Through field calculus constructs and building-block APIs, aggregate programming could help unlock the IoT's true potential by allowing complex distributed services to be specified succinctly and by enabling such services to be safely encapsulated, modulated, and composed with one another.

Journal of Simulation (JOS) publishes articles, technical notes, case studies and tutorials in the field of simulation, with a particular focus on the applications of simulation and modelling. Journal of Simulation is an official journal of the OR Society.

Collective adaptive systems are an emerging class of networked computational systems particularly suited for 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 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.

The notion of a computational field has been proposed as a unifying abstraction for developing distributed systems, focusing on the computations and coordination of aggregates of devices instead of individual behavior. Prior field-based languages, however, have suffered from a number of practical limitations that have posed barriers to adoption and use. We address these limitations by introduction of Protelis, a functional language based on computational fields and embedded in Java, thereby enabling the construction of widely reusable components of aggregate systems. We demonstrate the simplicity of Protelis integration and programming through two examples: simulation of a pervasive computing scenario in the Alchemist simulator [24], and coordinated management of a network of services.

Pervasive computing systems can be modelled effectively as populations of interacting autonomous components. The key challenge to realizing such models is in getting separately-specified and -developed sub-systems to discover and interoperate with each other in an open and extensible way, supported by appropriate middleware services. In this paper, we argue that nature-inspired coordination models offer a promising way of addressing this challenge. We first frame the various dimensions along which nature-inspired coordination models can be defined, and survey the most relevant proposals in the area. We describe the nature-inspired coordination model developed within the SAPERE project as a synthesis of existing approaches, and show how it can effectively support the multifold requirements of modern and emerging pervasive services. We conclude by identifying what we think are the open research challenges in this area, and identify some research directions that we believe are promising.PostprintPeer reviewe