Epidemic algorithms for replicated database maintenance
ACM SIGOPS Operating Systems Review
A delay-tolerant network architecture for challenged internets
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Lightweight probabilistic broadcast
ACM Transactions on Computer Systems (TOCS)
Epidemic-Style Proactive Aggregation in Large Overlay Networks
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Semi-Probabilistic Content-Based Publish-Subscribe
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Frugal event dissemination in a mobile environment
Proceedings of the ACM/IFIP/USENIX 2005 International Conference on Middleware
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Epidemics-inspired techniques have received huge attention in recent years from the distributed systems and networking communities. These algorithms and protocols rely on probabilistic message replication and redundancy to ensure reliable communication. Moreover, they have been successfully exploited to support group communication in distributed systems, broadcasting, multicasting and information dissemination in fixed and mobile networks. However, in most of the existing work, the probability of infection is determined heuristically, without relying on any analytical model. This often leads to unnecessarily high transmission overheads. In this paper we show that models of epidemic spreading in complex networks can be applied to the problem of tuning and controlling the dissemination of information in wireless ad hoc networks composed of devices carried by individuals, i.e., human-based networks. The novelty of our idea resides in the evaluation and exploitation of the structure of the underlying human network for the automatic tuning of the dissemination process in order to improve the protocol performance. We evaluate the results using synthetic mobility models and real human contacts traces.