6464793
Ringed Petersen spheres connected hypercube interconnection networks
On the basis of the short diameter of Petersen graph, and high connectivity of hypercube, a novel interconnection networks, RPSCH(n) (ringed Petersen spheres connected hypercube) is proposed, and whose characteristics are studied simultaneously. It is proved that RPSCH(n) is not only of regularity and good extensibility, but also of shorter diameter and better connectivity than those previous well-known interconnection networks such as Q/sub n/, RP(n) and HP(n). In addition, the unicasting and broadcasting routing algorithms are designed for RPSCH(n), whose communication efficiency are proved to be n-2 and n-2 respectively.
16518214
Key Distribution for Group-based Sensor Deployment Using a Novel Interconnection Graph
In this paper, we propose a pairwise key distribution scheme based on a novel interconnection graph termed Hierarchical Hypercube. Motivated by the fact that sensor nodes are often deployed in groups (for example, dropped from an airplane at different locations) and hence the whole network is composed of multiple such groups, we design Hierarchical Hypercube as a two layer topology, where each group is modeled by an inner hypercube and connections between the groups are modeled using an outer hypercube. we propose a topology termed Hierarchy Hypercube. While retaining the desirable properties already shown by existing pairwise schemes, by using Hierarchical Hypercube, direct communication from a node to any other nodes is not required, either within a group or among groups, and hence this topology can effectively and realistically reflect the connectivity of the physical sensor network deployed in groups. Furthermore, we propose key pre-distribution scheme based on this novel topology and show that the new scheme possesses high probability of direct key establishment, low memory overhead, and resilience in the presence of broken communication links and compromised nodes, and thus still retain the desirable properties even when the ideal logical connection are distorted in the real deployment.
1135112
Measurement and Statistics of Application Business in Complex Internet
Owing to independent topologies and autonomic routing mechanism, the logical networks formed by Internet application business behavior cause the significant influence on the physical networks. In this paper, the backbone traffic of TUNET (Tsinghua University Networks) is measured, further more, the two most important application business: HTTP and P2P are analyzed at IP-packet level. It is shown that uplink HTTP and P2P packets behavior presents spatio-temporal power-law characteristics with exponents 1.25 and 1.53 respectively. Downlink HTTP packets behavior also presents power-law characteristics, but has more little exponents γ = 0.82 which differs from traditional complex networks research result. Moreover, downlink P2P packets distribution presents an approximate power-law which means that flow equilibrium profits little from distributed peer-to peer mechanism actually.
26132055
Car Plate Localization Using Pulse Coupled Neural Network in Complicated Environment
Car plate recognition is an important problem in many traffic related applications. In this paper, we focus on car plate localization-the first step of car plate recognition. We propose a hybrid method based on Pulse Coupled Neural Network (PCNN) and wavelet analysis. First of all, we use PCNN to enhance the image. Then, regions of interest (ROIs) will be get through wavelet analysis. After that, PCNN enhancement is applied again in ROIs, followed by a training and classification process for final labelling ROIs as car plate regions or not. Experiment results show that the precision can get 96%, which is higher than other localization methods on the same image database.
14688887
Data Compression Algorithm Based on Hierarchical Cluster Model for Sensor Networks
A new distributed algorithm of data compression based on hierarchical cluster model for sensor networks is proposed, in which, the whole sensor network is mapped into a kind of hierarchical clusters model firstly, and then different wavelet transform models are used to commit data compression in inner and super clusters respectively. Theoretical analyses and simulation results show that, the above new methods have good performance of approximation, and can compress data and reduce the amount of data efficiently.
45577558
MM-Correction: Meta-analysis-Based Multiple Hypotheses Correction in Omic Studies
The post-Genomic Era is characterized by the proliferation of high-throughput platforms that allow the parallel study of a complete body of molecules in one single run of experiments (omic approach). Analysis and integration of omic data represent one of the most challenging frontiers for all the disciplines related to Systems Biology. From the computational perspective this requires, among others, the massive use of automated approaches in several steps of the complex analysis pipeline, often consisting of cascades of statistical tests. In this frame, the identification of statistical significance has been one of the early challenges in the handling of omic data and remains a critical step due to the multiple hypotheses testing issue, given the large number of hypotheses examined at one time. Two main approaches are currently used: p-values based on random permutation approaches and the False Discovery Rate. Both give meaningful and important results, however they suffer respectively from being computationally heavy -due to the large number of data that has to be generated-, or extremely flexible with respect to the definition of the significance threshold, leading to difficulties in standardization. We present here a complementary/alternative approach to these current ones and discuss performances, properties and limitations.
6708583
Reducing error accumulation effect in multithreaded memory systems
Chip multithreading is exposed to dual challenges of increasing chip complexity and design variations. It is important to develop effective reliability-enhancing schemes to ensure robust computing. In this paper, we propose the immediate write-back and self-recovery schemes to reduce error accumulation effect in multithreaded memory systems. These schemes are built upon the previously proposed dynamic multithreading redundancy technique for improving reliability in multithreaded architectures. The idea of DMR is to exploit self-generated hardware redundancy due to inter-thread variations inherent in multithreaded architectures. Simulation results demonstrate that the proposed solutions improve error-control performance with minimal hardware overheads. The proposed immediate write-back and self-recovery schemes also feature good scalability for future process generations