Epcast: Controlled Dissemination in Human-Based Wireless Networks Using Epidemic Spreading Models Export

@incollection{scellato:epcast, abstract = {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.}, author = {Scellato, Salvatore and Mascolo, Cecilia and Musolesi, Mirco and Latora, Vito}, citeulike-article-id = {5248728}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-92191-2_26}, citeulike-linkout-1 = {http://www.springerlink.com/content/g4k3j1t56050m75r}, doi = {10.1007/978-3-540-92191-2_26}, journal = {Bio-Inspired Computing and Communication}, keywords = {crawdad, dartmouth\_campus, dtn, epidemic, information-dissemination, mobile, nus\_contact, routing}, pages = {295--306}, posted-at = {2009-07-24 09:16:06}, priority = {2}, title = {Epcast: Controlled Dissemination in Human-Based Wireless Networks Using Epidemic Spreading Models}, url = {http://dx.doi.org/10.1007/978-3-540-92191-2_26}, year = {2008} }

TY - CHAP ID - scellato:epcast L3 - citeulike-article-id:5248728 N2 - 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. JF - Bio-Inspired Computing and Communication EP - 306 TI - Epcast: Controlled Dissemination in Human-Based Wireless Networks Using Epidemic Spreading Models SP - 295 KW - crawdad KW - dartmouth_campus KW - dtn KW - epidemic KW - information-dissemination KW - mobile KW - nus_contact KW - routing AU - Scellato, Salvatore AU - Mascolo, Cecilia AU - Musolesi, Mirco AU - Latora, Vito PY - 2008/// UR - http://dx.doi.org/10.1007/978-3-540-92191-2_26 ER -