The tradeoff between analyzability and expressiveness is a key factor when choosing a suitable dataflow model of computation (MoC) for designing, modeling, and simulating applications considering a formal base. A large number of techniques and analysis tools exist for static dataflow models, such as synchronous dataflow. However, they cannot express the dynamic behavior required for more dynamic applications in signal streaming or to model runtime reconfigurable systems. On the other hand, dynamic dataflow models like Kahn process networks sacrifice analyzability for expressiveness. Scenario-aware dataflow (SADF) is an excellent tradeoff providing sufficient expressiveness for dynamic systems, while still giving access to powerful analysis methods. In spite of an increasing interest in SADF methods, there is a lack of formally-defined functional models for describing and simulating SADF systems. This article overcomes the current situation by introducing a functional model for the SADF MoC, as well as a set of abstract operations for simulating it. We present the first modeling and simulation tool for SADF so far, implemented as an open source library in the functional framework ForSyDe. We demonstrate the capabilities of the functional model through a comprehensive tutorial-style example of a RISC processor described as an SADF application, and a traditional streaming application where we model an MPEG-4 simple profile decoder. We also present a couple of alternative approaches for functionally modeling SADF on different languages and paradigms. One of such approaches is used in a performance comparison with our functional model using the MPEG-4 simple profile decoder as a test case. As a result, our proposed model presented a good tradeoff between execution time and implementation succinctness. Finally, we discuss the potential of our formal model as a frontend for formal system design flows regarding dynamic applications.
Drones can play a game-changing role in reducing both cost and time in the context of last-mile deliveries. This paper addresses the last-mile delivery problem from a complex system viewpoint, where the collective performance of the drones is investigated. We consider a last-mile delivery system with a tradable permit model (TPM) for airspace use. Typically, in other research works regarding lastmile delivery drones, a fully cooperative centralized scenario is contemplated. In our approach, due to the TPM, the agents (i.e. drones) need to compete for airspace permits in a distributed manner. We simulate the system and evaluate how different parameters, such as the arrival rate and airspace dimensions, impact the system behavior in terms of the cost and time needed by the drones to acquire flight permits, and the airspace utilization. We use a simplified simulation model, where the agents' strategies are naïve, and the drones' flight dynamics are not accounted for. Nevertheless, the simulation's level of detail is adequate for capturing interesting properties from the agents' collective behavior, as our results support. The obtained results show that the system's performance is satisfactory, even with naïve agents and under high traffic conditions. Moreover, a real-world implementation of our competitive decentralized approach would lead to advantages, such as fast permit transactions, simple computational infrastructures, and error resilience.
Component-based software engineering offers a way to break complex systems into well-defined parts. Self-adaptive mechanisms are crucial to enable run-time reconfiguration and increase parts reuse in other computer systems and environments. These systems must satisfy functional and nonfunctional requirements. Despite efficient data integration being a common aspiration, the practicality of achieving interoperability remains a challenge for quickly transforming functional processes. For other components work together with the existing ones, and for the new system components development to operate seamlessly with and among other systems, while maintaining proprietary information integrity, the adoption of a common set of "building codes" is required. This paper proposes a self-adaptive framework for a real-time system through a scope analysis of stakeholders' requirement. It implements generic behavioral models for Systems Servers and Invokers. Changes on a statechart dimension while adapting a system to the framework lead software engineers to a nearly transparent integration process. Platform dependencies are also captured separately, enabling code-generation subsystem to reuse same components across a wide range of heterogeneous platforms and real-time systems. The framework can lead software components to high degrees of cost-effective reuse and it is tested in a real-time system prototype developed in the Brazilian Aeronautical Institute of Technology (Instituto Tecnológico de Aeronáutica -ITA). The proposed framework focused on self-adaptive services components at run-time and on an efficient interoperability approach. At the end, functional requirements and the software architectural structure are enforced such that the end-to-end timing behavior of the resulting system and its specifications can be verified.
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