Gustavo Rau de Almeida Callou

A Methodology for Mapping SysML Activity Diagram to Time Petri Net for Requirement Validation of Embedded Real-Time Systems with Energy Constraints

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.

Quantifying the sustainability impact of data center availability

Data center availability is critical considering the explosive growth in Internet services and peoples dependence on them. Furthermore, in recent years, sustainability has become important. However, data center designers have little information on the sustainability impact of data center availability architectures. In this paper, we present an approach to estimate the sustainability impact of such architectures. Availability is computed using Stochastic Petri Net (SPN) models while an exergy-based lifecycle assessment (LCA) approach is used for quantifying sustainability impact. The approach is demonstrated on real life data center power infrastructure architectures. Five different architectures are considered and initial results show that quantification of sustainability impact provides important information to a data center designer in evaluating availability architecture choices.

Mapping SysML State Machine Diagram to Time Petri Net for Analysis and Verification of Embedded Real-Time Systems with Energy Constraints

The main objective of this paper is to propose a solution for modeling, analysis and verification of embedded real-time systems with energy constraints. For that, we combine functionalities of the SysML models and annotation from MARTE with the advantages of using time Petri net. This formalism allows analysis and verification of functional, timing and energy requirements in early phases of the development lifecycle. In order to depict the practically usability of the proposed method, a real-world case study is presented, namely, pulse-oximeter. Experimental results have demonstrated an accuracy of 96% using the proposed formal method in comparison with the values obtained with the hardware platform.

Energy consumption and execution time estimation of embedded system applications

Embedded systems often have conflicting constraints such as energy and time which considerably harden the design of those systems. In this context, this work proposes a mechanism for supporting design decisions on energy consumption and performance of embedded system applications. In order to depict the practical usability of the proposed methodology, a real case study as well as customized examples are presented. The estimates obtained through the conceived model are 93% close to the respective measures obtained from the real hardware platform.

Models for dependability and sustainability analysis of data center cooling architectures

The advent of cloud computing, social networks and e-commerce have demanded more computational resources from data centers. Prominent issues are sustainability, cost and dependability, which are significantly impacted by the redundant infrastructures needed to support those services. In this context, models are important to support data center designers to estimate previous issues before implementing the final architecture. This paper proposes a set of models for the integrated quantification of sustainability impact, cost and dependability of data center cooling infrastructures with the support of an environment, namely, ASTRO. Besides, a model is proposed for verifying if the energy flow does not exceed the maximum energy capacity that each component can provide (considering power devices) or the maximum cooling capacity (assuming cooling equipment). Additionally, this work presents a case study which analyzes the environmental impact, dependability metrics as well as the acquisition and operational costs of five real-world data center cooling architectures.

ASTRO: A tool for dependability evaluation of Data Center infrastructures

The advent of cloud computing has demanded more computational resources from data centers in order to provide high-availability services required in this new paradigm. To support data center dependability evaluation, this paper presents a tool, namely, ASTRO, which adopts a hybrid modeling approach, that includes Reliability Block Diagrams (RBD), Stochastic Petri Nets (SPN) and Data Center High-Level models. In addition, this tool also provides a prominent functionality in which an evaluation result can be reused in other models. ASTRO Tool also permits a hierarchical modeling, supporting the piecewise approach proposed by the methodology in which the tool is inserted.

Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes

The advent of services such as cloud computing, social networks and e-commerce has led to an increased demand for computer resources from data centers. Prominent issues for data center designers are sustainability, cost, and dependability, which are each significantly affected by the redundant architectures required to support these services. Within this context, models are important tools for designers when attempting to quantify these issues before implementing the final architecture. This paper proposes a set of models for the integrated quantification of the sustainability impact, cost, and dependability of data center power and cooling infrastructures. This is achieved with the support of an environment called ASTRO. The approach taken to perform the system dependability evaluation employs a hybrid modeling strategy which recognizes the advantages of both stochastic Petri nets and reliability block diagrams. Additionally, an energy flow model is proposed to estimate the environmental impact and cost of data center architectures whilst respecting the energy constraints of each device. This work also presents a case study which analyzes the environmental impact and dependability metrics as well as the operational energy cost of real-world data center power and cooling architectures within the context of the energy mixes of the US and Brazil.

A Petri Net-Based Approach to the Quantification of Data Center Dependability

Data center availability and reliability have accomplished greater concern due to increased dependence on Internet services (e.g., Cloud computing paradigm, social networks and e-commerce). For companies that heavily depend on the Internet for their operations, service outages can be very expensive, easily running into millions of dollars per hour [15]. A widely used design principle in fault-tolerance is to introduce redundancy to enhance availability. However, since redundancy leads to additional use of resources and energy, it is expected to have a negative impact on sustainability and the associated cost.

Estimating reliability importance and total cost of acquisition for data center power infrastructures

The number and size of data centers have greatly increased in recent years, mainly, due to the explosive growth of Internet services, such as those based on cloud computing paradigm. Therefore, service providers have intensified efforts on improving the quality of services while minimizing the costs of data centers, for instance, those associated to out-of-services periods. In other words, robust data center infrastructures are necessary, such that dependability requirements are satisfied while simultaneously incurring costs as minimal as possible. This paper proposes an approach that combines reliability importance indexes with TCA (Total Cost of Acquisition) to evaluate data center power infrastructures. The proposed approach aims at indicating the benefits and drawbacks of different architectures for power infrastructures to guide the decision maker in evaluating the most appropriate design.

Estimating sustainability impact, total cost of ownership and dependability metrics on data center infrastructures

The advent of cloud computing has demanded more computational resources from data centers. Prominent issues are dependability, total cost of ownership and sustainability, which are significantly impacted by the redundant infrastructures needed to support cloud computing services. In this context, models are important to support data center designers to estimate previous issues before implementing the final infrastructure. This paper presents a set of formal models for estimating sustainability impact and dependability metrics in data center infrastructures with the support of an integrated environment, namely, ASTRO. Besides, we adopt reliability importance to identify the most critical components in system reliability in order to propose different data center power infrastructures.