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检索条件"机构=Dpt. of Computer Architecture and Automation CCS-Center for Computational Simulation"

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Advanced migraine prediction simulation system 49

Advanced migraine prediction simulation system

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49th Summer computer simulation Conference, SCSC 2017, Part of the 2017 Summer simulation Multi-Conference, SummerSim 2017

作者： Pagán, Josué Moya, José M. Mittal, Saurabh Ayala, José L. Department of Computer Architecture and Automation CCS-Center for Computational Simulation Complutense University of Madrid Madrid Spain LSI - Electronic Engineering Department CCS-Center for Computational Simulation Technical University of Madrid Madrid Spain Complex Systems Research Lab Dunip Technologies LLC HerndonVA United States Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid Spain

ISBN: (纸本)9781510838284

In the Internet of Things (IoT) era, there is growing interest in wireless monitoring sensors for detection, classification and prediction of health symptoms. The prediction of symptoms in chronic diseases such as migraines brings new hope to improve patients' lives. The prediction of a migraine symptomatic event through monitoring hemodynamic variables has been previously demonstrated in our earlier work. In this paper, a simulation-based approach for a real-Time migraine prediction system is described. The simulation has been implemented using the specifications of the formal description language Discrete EVent Systems (DEVS). The simulation system is a proof of concept that is ready for testing in a real-world ambulatory monitoring environment. The results obtained encourage developing a hardware/software (HW/SW) cosimulation system that incorporates Hardware-in-The-Loop (HIL) components as prior step to the expensive and slow hardware implementation of a complete migraine prediction device. When such a system is used in a real-Time setting, it can simulate failures in sensors and trigger alarms for active patient response. © 2017 Society for Modeling & simulation International (SCS).

关键词： Forecasting

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Building accurate models to determine the current CPU utilization of a host within a virtual machine allocated on it 49

Building accurate models to determine the current CPU utiliz...

引用

49th Summer computer simulation Conference, SCSC 2017, Part of the 2017 Summer simulation Multi-Conference, SummerSim 2017

作者： Briongos, Samira Malagón, Pedro Risco, José L. Moya, José M. Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid Spain LSI - Electronic Engineering Department CCS-Center for Computational Simulation Universidad Poliécnica de Madrid Madrid Spain

ISBN: (纸本)9781510838284

In cloud computing environments there are several virtual machines running in the same host. This fact opens the door for possible side channel-Attacks. Prior to perform an attack it is mandatory to determine coresidency with the victim. An synchronized variation in the CPU activity in the host is a possible indicator of the presence of neighboring processes. However, cloud providers do not give information about the hosts CPU load, so we have to figure out a way of estimating it. We estimate the host CPU load considering its impact on the performance of a virtual machine (VM) running on it. In this work, we show that it is possible to calculate the CPU load of the host by executing a reference process, measuring the time it takes to execute, and using this information as an input to generate the CPU load models. We explore regression methods and regression methods tuned with genetic algorithms for the model generation. As a result, considering a CPU load value between 0 (no load) and 100 (maximum load), we obtain models which compute the host load with a mean squared error of around 5%, 10% and 30% (depending on the host architecture) when estimating the load every second. © 2017 Society for Modeling & simulation International (SCS).

关键词： Genetic algorithms

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