In the article we study a model of TCP connection with Active Queue Managementin an intermediate IP router. We use the fluid flow approximation technique to model the interactions between the set of TCP flows and AQM algoithms. Computations for fluid flow approximation model are performed in the CUDA environment.
This paper addresses the problem of efficient searchingfor Nonlinear Feedback Shift Registers (NLFSRs) with a guaranteed full period. The maximum possible period for an n-bit NLFSR is 2n1 (an all-zero state is omitted). A multi-stages hybrid algorithm which utilizes Graphics Processor Units (GPU) power was developed for processing data-parallel throughput computation. Usage of the abovementioned algorithm allows giving an extended list of n-bit NLFSR with maximum period for 7 cryptographically applicable types of feedback functions
This paper presents an alternative approach to the sequential data classification, based on traditional machine learning algorithms (neural networks, principal component analysis, multivariate Gaussian anomaly detector) and finding the shortest path in a directed acyclic graph, using A* algorithm with a regression-based heuristic. Palm gestures were used as an example of the sequential data and a quadrocopter was the controlled object. The study includes creation of a conceptual model and practical construction of a system using the GPU to ensure the realtime operation. The results present the classification accuracy of chosen gestures and comparison of the computation time between the CPU- and GPU-based solutions.