Stochastic Process Algebras (SPA) are process algebras in which the duration of each activity is given by a random variable. If the stochastic aspect is restricted to Markovian, i.e. exponentially distributed durations, nice algebraic foundations are available. They include a formal semantics and an equational theory for Markovian bisimulation , a congruence that can be seen as a stochastic cou...

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quanti...

In this paper, we investigate a single server batch arrival non-Markovian retrial queueing model with random break down and Bernoulli vacation. Customers arrive in batches accordingly Poisson process with arrival rate λ but are served one by one with first come first served basis. All customers demand the first essential service, whereas only some of them demand the second optional service. The...

Building performance models for microservices applications in DevOps is costly and error-prone. Accurate service demand distribution estimation critical to model parameterization. However, traditional methods focus on capturing the mean demand, disregarding higher-order moments of distribution. To address this limitation, we propose estimate higher a microservice from monitoring traces. We firs...

We introduce immediate transitions as an extension of Stochastic Process Algebras (SPA). We distinguish two diierent classes of immediate transitions: probabilistic branching and management activities. We discuss both approaches and develop a theory for the probabilistic branching case. Although we use TIPP as a sample language within this paper, the theory can easily be adapted to other Stocha...

Extended Markovian Process Algebra (EMPA) is a process algebra suitable for expressing functional and performance aspects of concurrent systems. It is equipped with an operational interleaving semantics, a functional semantics, a Markovian semantics and an operational net semantics. In this paper we apply an integrated approach based on EMPA for mod-eling and analyzing concurrent systems to the...

Stochastic (Markovian) process algebra extend classical process algebra with probabilistic exponentially distributed time durations denoted by rates (the parameter of the exponential distribution). Defining a semantics for such an algebra, so to derive Continuous Time Markov Chains from system specifications, requires dealing with transitions labeled by rates. With respect to standard process a...

In this paper, finite phase semi-Markov processes are introduced. By introducing variables and a simple transformation, every finite phase semi-Markov process can be transformed to a finite Markov chain which is called its associated Markov chain. A consequence of this is that every phase semi-Markovian switching system may be equivalently expressed as its associated Markovian switching system....

We introduce a novel stochastic process algebra, called PHASE, which directly supports phase-type distributions, useful for approximating the dynamics of non-Markovian HCI systems. In order to encourage the effective use of PHASE, we give a step by step account of how PHASE processes can be implemented in PRISM, one of the most powerful and popular probabilistic model checkers currently availab...