Smart Contract Languages: A Multivocal Mapping Study

Blockchain is a disruptive technology that has attracted the attention of the scientific community and compa nies, as proven by the exponential growth of publications on this topic in recent years. This growing interest is mainly due to the promise that the use of blockchain enables it to be verified, without including any trusted intermediaries, that the information received from the network is authentic and up-to-date. In this respect, blockchain is a distributed database that can be seen as a ledger that records all transactions that have ever been executed. In this context, smart contracts are pieces of software used to facilitate, verify, and enforce the negotiation of a transaction on a blockchain platform. These pieces of software are implemented by using programming languages, which are sometimes provided by the blockchain platforms themselves. This study aims to (1) identify and categorise the state-of-the-art related to smart contract languages, in terms of the existing languages and their main features, and (2) identify new research opportunities. The review has been conducted as a multivocal mapping study that followsthe guidelines proposed by Garousi et al. for conducting multivocal literature reviews, as well as the guidelines proposed by Kitchenham and Charters for conducting mapping studies. As a result of the implementation of the review protocol, 4,119 papers were gathered, and 109 of them were selected for extraction. The contributions of this article are twofold: (1) 101 different smart contract languages have been identified and classified according to a variety of criteria; (2) a discussion on the findings and their implications for future research have been outlined. As a conclusion, it could be stated that a rigorous and replicable overview of the state-of-the-art of smart contract languages has been provided that can benefit not only researchers but also practitioners in the field, thanks to its multivocal nature.Ministerio de Ciencia y Tecnología RTI2018-094283-B-C33 (ECLIPSE)Junta de Andalucía COPERNICA (P20-01224)Junta de Andalucía METAMORFOSIS (US-1381375

Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives

Collectiveness is an important property of many systems--both natural and artificial. By exploiting a large number of individuals, it is often possible to produce effects that go far beyond the capabilities of the smartest individuals, or even to produce intelligent collective behaviour out of not-so-intelligent individuals. Indeed, collective intelligence, namely the capability of a group to act collectively in a seemingly intelligent way, is increasingly often a design goal of engineered computational systems--motivated by recent techno-scientific trends like the Internet of Things, swarm robotics, and crowd computing, just to name a few. For several years, the collective intelligence observed in natural and artificial systems has served as a source of inspiration for engineering ideas, models, and mechanisms. Today, artificial and computational collective intelligence are recognised research topics, spanning various techniques, kinds of target systems, and application domains. However, there is still a lot of fragmentation in the research panorama of the topic within computer science, and the verticality of most communities and contributions makes it difficult to extract the core underlying ideas and frames of reference. The challenge is to identify, place in a common structure, and ultimately connect the different areas and methods addressing intelligent collectives. To address this gap, this paper considers a set of broad scoping questions providing a map of collective intelligence research, mostly by the point of view of computer scientists and engineers. Accordingly, it covers preliminary notions, fundamental concepts, and the main research perspectives, identifying opportunities and challenges for researchers on artificial and computational collective intelligence engineering.Comment: This is the author's final version of the article, accepted for publication in the Artificial Life journal. Data: 34 pages, 2 figure

IntegraDos: facilitating the adoption of the Internet of Things through the integration of technologies

También, han sido analizados los componentes para una integración del IoT y cloud computing, concluyendo en la arquitectura Lambda-CoAP. Y por último, los desafíos para una integración del IoT y Blockchain han sido analizados junto con una evaluación de las posibilidades de los dispositivos del IoT para incorporar nodos de Blockchain. Las contribuciones de esta tesis doctoral contribuyen a acercar la adopción del IoT en la sociedad, y por tanto, a la expansión de esta prominente tecnología. Fecha de lectura de Tesis: 17 de diciembre 2018.El Internet de las Cosas (IoT) fue un nuevo concepto introducido por K. Asthon en 1999 para referirse a un conjunto identificable de objetos conectados a través de RFID. Actualmente, el IoT se caracteriza por ser una tecnología ubicua que está presente en un gran número de áreas, como puede ser la monitorización de infraestructuras críticas, sistemas de trazabilidad o sistemas asistidos para el cuidado de la salud. El IoT está cada vez más presente en nuestro día a día, cubriendo un gran abanico de posibilidades con el fin de optimizar los procesos y problemas a los que se enfrenta la sociedad. Es por ello por lo que el IoT es una tecnología prometedora que está continuamente evolucionando gracias a la continua investigación y el gran número de dispositivos, sistemas y componentes emergidos cada día. Sin embargo, los dispositivos involucrados en el IoT se corresponden normalmente con dispositivos embebidos con limitaciones de almacenamiento y procesamiento, así como restricciones de memoria y potencia. Además, el número de objetos o dispositivos conectados a Internet contiene grandes previsiones de crecimiento para los próximos años, con unas expectativas de 500 miles de millones de objetos conectados para 2030. Por lo tanto, para dar cabida a despliegues globales del IoT, además de suplir las limitaciones que existen, es necesario involucrar nuevos sistemas y paradigmas que faciliten la adopción de este campo. El principal objetivo de esta tesis doctoral, conocida como IntegraDos, es facilitar la adopción del IoT a través de la integración con una serie de tecnologías. Por un lado, ha sido abordado cómo puede ser facilitada la gestión de sensores y actuadores en dispositivos físicos sin tener que acceder y programar las placas de desarrollo. Por otro lado, un sistema para programar aplicaciones del IoT portables, adaptables, personalizadas y desacopladas de los dispositivos ha sido definido

