Danilo Oliveira

Sensitivity analysis of a hierarchical model of mobile cloud computing

Abstract Mobile cloud computing is a new paradigm that uses cloud computing resources to overcome the limitations of mobile computing. Due to its complexity, dependability and performance studies of mobile clouds may require composite modeling techniques, using distinct models for each subsystem and combining state-based and non-state-based formalisms. This paper uses hierarchical modeling and four different sensitivity analysis techniques to determine the parameters that cause the greatest impact on the availability of a mobile cloud. The results show that distinct approaches provide similar results regarding the sensitivity ranking, with specific exceptions. A combined evaluation indicates that system availability may be improved effectively by focusing on a reduced set of factors that produce large variation on the measure of interest. The time needed to replace a fully discharged battery in the mobile device is a parameter with high impact on steady-state availability, as well as the coverage factor for the failures of some cloud servers. This paper also shows that a sensitivity analysis through partial derivatives may not capture the real level of impact for some parameters in a discrete domain, such as the number of active servers. The analysis through percentage differences, or the factorial design of experiments, fulfills such a gap.

Molecular surveillance of the Newcastle disease virus in domestic and wild birds on the North Eastern Coast and Amazon biome of Brazil

Brazil is one of the worlds largest countries with a rich diversity of wildlife, including resident and migratory wild birds, which may be natural reservoirs of the Newcastle disease virus (NDV). Because Brazil is a major global exporter of chicken meat, the emergence of such a disease may have a huge negative impact not only on the economy due to trade restrictions and embargoes, but also on the quality of life of the population. Samples were collected from 1,022 asymptomatic domestic and wild birds from the Brazilian coast and the Amazon region using tracheal/cloacal swabs and tested by RT-qPCR. The results showed 7 (0.7%) birds were positive for NDV. The positive samples were then isolated in embryonated chicken eggs and their matrix protein genes were partially sequenced, revealing a low-pathogenicity NDV. This study confirms the maintenance of the velogenic-NDV free status of Brazil.

An Investigative Approach to Software Aging in Android Applications

This paper proposes an investigative approach to indicators of software aging in applications developed for Android, a Linux-based operating system primarily designed for touch screen mobile devices such as smartphones and tablets. Software aging is a degrading factor in systems, leading to poor performance, failures, and may ultimately result in system downtime. The methodology proposed identifies memory leaking in Android applications. In order to test the approach, case studies were performed with the Monkey tool as workload generator, employing Linux utilities to monitor the environment. Communication between the computer and the smartphone was handled with the ADB tool, a toolkit included in the Android SDK package. Experimental results confirmed both the effectiveness of the procedure and the existence of software aging phenomenon in the Foursquare application running on the Android OS platform.

Dependability evaluation of a mhealth system using a mobile cloud infrastructure.

The use of mobile cloud computing infrastructure can be used to improve the delivery of health services. This paper proposes a high-level model that characterizes the behavior of an mHealth system. The main objective of this work is to identify the probability of a message being delivered at a time t, whereas several components involved may fail. Various scenarios were analysed considering different possibilities for communications, battery discharge rates and timeouts. The results show that, in the best case, a message may be delivered in 1.3 minutes with a 0.9999 probability, but in the worst case may take up to 8.8 minutes.

Hierarchical Model and Sensitivity Analysis for a Cloud-Based VoD Streaming Service

Cloud computing environments provide storage capacity, processing power, and other computational resources in a flexible way, enabling fast adaptation to highly dynamic workloads. Multimedia services, such as video streaming, are examples of applications that can use cloud computing to leverage their provisioning capacity. This way, it is possible to offer a large variety of multimedia content in many formats, so the users will be able to watch videos as they wish, with a proper resolution and quality, according to his preferences and connection speed. Private infrastructures for Video on Demand (VoD) and live video streaming are especially useful for e-learning on large corporations, universities, and governments. Analytical models are effective tools to evaluate the availability of software, hardware, and other computational resources. In this paper, we study a VoD service hosted in a private cloud computing environment. We present availability models considering the VoD streaming server components that are necessary for viewers access. Hierarchical modeling techniques are used to deal with the complexity of representing such system. Sensitivity analysis is used to determine the parameters that cause greatest impact on the availability, identifying which components require attention when attempting to achieve increased availability in a system. The proposed models are useful for planning private cloud infrastructures for VoD services.

