Mining Traces of Large Scale Systems

Proposing New Methods to Enhance the Low-Resolution Simulated GPR Responses in the Frequency and Wavelet Domains

To date, a number of numerical methods, including the popular Finite-Difference Time Domain (FDTD) technique, have been proposed to simulate Ground-Penetrating Radar (GPR) responses. Despite having a number of advantages, the finite-difference method also has pitfalls such as being very time consuming in simulating the most common case of media with high dielectric permittivity, causing the for...

Bridging the Data Gap: Data Related Challenges in Evaluating Large Scale Collaborative Security Systems

Data-sharing approaches such as collaborative security have been successfully applied to systems addressing multiple classes of cyber security threats. In spite of these results, scale presents a major challenge to further advances: collaborative security systems are designed to operate at a large scale (Internetor ISP-scale), and obtaining and sharing traces suitable for experimentation is dif...

Mining for Availability Models in Large-Scale Distributed Systems: A Case Study of SETI@home

In the age of cloud, Grid, P2P, and volunteer distributed computing, large-scale systems with tens of thousands of unreliable hosts are increasingly common. Invariably, these systems are composed of heterogeneous hosts whose individual availability often exhibit different statistical properties (for example stationary versus non-stationary behaviour) and fit different models (for example Expone...

A Three-terms Conjugate Gradient Algorithm for Solving Large-Scale Systems of Nonlinear Equations

Nonlinear conjugate gradient method is well known in solving large-scale unconstrained optimization problems due to it’s low storage requirement and simple to implement. Research activities on it’s application to handle higher dimensional systems of nonlinear equations are just beginning. This paper presents a Threeterm Conjugate Gradient algorithm for solving Large-Scale systems of nonlinear e...

Decentralized Interaction Estimators in Large Scale Power Systems with Neural Networks.