Danilo Pianini

Roberto Casadei, Stefano Mariani, Danilo Pianini et al.

A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes. Especially in large-scale settings, the problem can be addressed through decentralised and situated computing systems: nodes can locally sense, process, and act upon signals, and coordinate with neighbours to implement collective strategies. Accordingly, in this work we devise distributed coordination strategies for the estimation of a spatial phenomenon through collaborative adaptive sampling. Our design is based on the idea of dynamically partitioning space into regions that compete and grow/shrink to provide accurate aggregate sampling. Such regions hence define a sort of virtualised space that is "fluid", since its structure adapts in response to pressure forces exerted by the underlying phenomenon. We provide an adaptive sampling algorithm in the field-based coordination framework, and prove it is self-stabilising and locally optimal. Finally, we verify by simulation that the proposed algorithm effectively carries out a spatially adaptive sampling while maintaining a tuneable trade-off between accuracy and efficiency.

Martina Baiardi, Samuele Burattini, Giovanni Ciatto et al.

Multi-agent systems are designed to deal with open, distributed systems with unpredictable dynamics, which makes them inherently hard to test. The value of using simulation for this purpose is recognized in the literature, although achieving sufficient fidelity (i.e., the degree of similarity between the simulation and the real-world system) remains a challenging task. This is exacerbated when dealing with cognitive agent models, such as the Belief Desire Intention (BDI) model, where the agent codebase is not suitable to run unchanged in simulation environments, thus increasing the reality gap between the deployed and simulated systems. We argue that BDI developers should be able to test in simulation the same specification that will be later deployed, with no surrogate representations. Thus, in this paper, we discuss how the control flow of BDI agents can be mapped onto a Discrete Event Simulation (DES), showing that such integration is possible at different degrees of granularity. We substantiate our claims by producing an open-source prototype integration between two pre-existing tools (JaKtA and Alchemist), showing that it is possible to produce a simulation-based testing environment for distributed BDI} agents, and that different granularities in mapping BDI agents over DESs may lead to different degrees of fidelity.

Roberto Casadei, Gianluca Aguzzi, Giorgio Audrito et al.

Today's distributed and pervasive computing addresses large-scale cyber-physical ecosystems, characterised by dense and large networks of devices capable of computation, communication and interaction with the environment and people. While most research focusses on treating these systems as "composites" (i.e., heterogeneous functional complexes), recent developments in fields such as self-organising systems and swarm robotics have opened up a complementary perspective: treating systems as "collectives" (i.e., uniform, collaborative, and self-organising groups of entities). This article explores the motivations, state of the art, and implications of this "collective computing paradigm" in software engineering, discusses its peculiar challenges, and outlines a path for future research, touching on aspects such as macroprogramming, collective intelligence, self-adaptive middleware, learning, synthesis, and experimentation of collective behaviour.

Danilo Pianini, Guido Salvaneschi

The 1st workshop on Architectures, Languages and Paradigms for IoT (ALP4IoT 2017), was held in Turin on September 19th, 2017. ALP4IoT was a satellite event of the 13th International Conference on integrated Formal Methods (iFM 2017). The workshop aimed at critically reviewing the state-of-the-art and the state-of-the-practice of formal techniques and software methods for the IoT, presenting open problems and challenges and triggering a discussion among the participants with different views and backgrounds. The Internet of Things is ushering a dramatic increase in number and variety of interconnected and smart objects. Communication capabilities and computational power are growingly embedded in everyday devices, including personal smart devices, public displays, cars, drones, and electronic tags. This state of the things opens an unprecedented range of research opportunities: the inherent distribution, mobility, situatedness, and heterogeneity of such devices call for proper scientific understanding of the foundations of such systems as well as for novel software methods. The workshop solicited original contributions on architectures, languages, paradigms, and techniques with potential practical and theoretical impact on software systems targeting the IoT, welcoming inter-disciplinary approaches.