Engineering Resilient Collective Adaptive Systems by Self-Stabilisation

Abstract

Collective adaptive systems are an emerging class of networked computational systems, particularly suited in application domains such as smart cities, complex sensor networks, and the Internet of Things. These systems tend to feature large scale, heterogeneity of communication model (including opportunistic peer-to-peer wireless interaction), and require inherent self-adaptiveness properties to address unforeseen changes in operating conditions. In this context, it is extremely difficult (if not seemingly intractable) to engineer reusable pieces of distributed behaviour so as to make them provably correct and smoothly composable.Building on the field calculus, a computational model (and associated toolchain) capturing the notion of aggregate network-level computation, we address this problem with an engineering methodology coupling formal theory and computer simulation. On the one hand, functional properties are addressed by identifying the largest-to-date field calculus fragment generating self-stabilising behaviour, guaranteed to eventually attain a correct and stable final state despite any transient perturbation in state or topology, and including highly reusable building blocks for information spreading, aggregation, and time evolution. On the other hand, dynamical properties are addressed by simulation, empirically evaluating the different performances that can be obtained by switching between implementations of building blocks with provably equivalent functional properties. Overall, our methodology sheds light on how to identify core building blocks of collective behaviour, and how to select implementations that improve system performance while leaving overall system function and resiliency properties unchanged.

Towards Adaptive Flow Programming for the IoT: The Fluidware Approach

“…The Fluidware approach will also require the definition of new conceptual abstractions to reason about complex IoT services and applications and their requirements. In addition, it will call for the identification of specific methodological guidelines to drive the design and development process, to be necessarily accompanied by Fluidware-specific tools to support the activities of the development process, and to provide correctness guarantees [14], [15], [16], [13].…”

“…To formalize the Fluidware operational model and implement its basic programming interface, we plan to undertake the following activities: (i) develop the operational model of funnel processes, to serve as a blueprint for implementation of the platform, for defining composition techniques, and to check well-formedness of specifications and properties-it will include development of a core calculus, operational semantics, and by-construction proofs of behaviour properties, e.g., in the style of [13]; and (ii) implement a library to provide the core mechanisms devised in the model, to specify and compose processes, as an interface towards the platform and existing simulators. We envisage the adoption of modern techniques to smoothly integrate with mainstream programming and functional-oriented declarative approaches.…”

On Distributed Runtime Verification by Aggregate Computing

“…The field calculus [17,31] is a minimal functional language that identifies basic constructs to manipulate fields, and whose operational semantics can act as blueprint for developing toolchains to design and deploy systems of possibly myriad devices interacting via proximity-based broadcasts. Recent works have also adopted this field calculus as a lingua franca to investigate formal properties of resiliency to environment changes [28,31], and to device distribution [12].…”

Guest Editorial for the Special Issue on FORmal methods for the quantitative Evaluation of Collective Adaptive SysTems (FORECAST)

“…The article by Viroli et al [12] presents an approach to aggregate computing based on field calculus (and associated toolchain) as computational model. Aggregate computing supports the design of complex and large-scale software systems by focusing on the global behavior of a collection of devices, thus abstracting away from their individual behavior.…”