Orlando Loques

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This paper proposes and evaluates an approach for power and performance management in virtualized server clusters. The major goal of our approach is to reduce power consumption in the cluster while meeting performance requirements. The contributions of this paper are: (1) a simple but effective way of modeling power consumption and capacity of servers even(More)
In this paper we present an optimization solution for power and performance management in a platform running multiple independent applications. Our approach assumes a virtualized server environment and includes an optimization model and strategy to dynamically control the cluster power consumption, while meeting the application's workload demands.
An increasing number of large-scale server clusters are being deployed in data centers for supporting many different web-based application services in a seamless fashion. In this scenario, the rising energy costs for keeping up those web clusters is becoming an important concern for many business. In this paper we present an optimization solution for power(More)
Heterogeneous multi-core processors with big/highperformance and small/low-power cores have been proposed as an alternative design to improve energy efficiency over traditional homogeneous multi-cores. We make the case for proportional-share scheduling of threads in heterogeneous processor cores aimed at improving combined energy efficiency and performance.(More)
This paper presents an approach to describe, deploy and manage component-based applications having dynamic functional and non-functional requirements, which include different types of QoS. The approach is centered on an ADL that allows functional and non-functional requirements to be described by high-level textual contracts. The meta information extracted(More)
Self-Adaptive Systems are target of frequent research regarding different aspects. However, they still present several challenges related to assurance, dependability, verification, and validation. Adaptations can be related to a set of concerns (i.e., why, what, when, where, who, and how), which are evaluated during, operation and post operation phases. We(More)
We present a decision-level data fusion technique for monitoring and reporting critical health conditions of a hypertensive patient at home. Variables associated to the patient (physiological and behavioral) and to the living environment are considered in the solution, contributing to improve the confidence on the system outputs. In the paper, we model the(More)
The rising energy costs for keeping up large-scale server clusters is becoming an increasingly important concern for many businesses. In this paper, we present a dynamic configuration model for consolidating multiple services or applications in virtualized server clusters aimed at optimizing power consumption. Dynamic configurations in the cluster include(More)
The current trend to move from homogeneous to heterogeneous multicore systems provides compelling opportunities for achieving performance and energy efficiency goals. Running multiple threads in multicore systems poses challenges on meeting limited shared resources, such as memory bandwidth. We propose an optimization approach that includes an Integer(More)