Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Characterization of soils in an area of prescribed fire

The prescribed fire is a technique that is often used, it has several advantages. Pedological and hydropedological techniques were tested to assess the prescribed fire changes may cause in soils. This work was performed in Tresminas area (Vila Pouca de Aguiar, Northern Portugal), during February and March 2011. In the present study we applied several techniques. For the field sampling was followed the ISO 10381-1[1], ISO 10381-2[2], and FAO rules [3], as well as were used a grid with 17 points for measuring the soil parameters. During the fire, we have tried to check, with the assistance of the Portuguese Forestry Authority, some important parameters such as, the propagation speed, the size of the flame front and the intensity of energy emitted per unit area. Before the fire, was collected carefully soil disturbed and undisturbed samples for laboratory analysis, and measured soil water content; we also have placed four sets of thermocouples for measuring soil temperature. After the fire, were collected the thermocouples and new soil samples; the water content were measured in the soil and collected ashes. In the laboratory, after preparing and sieving the samples, were determined the soil particle size. The soil pH and electrical conductivity in water was also determined. The total carbon (TC) and inorganic carbon (IC)[4] was measured by a Shimadzu TOC-Vcsn. The water content in soil has not varied significantly before and after the fire, as well as soil pH and soil electrical conductivity. The TC and IC did not change, which was expected, since the fire not overcome the 200° C. Through the various parameters, we determined that the prescribed fire didn’t affect the soil. The low temperature of the fire and its rapid implementation that lead to the possible adverse effects caused by the wild fire didn’t occurred.

Fractional Dynamics of Computer Virus Propagation

We propose a fractional model for computer virus propagation. The model includes the interaction between computers and removable devices. We simulate numerically the model for distinct values of the order of the fractional derivative and for two sets of initial conditions adopted in the literature. We conclude that fractional order systems reveal richer dynamics than the classical integer order counterpart. Therefore, fractional dynamics leads to time responses with super-fast transients and super-slow evolutions towards the steady-state, effects not easily captured by the integer order models.

Fractional Dynamics of Computer Virus Propagation

We propose a fractional model for computer virus propagation. The model includes the interaction between computers and removable devices. We simulate numerically the model for distinct values of the order of the fractional derivative and for two sets of initial conditions adopted in the literature. We conclude that fractional order systems reveal richer dynamics than the classical integer order counterpart. Therefore, fractional dynamics leads to time responses with super-fast transients and super-slow evolutions towards the steady-state, effects not easily captured by the integer order models.