Thais Webber

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The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of parallel and distributed systems. However, iterative numerical algorithms, even well-fitted to a multidimensional structured representation of Markov chains, still face the state space(More)
This paper presents a software package, called GTAexpress, to handle structured continuous-time Markovian models expressed using Generalized Tensor Algebra, also known as, Kronecker descriptors. The proposed software package has the most advanced methods to provide stationary and transient solutions as well as some basic structural properties of models(More)
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(More)
The key operation to obtain stationary and transient solutions of transition systems described by Kronecker structured formalisms is the Vector-Descriptor product. This operation is usually performed with shuffling operations and matrices aggregations to reduce the floating point multiplications inside iterative methods. Due to the flexibility of the(More)
This paper proposes an architectural improvement for the Modbus RTU protocol to integrate equipments in industrial automation networks, employing hybrid communication with wired Modbus RTU and wireless IEEE 802.15.4. These environments have different electromagnetic interferences, requiring protocols with noise immunity to varied equipments such as motors(More)
Many Markovian stochastic structured modeling formalisms like Petri nets, automata networks and process algebra represent the infinitesimal generator of the underlying Markov chain as a descriptor instead of a traditional sparse matrix. A descriptor is a compact and structured storage based on a sum of tensor (Kronecker) products of small matrices that can(More)
Software development projects have become a challenge for both industry and academia regarding the performance evaluation of teams. Recently, a Stochastic Automata Networks (SAN) model was proposed as theoretical representation for performance prediction of software development teams. In this paper, we present an exercise of such SAN analytical modeling for(More)
The description of large state spaces through stochastic structured modeling formalisms like stochastic Petri nets, stochastic automata networks and performance evaluation process algebra usually represent the infinitesimal generator of the underlying Markov chain as a Kronecker descriptor instead of a single large sparse matrix. The best known algorithms(More)
Simulation is an interesting alternative to solve Markovian models. However, when compared to analytical and numerical solutions it suffers from a lack of precision in the results due to the very nature of simulation, which is the choice of samples through pseudorandom generation. This paper proposes a different way to simulate Markovian models by using a(More)
Kronecker descriptors are an efficient option to store the underlying Markov chain of a model in a structured and compact fashion. The basis of classical numerical solutions for Kronecker descriptors represented models is the VectorDescriptor Product (VDP). The Shuffle algorithm is the most popular VDP method to handle generalized descriptors, i.e.,(More)