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Hierarchical stochastic activity networks (HSANs) are a newly introduced extension of stochastic activity networks (SANs). HSAN models encapsulate hierarchies and a key benefit of these models is the possibility of automatic employment of composition techniques by their modelling tools. For modelling and evaluation with HSANs, we have developed a software tool called SANBuilder. This tool has an integrated development environment (IDE) for construction, animation, simulation and analytic solution of SAN-based models. We have implemented in this tool some state-of-the-art methods for the simulation and analytic solution of SAN and HSAN models. In addition to an introduction to HSANs, this... 

Recently, some works have been done in studying activity network as a more realistic representation of users’ behavior in online social networks. However, there is a major deficiency of a suitable definition of activity network based on a comprehensive study of various activity networks separately and combined. The main purpose of our research is to understand the differences between users’ behavior by various Facebook activities, so as to claim that these networks should not be blindly composed; neither should the result of analyzing each of them individually be generalized to others. For this purpose, degree distribution, small-world phenomenon, degree correlation, reciprocity, and... 

Recently, some works have been done in studying activity network as a more realistic representation of users’ behavior in online social networks. However, there is a major deficiency of a suitable definition of activity network based on a comprehensive study of various activity networks separately and combined. The main purpose of our research is to understand the differences between users’ behavior by various Facebook activities, so as to claim that these networks should not be blindly composed; neither should the result of analyzing each of them individually be generalized to others. For this purpose, degree distribution, small-world phenomenon, degree correlation, reciprocity, and... 

Availability of the service delivered by cloud providers is one of the most important QoS factors of the service level agreements between providers and customers. Since current Infrastructure-as-a-Service providers use virtualization technology to manage data centers, virtual data centers (VDCs) have become a popular infrastructure for cloud computing. In order to study the service availability, a stochastic activity network (SAN) model is presented in this paper. The proposed SAN model can be appropriately used to investigate the impact of different characteristics and policies on service availability of VDCs  

Stochastic activity networks (SANs) are a stochastic generalization of Petri nets. SAN models have been used to evaluate a wide range of systems and are supported by several modeling tools. We have introduced object stochastic activity networks (OSANs) to overcome some restrictions of these models. OSANs integrate the concepts of object-orientation into SAN models. Elements of OSANs and their submodels are defined as classes. OSANs are more appropriate that most other objectoriented or high-level extensions of Petri nets for application on software systems. In this paper, we will present the definitions, behavior and an example of OSAN models. The objectorientation of OSANs and the... 

Stochastic activity networks (SANs) are a well-known petri net-based formalism used for the performance and dependability modeling of a wide range of systems. On the other hand, the growing complexity of timed systems makes it imperative to apply formal analysis techniques in the early stages of the system's development. Finding a suitable framework for the modeling, evaluation, and verication of these systems is still a great challenge. In this paper, we introduce a new formalism named timed activity networks (TANs), which are based on the activity networks that are the nondeterministic settings of the SANs. The advantages of TANs are 2-fold: 1) allowing the construction of more compact... 

We have recently introduced a high-level extension for stochastic activity networks (SANs) called coloured stochastic activity networks (CSANs). CSANs have several distinguishing properties, which make them quite appropriate for modeling and evaluation of software performance and dependability. CSANs have introduced a construct called coloured place for data manipulation. A coloured place holds a list of tokens of a userdefined token type. CSAN models can be evaluated by state space analysis techniques or discrete-event simulation. However, their state spaces will become very large, even for a small CSAN model. For efficient evaluation of these models by state space analysis methods, we will... 

The unified modelling language (UML) is a de facto standard for object-oriented modelling. However, the formal semantics for the notations included in UML are not provided, which are a key requirement for the verification and evaluation purposes. To solve this problem, Petri net formalism has been used as a complement to UML in several research projects. However, there is not a complete transformation technique for all concepts and diagrams of UML to an extension of Petri nets. We have recently introduced object stochastic activity networks (OSANs). OSANs are a high-level modelling formalism that integrates object-orientation into stochastic activity networks (SANs). In this paper, we... 

