors Cooperation: The Distributed Content Placement Case," 2012.
[15] E. Jaho and I. Stavrakakis, "Joint Interest- and Locality-Aware Content Dissemination in Social Networks," Proc. Sixth Int'l Conf. Wireless On-Demand Network Systems and Services, pp. 161-168, 2009.
[16] E. Koutsoupias and C.H. Papadimitriou, "Worst-Case Equilibria," Computer Science Rev., vol. 3, no. 2, pp. 65-69, 2009.
[17] S. Kullback, Information Theory and Statistics. Wiley, 1959.
[18] K.-W. Kwong, A. Chaintreau, and R. Guerin, "Quantifying Content Consistency Improvements through Opportunistic Contacts," Proc. Fourth ACM Workshop Challenged Networks, pp. 43-50, Sept. 2009.
[19] N. Laoutaris, O. Telelis, V. Zissimopoulos, and I. Stavrakakis, "Distributed Selfish Replication," IEEE Trans. Parallel Distributed Systems, vol. 17, no. 12, pp. 1401-1413, Dec. 2006.
[20] A. Leff, J. Wolff, and P. Yu, "Replication Algorithms in a Remote Caching Architecture," IEEE Trans. Parallel Distributed Systems, vol. 4, no. 11, pp. 1185-1204, Nov. 1993.
[21] T. Loukopoulos, I. Ahmad, and D. Papadias, "An Overview of Data Replication on the Internet," Proc. Int'l Symp. Parallel Architectures, Algorithms and Networks, pp. 31-36, 2002.
[22] D. Luenberger and Ye, Linear and Nonlinear Programming, third ed. Springer, 2008.
[23] R.D. Mori, Spoken Dialogues with Computers. Academic Press, 1997.
[24] J.L. Myers and A.D. Well, Research Design and Statistical Analysis, second ed., Nov. 2003.
[25] V. Pacifici and G. Dãn, "Selfish Content Replication on Graphs," Proc. 23rd Int'l Teletraffic Congress (ITC '11), pp. 119-126, 2011.
[26] A.A. Rahman and S. Hailes, "A Distributed Trust Model," Proc. Workshop New Security Paradigms, pp. 48-60, 1997.
[27] J.P. Scott, Social Network Analysis: A Handbook, Jan. 2000.
[28] A. Shikfa, M. Onen, and R. Molva, "Privacy in Content-based Opportunistic Networks," Proc. Int'l Conf. Advanced Information Networking and Applications Workshops, pp. 832-837, 2009.
[29] R.L. Trivers, "The Evolution of Reciprocal Altruism," The Quarterly Rev. of Biology, vol. 46, no. 1, pp. 35-57, 1971.
[30] J. Vegelius, S. Janson, and F. Johansson, "Measures of Similarity between Distributions," Quality and Quantity, vol. 20, no. 4, pp. 437-441, 1986.
[31] J. Wang, W.W. Tsang, and G. Marsaglia, "Evaluating Kolmogorov's Distribution," J. Statistical Software, vol. 8, no. 18, pp. 1-4, Nov. 2003.
[32] O. Wolfson and S. Jajodia, "Distributed Algorithms for Dynamic Replication of Data," Proc. 11th ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems, pp. 149-163, 1992.
39 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool