Cooperative content replication in networks with autonomous nodes
Computer Communications
An Interests Discovery Approach in Social Networks Based on Semantically Enriched Graphs
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
| Hi-index | 0.00 |
This paper explores how the degree of similarity within a social group can be exploited in order to dictate the behavior of the individual nodes, so as to best accommodate the typically non-coinciding individual and social benefit maximization. More specifically, this paper investigates the impact of social similarity on the effectiveness of content dissemination, as implemented through three classes representing well the spectrum of behavior-shaped content storage strategies: the selfish, the self-aware cooperative and the optimally altruistic ones. This 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 foreigners with almost no similarity, altruism or cooperation cannot bring much benefits to either the group or the individuals and thus, a selfish behavior would make sense due to its simplicity. Finally, the self-aware cooperative behavior could be adopted as an easy to implement distributed scheme — compared to the optimally altruistic one — that has close to the optimal performance for tight social groups, and has the additional advantage of not allowing mistreatment to any node (i.e., the content retrieval cost become larger compared to the cost of the selfish strategy).