This paper presents a hierarchically distributed algorithm for the execution of distribution state estimation function in active networks equipped with some phasor measurement units. The proposed algorithm employs voltage-based state estimation in rectangular form and is well-designed for large-scale active distribution networks. For this purpose, as the first step, the distribution network is supposed to be divided into some overlapped zones and local state estimations are executed in parallel for extracting operating states of these zones. Then, using coordinators in the feeders and the substation, the estimated local voltage profiles of all zones are coordinated with the local state... 

In this paper, Stochastic Activity Networks (SANs) are exploited to model and evaluate the power consumption and performance of virtualized servers in cloud computing. The proposed SAN models the physical servers in three different power consumption and provisioning delay modes, switching the status of the servers according to the workload of the corresponding cluster if required. The Dynamic Voltage and Frequency Scaling (DVFS) technique is considered in the proposed model for dynamically controlling the supply voltage and clock frequency of CPUs. Thus, Virtual Machines (VMs) on top a physical server can be divided into several power consumption and processing speed groups. According to the... 

This paper presents a mathematical model using Stochastic Activity Networks (SANs) to model a grid resource, and compute the throughput of a resource in servicing grid tasks, wherein the failure–repair behavior of the processors inside the resource is taken into account. The proposed SAN models the structural behavior of a grid resource and evaluates the combined performance and availability measure of the resource. Afterwards, the curve fitting technique is used to find a suitable function fitted to the throughput of a resource for grid tasks. Having this function and the size of each grid job based on its tasks, an algorithm is proposed to compute the makespan of each available resource to... 

In this paper, Stochastic Activity Networks (SANs) are used to model and evaluate the performance and power consumption of an Infrastructure-as-a-Service (IaaS) cloud. The proposed SAN model is scalable and flexible, yet encompasses some details of an IaaS cloud, such as Virtual Machine (VM) provisioning, VM multiplexing, and failure/repair behavior of VMs. Using the proposed SAN, a power-aware self-adaptive resource management scheme is presented for IaaS clouds that automatically adjusts the number of powered-on Physical Machines (PMs) regarding variable workloads in different time intervals. The proposed scheme respects user-oriented metrics by avoiding Service Level Agreement (SLA)... 

Recent years witnessed a steep rise in data generation and, consequently, the widespread adoption of software solutions able to support data-intensive applications. Many companies currently engage in data-intensive processes, however, fully embracing a data-driven paradigm is still cumbersome, and establishing a production-ready and fine-tuned deployment is time-consuming. This situation calls for innovative models and techniques to streamline the process of deployment configuration for Big Data applications. Moreover, many companies are using Cloud deployed clusters, which represent a cost-effective alternative to installation on premises. Accurate and fast prediction of the execution time... 

Companies depend on mining data to grow their business more than ever. To achieve optimal performance of Big Data analytics workloads, a careful configuration of the cluster and the employed software framework is required. The lack of flexible and accurate performance models, however, render this a challenging task. This paper fills this gap by presenting accurate performance prediction models based on Stochastic Activity Networks (SANs). In contrast to existing work, the presented models consider multiple work queues, a critical feature to achieve high accuracy in realistic usage scenarios. We first introduce a monolithic analytical model for a multi-queue YARN cluster running DAG-based Big... 

This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare.... 

Stochastic activity networks (SANs) are a powerful and flexible extension of Petri nets. These models can be used for the modelling and analysis of various kinds and different aspects of distributed real-time systems. Similar to other classical extensions of Petri nets, SANs have some limitations for modelling complex and large-scale systems. In order to remove some of these limitations and provide high-level modelling constructs, we have defined a new extension for SANs, called hierarchical stochastic activity networks (HSANs). HSAN models provide a construct for composing a hierarchy of SAN submodels that is called macro activity. HSANs encapsulate hierarchies and a key benefit of these... 

This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare.... 

Infrastructure-as-a-Service (IaaS) clouds not only have to meet business requirements but also need to consider other important metrics that influence the quality of service, such as performance, availability, and power consumption. In this paper, we present a Stochastic Activity Network (SAN) based analytical approach that simultaneously computes these metrics under a given load for IaaS cloud data centers. The model's high-level abstraction of IaaS clouds allows us to evaluate different resource management strategies and features, including cloud federation and dispatching policies. In a first step, we model a single rack including its autonomous local manager responsible for scheduling...