Mobile Cloud Performance Evaluation Using Stochastic Models

Mobile Cloud Computing (MCC) helps increasing performance of intensive mobile applications by offloading heavy tasks to cloud computing infrastructures. The first step in this procedure is partitioning the application into small tasks and identifying those that are better suited for offloading. The method call partitioning strategy splits the code into a set of method calls that are offloaded to remote servers. Quite often, many applications need to make use of multiple servers for parallel processing of intensive computational operations. Predicting the behavior of such parallelizable applications is not an easy task. Deciding the number of remote servers determines the performance of the applications and the costs of the cloud usage. On one hand, users are interested in improving the performance of their applications, so they would like to use as many servers as possible, but on the other hand, they would also like to reduce their costs by using fewer cloud resources. In this paper, we propose a Stochastic Petri Net (SPN) modeling strategy to represent method call executions of mobile cloud systems. This approach enables a designer to plan and optimize MCC environments in which SPNs represent the system behavior and estimate the execution time of parallelizable applications.

Performance evaluation of medical imaging service

Public/private decision makers have faced challenges to improve healthcare services for supporting the increasing demand and simultaneously reducing the associated costs. Although the adoption of information and communication technologies (ICTs) are important in this context, the current service status should be firstly examined and different configurations/scenarios quantitatively evaluated before any further adjustment. Formal methods are of great importance, since they provide mathematical means for quantitative evaluation of systems and allow property analysis/verification. This paper presents an approach based on stochastic Petri nets for the performance evaluation of medical imaging service, adopting a real-world case study to demonstrate the feasibility of the proposed approach.

Advanced Stochastic Petri Net Modeling with the Mercury Scripting Language

Formal models are widely used in performance and dependability studies of computational systems. Graphical modeling tools allow users to compose such models with ease, but they complicate the creation of models with a dynamic/complex structure, the hierarchical arrangement of different models, and the automatic execution of models with different parameter configurations. To overcome this problem, we created a scripting language for the Mercury tool that supports the combination of different modeling approaches (e.g., Stochastic Petri Nets and Reliability Block Diagrams) in a single project. In this paper, we focus on the extensions developed to improve the capabilities of Generalized Stochastic Petri net Modeling: substitution transitions, phase-type delays for timed transitions, support for nets with a variable structure, and event-based programming for simulation.

Mercury: Performance and Dependability Evaluation of Systems with Exponential, Expolynomial, and General Distributions

The evaluation of dependability or performance of general systems usually relies on the assistance of stochastic modeling and simulation tools. Those software packages enables the creation of models and computation of metrics quickly and accurately. This paper introduces the Mercury tool, which is an integrated software that enables creating and evaluating Reliability Block Diagrams, Stochastic Petri Nets, Continuous Time Markov Chains, and Energy Flow Models. Mercury provides a graphical user interface, a script language for command-line interface, and also an API (Application Programming Interface) that enables interaction through external applications. The evaluation of models is not restricted to the assumption of Exponential distributions, which is a common constraint in other similar tools. Mercury implements a simulation framework that allows more than 25 probability distributions, as well as a moment matching method that enables expolynomial —phase-type —distributions for models solved through numerical analysis. This paper presents the main features and methods available in Mercury to aid the dependability and performance evaluation of various systems, for both academy and industry. The accuracy and applicability of the tool is illustrated by a case study of packet loss and throughput for a Video on Demand (VoD) system.