Total order in opportunistic networks

Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.Peer ReviewedPostprint (author's final draft

On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks

We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity. We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals. We simulate a message spreading process over the recorded proximity network, focusing on both the topological and the temporal properties. We show that by using an appropriate technique to deal with the temporal heterogeneity of proximity events, a universal statistical pattern emerges for the delivery times of messages, robust across all the data sets. Our results are useful to set constraints for generic processes of data dissemination, as well as to validate established models of human mobility and proximity that are frequently used to simulate realistic behaviors.Comment: A. Panisson et al., On the dynamics of human proximity for data diffusion in ad-hoc networks, Ad Hoc Netw. (2011

"Hierarchical routing in sensor networks using κ-dominating sets "

Michael Q. Rieck is an associate professor at Drake University in Des Moines, Iowa, USA. He holds a Ph. D. in mathematics from the University of South Florida. His primary research interests are in the areas of camera tracking and ad hoc wireless networks. He has also published results in the areas of triangle geometry, discrete mathematics, linear algebra, finite fields and association schemes.For a connected graph, representing a sensor network, distributed algorithms for the Set Covering Problem can be employed to construct reasonably small subsets of the nodes, called k-SPR sets. Such a set can serve as a virtual backbone to facilitate shortest path routing, as introduced in [4] and [14]. When employed in a hierarchical fashion, together with a hybrid (partly proactive, partly reactive) strategy, the κ-SPR set methods become highly scalable, resulting in guaranteed minimal path routing, with comparatively little overhead. © Springer-Verlag Berlin Heidelberg 2005