UML class diagrams supporting formalism definition in the Draw-Net Modeling System

The Draw-Net Modeling System (DMS) is a customizable framework supporting the design and the solution of models expressed in any graph-based formalism, thanks to an open architecture. During the years, many formalisms (Petri Nets, Bayesian Networks, Fault Trees, etc.) have been included in DMS. A formalism defines all the primitives that can be used in a model (nodes, arcs, properties, etc.) and is stored into XML files. The paper describes a new way to manage formalisms: the user can create a new formalism by drawing a UML Class Diagrams (CD); then the corresponding XML files are automatically generated. If instead the user intends to edit an existing formalism, a "reverse engineering" function generates the CD from the XML files. The CD can be handled inside DMS, and acts an intuitive and graphical "meta-model" to represent the formalism. An application example is presented

The GreatSPN tool: recent enhancements

GreatSPN is a tool that supports the design and the qualitative and quantitative analysis of Generalized Stochastic Petri Nets (GSPN) and of Stochastic Well-Formed Nets (SWN). The very first version of GreatSPN saw the light in the late eighties of last century: since then two main releases where developed and widely distributed to the research community: GreatSPN1.7 [13], and GreatSPN2.0 [8]. This paper reviews the main functionalities of GreatSPN2.0 and presents some recently added features that significantly enhance the efficacy of the tool

List of requirements on formalisms and selection of appropriate tools

This deliverable reports on the activities for the set-up of the modelling environments for the evaluation activities of WP5. To this objective, it reports on the identified modelling peculiarities of the electric power infrastructure and the information infrastructures and of their interdependencies, recalls the tools that have been considered and concentrates on the tools that are, and will be, used in the project: DrawNET, DEEM and EPSys which have been developed before and during the project by the partners, and M\uf6bius and PRISM, developed respectively at the University of Illinois at Urbana Champaign and at the University of Birmingham (and recently at the University of Oxford)

Interactive Execution Monitoring of Agent Teams

There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10 percent of alerts are unwanted, as judged by domain experts)

Extended Fault Trees Analysis supported by Stochastic Petri Nets

This work presents several extensions to the Fault Tree [90] formalism used to build models oriented to the Dependability [103] analysis of systems. In this way, we increment the modelling capacity of Fault Trees which turn from simple combinatorial models to an high level language to represent more complicated aspects of the behaviour and of the failure mode of systems. Together with the extensions to the Fault Tree formalism, this work proposes solution methods for extended Fault Trees in order to cope with the new modelling facilities. These methods are mainly based on the use of Stochastic Petri Nets. Some of the formalisms described in this work are already present in the literature; for them we propose alternative solution methods with respect to the existing ones. Other formalisms are instead part of the original contribution of this work

Event-Driven Network Programming

Software-defined networking (SDN) programs must simultaneously describe static forwarding behavior and dynamic updates in response to events. Event-driven updates are critical to get right, but difficult to implement correctly due to the high degree of concurrency in networks. Existing SDN platforms offer weak guarantees that can break application invariants, leading to problems such as dropped packets, degraded performance, security violations, etc. This paper introduces EVENT-DRIVEN CONSISTENT UPDATES that are guaranteed to preserve well-defined behaviors when transitioning between configurations in response to events. We propose NETWORK EVENT STRUCTURES (NESs) to model constraints on updates, such as which events can be enabled simultaneously and causal dependencies between events. We define an extension of the NetKAT language with mutable state, give semantics to stateful programs using NESs, and discuss provably-correct strategies for implementing NESs in SDNs. Finally, we evaluate our approach empirically, demonstrating that it gives well-defined consistency guarantees while avoiding expensive synchronization and packet buffering