Dynamic communicability predicts infectiousness

Using real, time-dependent social interaction data, we look at correlations between some recently proposed dynamic centrality measures and summaries from large-scale epidemic simulations. The evolving network arises from email exchanges. The centrality measures, which are relatively inexpensive to compute, assign rankings to individual nodes based on their ability to broadcast information over the dynamic topology. We compare these with node rankings based on infectiousness that arise when a full stochastic SI simulation is performed over the dynamic network. More precisely, we look at the proportion of the network that a node is able to infect over a fixed time period, and the length of time that it takes for a node to infect half the network.We find that the dynamic centrality measures are an excellent, and inexpensive, proxy for the full simulation-based measures

An adaptive directed query dissemination scheme for wireless sensor networks

This paper describes a directed query dissemination scheme, DirQ that routes queries to the appropriate source nodes based on both constant and dynamic-valued attributes such as sensor types and sensor values. Unlike certain other query dissemination schemes, location information is not essential for the operation of DirQ. DirQ uses only locally available information in order to route queries accurately. Nodes running DirQ are able to adapt autonomously to changes in network topology due to certain cross-layer features that allow it to exchange information with the underlying MAC protocol. DirQ allows nodes to autonomously control the rate of sending update messages in order to keep the routing information updated. The rate of sending updates is dependent on both the number of queries injected into the network and the rate of variation of the measured physical parameter. Our results show that DirQ spends between 45% and 55% the cost of flooding

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.)