Hierarchically Distributed Peer-to-Peer Document Clustering and Cluster Summarization

In distributed data mining, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose a Hierarchically-distributed Peer-to-Peer (HP2PC) architecture and clustering algorithm. The architecture is based on a multi-layer overlay network of peer neighborhoods. Supernodes, which act as representatives of neighborhoods, are recursively grouped to form higher level neighborhoods. Within a certain level of the hierarchy, peers cooperate within their respective neighborhoods to perform P2P clustering. Using this model, we can partition the clustering problem in a modular way across neighborhoods, solve each part individually using a distributed K-means variant, then successively combine clusterings up the hierarchy where increasingly more global solutions are computed. In addition, for document clustering applications, we summarize the distributed document clusters using a distributed keyphrase extraction algorithm, thus providing interpretation of the clusters. Results show decent speedup, reaching 165 times faster than centralized clustering for a 250-node simulated network, with comparable clustering quality to the centralized approach. We also provide comparison to the P2P K-means algorithm and show that HP2PC accuracy is better for typical hierarchy heights. Results for distributed cluster summarization match those of their centralized counterparts with up to 88% accuracy.     

An Abstract Reachability Approach by Combining HOL Induction and Multiway Decision Graphs

In this paper, we provide a necessary infrastructure to define an abstract state exploration in the HOL theorem prover. Our infrastructure is based on a deep embedding of the Multiway Decision Graphs (MDGs) theory in HOL. MDGs generalize Reduced Ordered Binary Decision Diagrams (ROBDDs) to represent and manipulate a subset of first-order logic formulae. The MDGs embedding is based on the logical formulation of an MDG as Directed Formulae (DF). Then, the MDGs operations are defined and the correctness pro...     

Improved Results on Passivity Analysis of Uncertain Neural Networks with Time-Varying Discrete and Distributed Delays

In this paper, the passivity analysis problem is investigated for uncertain neural networks with time-varying discrete and distributed delays. Based on direct delay decomposition idea and free-weighting matrix approach, several new delay-dependent passive criterions are derived in terms of linear matrix inequalities (LMIs), which can be easily checked by the Matlab LMI toolbox. Numerical examples show that the obtained results improve some existing ones.     

A hybrid multicast connectivity solution for multi-party collaborative environments

In multi-party collaborative environments, a group of users can share multiple media streams via IP multicasting. However, despite of the efficiency of IP multicast, it is not widely available and alternative application-layer multicast approaches are introduced. Application-layer multicast is advantageous, however, it incurs additional processing delays. In this paper, we present a new hybrid-style application-layer multicast solution that satisfies both network efficiency and easy deployment. We achieve this goal by connecting multicast islands through UDP tunnels employing UMTP (UDP multicast tunneling protocol). We also design a MPROBE protocol to remove multicast loop among multicast island in real Internet. We verify the feasibility of the proposed solution by implementing a prototype tool, AG Connector, that works on Access Grid multi-party collaborative environment.

Evaluating the energy consumption and the silicon area of on-chip interconnect architectures

Sophisticated on-chip interconnects using packet and circuit switching techniques were recently proposed as a solution to non-scalable shared-bus schemes currently used in Systems-on-Chip (SoCs) implementation. Different interconnect architectures have been studied and adapted for SoCs to achieve high throughput, low latency and energy consumption, and efficient silicon area. Recently, a new on-chip interconnect architecture by adapting the WK-recursive network topology structure has been introduced for SoCs. This paper analyses and compares the energy consumption and the area requirements of Wk-recursive network with five common on-chip interconnects, 2D Mesh, Ring, Spidergon, Fat-Tree and Butterfly Fat-Tree. We investigated the effects of load and traffic models and the obtained results show that the traffic models and load that ends processing elements has a direct effect on the energy consumption and area requirements. In these results, WK-recursive interconnect generally has a higher energy consumption and silicon area requirements in heavy traffic load.     

DuD Recht

DuD Recht

DuD Recht     

Schmeh, Klaus: Versteckte Botschaften (TELEPOLIS): Die faszinierende Geschichte der Steganografie

Ohne Zusammenfassung     

Weak and strong stabilization of linear systems

We study the problem of stabilizing a distributed linear system on a subregion of its geometrical domain. We are concerned with two methods： the first approach enables us to characterize a stabilizing control via the steady state Riccati equation, and the second one is based on decomposing the state space into two suitable subspaces and studying the projections of the initial system onto such subspaces. The obtained results are performed through various examples.     

Stability margin of uncertain control systems

Achieving stability is the essential issue in the control system design. In this paper, four approaches that can be used to calculate the stability margin of the interval plant family are summarized and compared. The μ approach gives the bounds of the stability margin, and good estimation can be obtained with the numerical method. The eigenvalue approach yields accurate value, and the MATLAB＇s function robuststab sometimes provides wrong results. Since the eigenvalue approach is both accurate and computationally efficient, it is recommended for the calculation of the stability margin, while utilization of the function robuststab should be avoided due to the unreliable results it gives.