Eduardo Tavares

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.

Dependability models for designing disaster tolerant cloud computing systems

Hundreds of natural disasters occur in many parts of the world every year, causing billions of dollars in damages. This fact contrasts with the high availability requirement of cloud computing systems, and, to protect such systems from unforeseen catastrophe, a recovery plan requires the utilization of different data centers located far enough apart. However, the time to migrate a VM from a data center to another increases due to distance. This work presents dependability models for evaluating distributed cloud computing systems deployed into multiple data centers considering disaster occurrence. Additionally, we present a case study which evaluates several scenarios with different VM migration times and distances between data centers.

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.

Dependability assessment of virtualized networks

One of the key characteristics of virtual networks (VN) is their intrinsic dynamical aspects. VNs allow network operators to have on-demand negotiation of a variety of services. Risks are inherent to virtualized infrastructures since the underlying physical network components are failure-prone. Therefore evaluation and analysis of risks in VNs, from assessment of dependability attributes, are of paramount importance for accurate management and control tasks. This paper proposes and evaluates a method to assess dependability in virtualized network environments. Through the use of Reliability Block Diagram (RBD) and Stochastic Petri Nets (SPN), we provide a first look at risks in network virtualization by means of dependability modeling and analysis. Our methodology allows the networking research community to develop new heuristics when dealing with resource allocation in VNs, while taking into account dependability attributes.

Analyzing software performance and energy consumption of embedded systems by probabilistic modeling: an approach based on coloured petri nets

This paper presents an approach for analyzing embedded systems’ software energy consumption and performance based on probabilistic modeling. Such an approach applies Coloured Petri Net modeling language (CPN) for supporting simulation and analysis. The proposed approach offers three basic contributions for embedded system analysis field:(i)code modeling, a probabilistic model for scenarios exploration being presented, (ii) formalism, a formal and widespread modeling language (CPN) being applied, with previously validated engines and algorithms for simulation;(iii) flexibility, the proposed approach enabling modeling of different micro-controllers at different abstraction levels.

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.

Hard real-time tasks' scheduling considering voltage scaling, precedence and exclusion relations

Several scheduling approaches have been developed to address DVS in time-critical systems, however, overheads, precedence and exclusion relations have been neglected. This paper presents a pre-runtime scheduling method for hard real-time systems considering DVS, overheads as well as inter-task relations. The proposed method adopts a formal model based on time Petri nets in order to find a feasible schedule that satisfies timing and energy constraints.

An Environment for Measuring and Scheduling Time-Critical Embedded Systems with Energy Constraints

Over the last decade, energy consumption has received considerable attention from the scientific community, which has developed several techniques for increasing energy savings in embedded systems. Nevertheless, considering time-critical systems, the adoption of energy saving techniques,such as dynamic voltage scaling, considerably hardens the system design, since stringent timing constraints may be affected. This work presents an environment for measuring and scheduling hard real-time systems with energy constraints, providing a set of integrated tools for automatic assistance in these design activities. Besides, a formal model based on time Petri nets is adopted in order to provide a basis for precise pre-runtime schedule generation as well as to allow property analysis and verification.

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.