A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems

We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from k diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called aggregate computing, specifically designed to directly program the global behaviour of a whole ensemble of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall

Engineering Self-Adaptive Collective Processes for Cyber-Physical Ecosystems

The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. However, the scale, density, heterogeneity, interdependence, and QoS constraints of many target systems pose severe operational and engineering challenges. Beyond individual smart devices, cyber-physical collectives can provide services or solve complex problems by leveraging a “system effect” while coordinating and adapting to context or environment change. Understanding and building systems exhibiting collective intelligence and autonomic capabilities represent a prominent research goal, partly covered, e.g., by the field of collective adaptive systems. Therefore, drawing inspiration from and building on the long-time research activity on coordination, multi-agent systems, autonomic/self-* systems, spatial computing, and especially on the recent aggregate computing paradigm, this thesis investigates concepts, methods, and tools for the engineering of possibly large-scale, heterogeneous ensembles of situated components that should be able to operate, adapt and self-organise in a decentralised fashion. The primary contribution of this thesis consists of four main parts. First, we define and implement an aggregate programming language (ScaFi), internal to the mainstream Scala programming language, for describing collective adaptive behaviour, based on field calculi. Second, we conceive of a “dynamic collective computation” abstraction, also called aggregate process, formalised by an extension to the field calculus, and implemented in ScaFi. Third, we characterise and provide a proof-of-concept implementation of a middleware for aggregate computing that enables the development of aggregate systems according to multiple architectural styles. Fourth, we apply and evaluate aggregate computing techniques to edge computing scenarios, and characterise a design pattern, called Self-organising Coordination Regions (SCR), that supports adjustable, decentralised decision-making and activity in dynamic environments.Con lo sviluppo di informatica e intelligenza artificiale, la diffusione pervasiva di device computazionali e la crescente interconnessione tra elementi fisici e digitali, emergono innumerevoli opportunità per la costruzione di sistemi socio-tecnici di nuova generazione. Tuttavia, l'ingegneria di tali sistemi presenta notevoli sfide, data la loro complessità—si pensi ai livelli, scale, eterogeneità, e interdipendenze coinvolti. Oltre a dispositivi smart individuali, collettivi cyber-fisici possono fornire servizi o risolvere problemi complessi con un “effetto sistema” che emerge dalla coordinazione e l'adattamento di componenti fra loro, l'ambiente e il contesto. Comprendere e costruire sistemi in grado di esibire intelligenza collettiva e capacità autonomiche è un importante problema di ricerca studiato, ad esempio, nel campo dei sistemi collettivi adattativi. Perciò, traendo ispirazione e partendo dall'attività di ricerca su coordinazione, sistemi multiagente e self-*, modelli di computazione spazio-temporali e, specialmente, sul recente paradigma di programmazione aggregata, questa tesi tratta concetti, metodi, e strumenti per l'ingegneria di ensemble di elementi situati eterogenei che devono essere in grado di lavorare, adattarsi, e auto-organizzarsi in modo decentralizzato. Il contributo di questa tesi consiste in quattro parti principali. In primo luogo, viene definito e implementato un linguaggio di programmazione aggregata (ScaFi), interno al linguaggio Scala, per descrivere comportamenti collettivi e adattativi secondo l'approccio dei campi computazionali. In secondo luogo, si propone e caratterizza l'astrazione di processo aggregato per rappresentare computazioni collettive dinamiche concorrenti, formalizzata come estensione al field calculus e implementata in ScaFi. Inoltre, si analizza e implementa un prototipo di middleware per sistemi aggregati, in grado di supportare più stili architetturali. Infine, si applicano e valutano tecniche di programmazione aggregata in scenari di edge computing, e si propone un pattern, Self-Organising Coordination Regions, per supportare, in modo decentralizzato, attività decisionali e di regolazione in ambienti dinamici

From distributed coordination to field calculus and aggregate computing

open6siThis work has been partially supported by: EU Horizon 2020 project HyVar (www.hyvar-project .eu), GA No. 644298; ICT COST Action IC1402 ARVI (www.cost -arvi .eu); Ateneo/CSP D16D15000360005 project RunVar (runvar-project.di.unito.it).Aggregate computing is an emerging approach to the engineering of complex coordination for distributed systems, based on viewing system interactions in terms of information propagating through collectives of devices, rather than in terms of individual devices and their interaction with their peers and environment. The foundation of this approach is the distillation of a number of prior approaches, both formal and pragmatic, proposed under the umbrella of field-based coordination, and culminating into the field calculus, a universal functional programming model for the specification and composition of collective behaviours with equivalent local and aggregate semantics. This foundation has been elaborated into a layered approach to engineering coordination of complex distributed systems, building up to pragmatic applications through intermediate layers encompassing reusable libraries of program components. Furthermore, some of these components are formally shown to satisfy formal properties like self-stabilisation, which transfer to whole application services by functional composition. In this survey, we trace the development and antecedents of field calculus, review the field calculus itself and the current state of aggregate computing theory and practice, and discuss a roadmap of current research directions with implications for the development of a broad range of distributed systems.embargoed_20210910Viroli, Mirko; Beal, Jacob; Damiani, Ferruccio; Audrito, Giorgio; Casadei, Roberto; Pianini, DaniloViroli, Mirko; Beal, Jacob; Damiani, Ferruccio; Audrito, Giorgio; Casadei, Roberto; Pianini, Danil