In this paper we use the Activity diagram of the System Modeling Language (SysML) in combination with the new UML profile for Modeling and Analysis of Real-Time and Embedded systems (MARTE) in order to validate functional, timing and low power requirements in early phases of the embedded system development life-cycle. However, SysML lacks a formal semantics and hence it is not possible to apply, directly, mathematical techniques on SysML models for system validation. Thus, a novel approach for automatic translation of SysML Activity diagram into Time Petri Net with Energy constraints (ETPN) is proposed. In order to depict the practical usability of the proposed method, a case study is presented, namely, pulse-oximeter. Besides, the estimates obtained (execution time and energy consumption) from the model are 95% close to the respective measures obtained from the real hardware platform.

Data centers have evolved dramatically in recent years, due to the advent of social networking services, e-commerce and cloud computing. The conflicting requirements are the high availability levels demanded against the low sustainability impact and cost values. The approaches that evaluate and optimize these requirements are essential to support designers of data center architectures. Our work aims to propose an integrated approach to estimate and optimize these issues with the support of the developed environment, Mercury. Mercury is a tool for dependability, performance and energy flow evaluation. The tool supports reliability block diagrams (RBD), stochastic Petri nets (SPNs), continuous-time Markov chains (CTMC) and energy flow (EFM) models. The EFM verifies the energy flow on data center architectures, taking into account the energy efficiency and power capacity that each device can provide (assuming power systems) or extract (considering cooling components). The EFM also estimates the sustainability impact and cost issues of data center architectures. Additionally, a methodology is also considered to support the modeling, evaluation and optimization processes. Two case studies are presented to illustrate the adopted methodology on data center power systems.

Containers emerged as a new alternative to the virtual machines in large enterprise systems due to their virtualization mechanism that demands a low utilization level of the computational resources. Performance evaluation of Containers and virtual machines provides to practitioners and system administrators information about the quality of the services provisioned for virtualization. The main goal of this paper is to conduct a comparative study of the performance evaluation of virtual machines and containers. In order to accomplish this, a methodology is proposed to evaluate the performance of Docker containers and virtual machines. Additionally, a real-world case study is presented to illustrate the applicability of the proposed approach. For all the experiments, the Docker container shown lower execution times for the requests against virtual machine.