Packet transport on scale free networks

We introduce a model of information packet transport on networks in which the packets are posted by a given rate and move in parallel according to a local search algorithm. By performing a number of simulations we investigate the major kinetic properties of the transport as a function of the network geometry, the packet input rate and the buffer size. We find long-range correlations in the power spectra of arriving packet density and the network's activity bursts. The packet transit time distribution shows a power-law dependence with average transit time increasing with network size. This implies dynamic queueing on the network, in which many interacting queues are mutually driven by temporally correlated packet stream

Preferential Behaviour and Scaling in Diffusive Dynamics on Networks

We study the fluctuation properties and return-time statistics on inhomogeneous scale-free networks using packets moving with two different dynamical rules; random diffusion and locally navigated diffusive motion with preferred edges. Scaling in the fluctuations occurs when the dispersion of a quantity at each node or edge increases like the its mean to the power $\mu$. We show that the occurrence of scaling in the fluctuations of both the number of packets passing nodes and the number flowing along edges is related to preferential behaviour in either the topology (in the case of nodes) or in the dynamics (in case the of edges). Within our model the absence of any preference leads to the absence of scaling, and when scaling occurs it is non-universal; for random diffusion the number of packets passing a node scales with an exponent $\mu$ which increases continuously with increased acquisition time window from $\mu =1/2$ at small windows, to $\mu =1$ at long time windows; In the preferentially navigated diffusive motion, busy nodes and edges have exponent $\mu =1$, in contrast to less busy parts of the network, where an exponent $\mu =1/2$ is found. Broad distributions of the return times at nodes and edges illustrate that the basis of the observed scaling is the cooperative behaviour between groups of nodes or edges. These conclusions are relevant for a large class of diffusive dynamics on networks, including packet transport with local navigation rules

Growing trees in Internet news groups and forums

We present an empirical study of the networks created by users within internet news groups and forums and show that they organ- ise themselves into scale-free trees. The structure of these trees depends on the topic under discussion; specialist topics have trees with a short shallow structure whereas more universal topics are discussed widely and have a deeper tree structure. For news groups we find that the distribu- tion of the time intervals between when a message is posted and when it receives a response exhibits a composite power-law behaviour. From our statistics we can see if the news group or forum is free or is overseen by a moderator. The correlation function of activity, the number of messages posted in a given time, shows long range correlations connected with the users’ daily routines. The distribution of distances between each message and its root is exponential for most news groups and power-law for the fo- rums. For both formats we find that the relation between the supremacy ( the total number of nodes that are under the node i, including node i) and the degree is linear s(k) k, in contrast to the analytical relation for Barab´asi-Albert network

Combinatorial Bounds and Characterizations of Splitting Authentication Codes

We present several generalizations of results for splitting authentication codes by studying the aspect of multi-fold security. As the two primary results, we prove a combinatorial lower bound on the number of encoding rules and a combinatorial characterization of optimal splitting authentication codes that are multi-fold secure against spoofing attacks. The characterization is based on a new type of combinatorial designs, which we introduce and for which basic necessary conditions are given regarding their existence.Comment: 13 pages; to appear in "Cryptography and Communications

PERSIANN-MSA: A precipitation estimation method from satellite-based multispectral analysis

Visible and infrared data obtained from instruments onboard geostationary satellites have been extensively used for monitoring clouds and their evolution. The Advanced Baseline Imager (ABI) that will be launched onboard the Geostationary Operational Environmental Satellite-R (GOES-R) series in the near future will offer a larger range of spectral bands; hence, it will provide observations of cloud and rain systems at even finer spatial, temporal, and spectral resolutions than are possible with the current GOES. In this paper, a new method called Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks-Multispectral Analysis (PERSIANN-MSA) is proposed to evaluate the effect of using multispectral imagery on precipitation estimation. The proposed approach uses a self-organizing feature map (SOFM) to classify multidimensional input information, extracted from each grid box and corresponding textural features of multispectral bands. In addition, principal component analysis (PCA) is used to reduce the dimensionality to a few independent input features while preserving most of the variations of all input information. The above method is applied to estimate rainfall using multiple channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. In comparison to the use of a single thermal infrared channel, the analysis shows that using multispectral data has the potential to improve rain detection and estimation skills with an average of more than 50% gain in equitable threat score for rain/no-rain detection, and more than 20% gain in correlation coefficient associated with rain-rate estimation. © 2009 American Meteorological Society

Real-time monitoring of proton exchange membrane fuel cell stack failure

Uneven pressure drops in a 75-cell 9.5-kWe proton exchange membrane fuel cell stack with a U-shaped flow configuration have been shown to cause localised flooding. Condensed water then leads to localised cell heating, resulting in reduced membrane durability. Upon purging of the anode manifold, the resulting mechanical strain on the membrane can lead to the formation of a pin-hole/membrane crack and a rapid decrease in open circuit voltage due to gas crossover. This failure has the potential to cascade to neighbouring cells due to the bipolar plate coupling and the current density heterogeneities arising from the pin-hole/membrane crack. Reintroduction of hydrogen after failure results in cell voltage loss propagating from the pin-hole/membrane crack location due to reactant crossover from the anode to the cathode, given that the anode pressure is higher than the cathode pressure. Through these observations, it is recommended that purging is avoided when the onset of flooding is observed to prevent irreparable damage to the stack