Afonso Sales

Performance Models For Master/Slave Parallel Programs

This paper proposes the use of Stochastic Automata Networks (SAN) to develop models that can be efficiently applied to a large class of parallel implementations: master/slave (m/s) programs. We focus our technique in the description of the communication between master and slave nodes considering two standard behaviors: synchronous and asynchronous interactions. Although the SAN models may help the pre-analysis of implementations, the main contribution of this paper is to point out advantages and problems of the proposed modeling technique.

Analytical Modeling for Operating System Schedulers on NUMA Systems

Performance evaluation by benchmarking is one of the main approaches for measuring performance of a computer system. However, it is important to measure parts of a system before they are even implemented. This can be achieved through an analytical description of the system, allowing the analysis of the system performance. Additionally, the analytical model can be extended to consider also reliability issues. This paper presents a generic model for an Operating System (OS) scheduler using the Stochastic Automata Networks (SAN) formalism. SAN are used to describe processes and processors in the OS and their behavior when processes have to be migrated. Moreover, processor failures are also modeled in order to provide reliability indices. The proposed model uses actual benchmarks results obtained from a 4-processor Itanium2 SMP machine and a 12-processor Itanium2 NUMA machine.

Modular analytical performance models for ad hoc wireless networks

Wireless ad hoc networks raised a series of challenging research tracks. In order to analyze and validate the research results achieved, thorough performance evaluation efforts are needed. In this context, the contribution of this paper is two fold: at one side we investigate the effect of forwarding in wireless ad hoc networks, drawing the throughput behavior under variation of connectivity, interference end number of sources; on the other side we propose stochastic automata networks (SAN) as a formalism well suited to the area because of its modularity, allowing model reuse and the structured stepwise representation of important aspects of the reality, and due to its ability to deal with models of considerable sizes, allowing the analytical evaluation of more complex situations.

Structured stochastic modeling of fault-tolerant systems

Fault-tolerant mechanisms have been increasingly used to develop safety-critical systems. Therefore, the accurate description of these mechanisms is crucial if we do not want their use to bring any kind of unexpected result due to the misinterpretation of their features. The paper presents a new way of precisely describing fault tolerant mechanisms using a formalism that has a Markovian behavior. More specifically, we describe how to apply stochastic automata networks (SAN) to describe a dependable multiparty interaction (DMI) mechanism.

Reachable State Space Generation for Structured Models which Use Functional Transitions

This paper presents a new approach to obtain the Reachable State Space (RSS) of a structured model which uses functional transitions. We use Multi-valued Decision Diagrams (MDD) to store sets of reachable spaces and Stochastic Automata Networks (SAN) formalism to describe structured models. We focus our contribution in the proposal of a method to generate a compact MDD description taking advantage of the modular structure of SAN formalism, which also allows to represent the transition rate matrix of a continuous-time Markov chain by means of a sum of generalized Kronecker products. The method is tested on some models and the conclusion presents future work.

Analysis of exponential reliable production lines using Kronecker descriptors

This paper presents a solution procedure for reliable production lines with service times distributed according to an exponential distribution, based on a Markovian formulation with a Kronecker structured representation (sum of tensor products). Specifically, structured Markovian formalisms are used to reduce the impact of the well-known state explosion problem associated with other methods of solution. Such formalisms combined with the Kronecker representation deliver memory efficiency in storing very large models, i.e. models with more than states. The exact steady-state solutions of these models may be obtained using efficient existing software packages. The proposed solution procedure is illustrated with two detailed examples, and generalised with a model construction algorithm. The computed throughput for several examples of production lines with perfectly reliable machines, as well as the computational costs in terms of CPU time to solve them with PEPS2007 and GTAexpress software packages, are also presented. In effect the paper demonstrates the power of the use of the Kronecker descriptor analysis applied to the derivation of the exact solution of the particular class of production lines considered. The Kronecker descriptor methodology is well-known to analysts concerned with computer and communication systems.

Analytical Modeling of Software Development Teams in Globally Distributed Projects

Global software engineering is an area of increasing research challenges, in which teams are dispersed in multiple sites collaborating across borders and time zones. In spite of its potential competitive advantages, globally distributed projects must deal with difficulties when distributing resources such as teams with cultural diversities, different skills and experience levels. Both industry and academia demonstrate a special interest in the modeling and prediction, mainly representing systems in order to extract interesting indices, for example, evaluating whether or not a project will succeed. This paper demonstrates the usefulness of analytical modeling techniques in order to predict the outcome of geographically-distributed projects. We focus our attention to the participants interaction and its interplay when it affects team productivity. The models are parametrized considering single-site and multi-site scenarios, varying resources availability, teams expertise and support levels. Performance indices from both scenarios are presented and conclusion indicates possible model extensions.

Combining Challenge-Based Learning and Scrum Framework for Mobile Application Development

The market for mobile applications has been growing dramatically, as has the complexity of the applications and the speed of the development process. These changes require a rethinking of the development process and of how developers are trained. In order to better prepare faculty and students for the emerging mobile application market, this study presents a new learning and software development framework that combines Agile methodologies with the Challenge-Based Learning (CBL) framework. CBL provides a student-centered learning framework that mirrors the modern workplace. Agile methodologies address the changing landscape of mobile development environments. A combination of the CBL learning framework and Agile methodologies can better prepare students for the development market. This paper presents an empirical study applying CBL and Scrum in a mobile application development course evaluated through a series of post surveys. The results indicate that a teaching and learning environment based on practical experience combining the CBL framework with the Scrum process is an eective model to promptly teach undergraduates how to be successful mobile application developers.

Stochastic Model for QoS Assessment in Multi-tier Web Services

Service Level Agreements (SLAs) are used to guarantee quality of service (QoS) between customers and service providers. In an SLA, parties establish a common set of rules and responsibilities. In this paper we propose a practical stochastic modeling of a multi-tier architecture considering SLAs for specific transactions. The model is parameterized with available performance testing data for a real web service, and with a testing environment having unpredictable and unknown external workloads of simultaneous execution. In addition, we present multiple scenarios of external applications impacting on the SLAs in our target architecture. Having a previous knowledge about the average time demanded by some external applications, our model results can provide evidences when the system under test will not respect the agreed-upon SLAs. Finally, we discuss possible model extensions towards further unknown workload characterizations and considerations about application execution profiling.

MQNA - Markovian queueing networks analyser

This paper describes the MQNA - Markovian queueing networks analyser, a software tool to model and obtain the stationary solution of a large class of queueing networks. MQNA can directly solve open and closed product-form queueing networks using classical algorithms. For finite capacity queueing models, MQNA generates Markovian description in the stochastic automata networks (SAN) and stochastic petri nets (SPN) formalisms. Such descriptions can be exported to the PEPS - performance evaluation of parallel systems and SMART - stochastic model checking analyzer for reliability and timing software tools that can solve SAN and SPN models respectively.