Abstract:
A method for automatic database design for scalability by receiving a database schema and database workload; applying transaction chopping to split a large transaction into smaller transactions; select one or more transactions using dynamic programming based on transaction weights; deriving a database design that covers the selected transactions; and generating a transaction class design that is scalable.
Abstract:
A system and method for analysis of complex systems which includes determining model parameters based on time series data, further including profiling a plurality of types of data properties to discover complex data properties and dependencies; classifying the data dependencies into predetermined categories for analysis; and generating a plurality of models based on the discovered properties and dependencies. The system and method may analyze, using a processor, the generated models based on a fitness score determined for each model to generate a status report for each model; integrate the status reports for each model to determine an anomaly score for the generated models; and generate an alarm when the anomaly score exceeds a predefined threshold.
Abstract:
A system and method for analysis of complex systems which includes determining model parameters based on time series data, further including profiling a plurality of types of data properties to discover complex data properties and dependencies; classifying the data dependencies into predetermined categories for analysis; and generating a plurality of models based on the discovered properties and dependencies. The system and method may analyze, using a processor, the generated models based on a fitness score determined for each model to generate a status report for each model; integrate the status reports for each model to determine an anomaly score for the generated models; and generate an alarm when the anomaly score exceeds a predefined threshold.
Abstract:
Systems and method for modeling system dynamics, including extracting features representative of a temporal evolution of a dynamical system, further including deriving one or more vector trajectories by performing sliding window segmentation of one or more time series; applying a linear test to determine whether the one or more vector trajectories are linear or nonlinear; and performing linear or nonlinear subspace decomposition on the vector trajectory based on the linear test. The system and method may generate a system evolution model from the extracted features of the dynamical system and determine a fitness score of the system evolution model.