Programming the Interactions of Collective Adaptive Systems by Relying on Attribute-based Communication

Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and interdependent, and are operating in dynamic and possibly unpredictable environments. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavour. In this article we propose a language-based approach for programming the interactions of collective-adaptive systems by relying on attribute-based communication; a paradigm that permits a group of partners to communicate by considering their run-time properties and capabilities. We introduce AbC, a foundational calculus for attribute-based communication and show how its linguistic primitives can be used to program a complex and sophisticated variant of the well-known problem of Stable Allocation in Content Delivery Networks. Also other interesting case studies, from the realm of collective-adaptive systems, are considered. We also illustrate the expressive power of attribute-based communication by showing the natural encoding of other existing communication paradigms into AbC

Programming interactions in collective adaptive systems by relying on attribute-based communication

Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and interdependent, and are operating in dynamic and possibly unpredictable environments. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavour. In this article we propose a language-based approach for programming the interactions of collective-adaptive systems by relying on attribute-based communication; a paradigm that permits a group of partners to communicate by considering their run-time properties and capabilities. We introduce AbC, a foundational calculus for attribute-based communication and show how its linguistic primitives can be used to program a sophisticated variant of the well-known problem of Stable Allocation in Content Delivery Networks. In our variant, content providers are assigned to clients based on collaboration and by taking into account the preferences of both parties in a fully anonymous and distributed settings. We also illustrate the expressive power of attribute-based communication by showing the natural encoding of group-based, publish/subscribe-based and channel-based communication paradigms into AbC

Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

A distributed API for coordinating AbC programs

Collective adaptive systems exhibit a particular notion of interaction where environmental conditions largely influence interactions. Previously, we proposed a calculus, named AbC, to model and reason about CAS. The calculus proved to be effective by naturally modelling essential CAS features. However, the question on the tradeoff between its expressiveness and its efficiency, when implemented to program CAS applications, is to be answered. In this article, we propose an efficient and distributed coordination infrastructure for AbC. We prove its correctness, and we evaluate its performance. The main novelty of our approach is that AbC components are infrastructure agnostic. Thus the code of a component does not specify how messages are routed in the infrastructure but rather what properties a target component must satisfy. We also developed a Go API, named GoAt, and an Eclipse plugin to program in a high-level syntax which can be automatically used to generate matching Go code. We showcase our development through a non-trivial case study

A Behavioural Theory for Interactions in Collective-Adaptive Systems

We propose a process calculus, named AbC, to study the behavioural theory of interactions in collective-adaptive systems by relying on attribute-based communication. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interaction among components is dynamically established by taking into account "connections" as determined by predicates over their attributes. The structural operational semantics of AbC is based on Labeled Transition Systems that are also used to define bisimilarity between components. Labeled bisimilarity is in full agreement with a barbed congruence, defined by simple basic observables and context closure. The introduced equivalence is used to study the expressiveness of AbC in terms of encoding broadcast channel-based interactions and to establish formal relationships between system descriptions at different levels of abstraction

Genetic Programming for Smart Phone Personalisation

Personalisation in smart phones requires adaptability to dynamic context based on user mobility, application usage and sensor inputs. Current personalisation approaches, which rely on static logic that is developed a priori, do not provide sufficient adaptability to dynamic and unexpected context. This paper proposes genetic programming (GP), which can evolve program logic in realtime, as an online learning method to deal with the highly dynamic context in smart phone personalisation. We introduce the concept of collaborative smart phone personalisation through the GP Island Model, in order to exploit shared context among co-located phone users and reduce convergence time. We implement these concepts on real smartphones to demonstrate the capability of personalisation through GP and to explore the benefits of the Island Model. Our empirical evaluations on two example applications confirm that the Island Model can reduce convergence time by up to two-thirds over standalone GP personalisation.Comment: 43 pages, 11 figure

On Expressiveness and Behavioural Theory of Attribute-based Communication

Attribute-based communication is an interesting alternative to broadcast and binary communication when providing abstract models for the so called Collective Adaptive Systems which consist of a large number of interacting components that dynamically adjust and combine their behavior to achieve specifc goals. A basic process calculus, named AbC, is introduced whose primary primitive for interaction is attribute-based communication. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interactions among components are dynamically established by taking into account\connections" as determined by predicates over the attributes exposed by components. First, the syntax and the semantics of AbC are presented, then expressiveness and effectiveness of the calculus are demonstrated both in terms of the ability to model scenarios featuring collaboration, reconfiguration, and adaptation and of the possibility of encoding a process calculus for broadcasting channel-based communication and other communication paradigms. Behavioral equivalences for AbC are introduced for establishing formal relationships between different descriptions of the same system

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA

The AbU Language: IoT Distributed Programming Made Easy

Event-driven programming based on Event-Condition-Action (ECA) rules allows users to define complex automation routines in a simple, declarative way; for this reason, in recent years ECA rules have been adopted by the majority of companies in the Internet of Things (IoT) industry as a promising paradigm for implementing ubiquitous and pervasive systems. Unfortunately, programming simplicity comes to a price: most implementations of ECA rules are bound to a strongly centralized communication infrastructure, that poses serious limitations on the application scenarios for the IoT, due to scalability, security and availability issues. To mitigate these issues, recent works introduced abstractions for communication and coordination of ensembles of IoT devices in a decentralized setting, effectively moving the computation towards the edge of the network without sacrificing the programming simplicity prerogative of ECA rules. In particular, Attribute-based memory Updates is a communication model transparently enhancing ECA rules-based systems with an interaction mechanism where communication is similar to broadcast but actual receivers are selected on the spot, by means of predicates (i.e., properties) over devices attributes. In this paper, we introduce AbU-dsl, a Domain Specific Language for the IoT that compiles on top of an implementation of Attribute-based memory Updates. In this way, AbU-dsl provides a practical development interface, based on ECA rules, to effectively program IoT devices in a fully decentralized setting, by exploiting a full-fledged attribute-based interaction model. Thus, programmers can specify interactions between devices in a declarative way, abstracting from details such as devices identity, number, or even their existence, without the need for a central controlling service