In cyber-physical systems like automotive systems, there are components like sensors, actuators, and controllers that communicate asynchronously with each other. The computational model of actor supports modeling distributed asynchronously communicating systems. We propose Hybrid Rebeca language to support modeling of cyber-physical systems. Hybrid Rebeca is an extension of actor-based language Rebeca. In this extension, physical actors are introduced as new computational entities to encapsulate physical behaviors. To support various means of communication among the entities, the network is explicitly modeled as a separate entity from actors. We derive hybrid automata as the basis for analysis of Hybrid Rebeca models. We demonstrate the applicability of our approach through a case study in the domain of automotive systems. We use SpaceEx framework for the analysis of the case study. 

Programming time-critical systems is notoriously difficult. In this paper we propose an actor-oriented programming model with a semantic notion of time and a deterministic coordination semantics based on discrete events to exercise precise control over both the computational and timing aspects of the system behavior.

Assessing the impacts of a mobility initiative prior to deployment is a complex task for both urban planners and transport companies. Computational models like Tangramob offer an agent-based framework for simulating the evolution of urban traffic after the introduction of new mobility services. However, simulations can be computationally expensive to perform due to their iterative nature and the microscopic representation of traffic. To address this issue, we designed a simplified model architecture of Tangramob in Timed Rebeca (TRebeca) and we developed a tool-chain for the generation runnable instances of this model starting from the same input files of Tangramob. Running TRebeca models allows users to get an idea of how the mobility initiatives under study affect the traveling experience of commuters, in a short time and without the need to use the simulator during this first experimental step. Then, once a subset of these initiatives is identified according to user's criteria, it is reasonable to simulate them with Tangramob in order to get more detailed results. To validate this approach, we compared the output of both the simulator and the TRebeca model on a collection of mobility initiatives. The correlation between the results demonstrates the usefulness of using TRebeca models for unconventional contexts of application.

NP-hard time complexity of model checking algorithms for TCTL properties in dense time is one of the obstacles against using model checking for the analysis of real-time systems. Alternatively, a polynomial time algorithm is suggested for model checking of discrete time models against TCTL≤,≥ properties (i.e. TCTL properties without U=c modalities). The algorithm performs model checking against a given formula Φ for a state space with V states and E transitions in O(V(V+E)⋅|Φ|). In this work, we improve the model checking algorithm of TCTL≤,≥ properties, obtaining time complexity of O((Vlg⁡V+E)⋅|Φ|). We tackle the model checking of discrete timed actors as an application of the proposed algorithms. We show how the result of the fine-grained semantics of discrete timed actors can be model checked efficiently against TCTL≤,≥ properties using the proposed algorithm. This is illustrated using the timed actor modeling language Timed Rebeca. In addition to introducing a new efficient model checking algorithm, we propose a reduction technique which safely eliminates instantaneous transitions of transition systems (i.e. transition with zero time duration). We show that the reduction can be applied on-the-fly during the generation of the original timed transition system without a significant cost. We demonstrate the effectiveness of the reduction technique via a set of case studies selected from various application domains. Besides, while TCTL≤,≥ can be model checked in polynomial time, model checking of TCTL properties with U=c modalities is an NP-complete problem. Using the proposed reduction technique, we provide an efficient algorithm for model checking of complete TCTL properties over the reduced transition systems.

Self-adaptation is a well-known technique to handle growing complexities of software systems, where a system autonomously adapts itself in response to changes in a dynamic and unpredictable environment. With the increasing need for developing self-adaptive systems, providing a model and an implementation platform to facilitate integration of adaptation mechanisms into the systems and assuring their safety and quality is crucial. In this paper, we target Track-based Traffic Control Systems (TTCSs) in which the traffic flows through pre-specified sub-tracks and is coordinated by a traffic controller. We introduce a coordinated actor model to design self-adaptive TTCSs and provide a general mapping between various TTCSs and the coordinated actor model. The coordinated actor model is extended to build large-scale self-adaptive TTCSs in a decentralized setting. We also discuss the benefits of using Ptolemy II as a framework for model-based development of large-scale self-adaptive systems that supports designing multiple hierarchical MAPE-K feedback loops interacting with each other. We propose a template based on the coordinated actor model to design a self-adaptive TTCS in Ptolemy II that can be instantiated for various TTCSs. We enhance the proposed template with a predictive adaptation feature. We illustrate applicability of the coordinated actor model and consequently the proposed template by designing two real-life case studies in the domains of air traffic control systems and railway traffic control systems in Ptolemy II. 

Understanding the impacts of a mobility initiative prior to deployment is a complex task for both urban planners and transport companies. To support this task, Tangramob offers an agent-based simulation framework for assessing the evolution of urban traffic after the introduction of new mobility services. However, Tangramob simulations are computationally expensive due to their iterative nature. Thus, we simplified the Tangramob model into a Timed Rebeca (TRebeca) model and we designed a tool-chain that generates instances of this model starting from the same Tangramob’s inputs. Running TRebeca models allows users to get an idea of how mobility initiatives affect the system performance, in a short time, without resorting to the simulator. To validate this approach, we compared the output of both the simulator and the TRebeca model on a collection of mobility initiatives. Results show a correlation between them, thus demonstrating the usefulness of using TRebeca models for unconventional contexts of application.

Programmers often use informal worst-case analysis and debugging to ensure that schedulers satisfy real-time requirements. Not only can this process be tedious and error-prone, it is inherently conservative and thus likely to lead to an inefficient use of resources. We propose to use model checking to find a schedule which optimizes the use of resources while satisfying real-time requirements. Specifically, we represent a Wireless sensor and actuator network (WSAN) as a collection of actors whose behaviors are specified using a Java-based actor language extended with operators for real-time scheduling and delay representation. We show how the abstraction mechanism and the compositionality of actors in the actor model may be used to incrementally build a model of a WSAN's behavior from node-level and network models. We demonstrate the approach with a case study of a distributed real-time data acquisition system for high-frequency sensing using Timed Rebeca modeling language and the Afra model checking tool.

Expressive power of a language is generally defined as the breadth of ideas that can be represented and communicated in a language. For formal languages, the expressive power has been evaluated by checking its Turing completeness. In a modeling process, apart from the modeling language, we have two other counterparts: the system being modeled and the modeler. I argue that faithfulness to the system being modeled and usability for the modeler are at least as important as the expressive power of the modeling language, specially because most of the modeling languages used today are highly expressive. I call faithfulness and usability together “friendliness”. I show how we used the actor-based language Rebeca in modeling different applications, where it is friendly, and where it is not. I discuss how the friendliness of Rebeca may help in the analysis of models and allows for system synthesis on the basis of models.