Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2016 | Book

Formal Specification and Analysis of Robust Adaptive Distributed Cyber-Physical Systems Read chapter Read first chapter

Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems

16th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2016, Bertinoro, Italy, June 20-24, 2016, Advanced Lectures

Editors: Marco Bernardo, Rocco De Nicola, Jane Hillston

Publisher: Springer International Publishing

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

This book presents 8 tutorial lectures given by leading researchers at the 16th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2016, held in Bertinoro, Italy, in June 2016.
SFM 2016 was devoted to the Quantitative Evaluation of Collective Adaptive Systems and covered topics such as self-organization in distributed systems, scalable quantitative analysis, spatio-temporal models, and aggregate programming.

Table of Contents

Frontmatter
Formal Specification and Analysis of Robust Adaptive Distributed Cyber-Physical Systems
Abstract
We are interested in systems of cyber-physical agents that operate in unpredictable, possibly hostile, environments using locally obtainable information. How can we specify robust agents that are able to operate alone and/or in cooperation with other agents? What properties are important? How can they be verified?
In this tutorial we describe a framework called Soft Agents, formalized in the Maude rewriting logic system. Features of the framework include: explicit representation of the physical state as well as the cyber perception of this state; robust communication via sharing of partially ordered knowledge, and robust behavior based on soft constraints. Using Maude functionality, the soft agent framework supports experimenting with, formally testing, and reasoning about specifications of agent systems.
The tutorial begins with a discussion of desiderata for soft agent models. Use of the soft agent framework for specification and formal analysis of agent systems illustrated in some detail by a case-study involving simple patrolling bots. A more complex case study involving surveillance drones is also discussed.
Carolyn Talcott, Vivek Nigam, Farhad Arbab, Tobias Kappé
Dependability of Adaptable and Evolvable Distributed Systems
Abstract
This article is a tutorial on how to achieve software evolution and adaptation in a dependable manner, by systematically applying formal modelling and verification. It shows how software can be designed upfront to tolerate different sources of uncertainty that cause continuous future changes. If possible changes can be predicted, and their occurrence can be detected, it is possible to design the software to be self-adaptable. Otherwise, continuous evolution has to be supported and continuous flow into operation has to be ensured. In cases where systems are designed to be continuously running, it is necessary to support safe continuous software deployment that guarantees correct operation in the presence of dynamic reconfigurations. The approaches we survey here have been mainly developed in the context of the SMScom project, funded by the European Commission –Programme IDEAS-ERC (http://​erc-smscom.​dei.​polimi.​it/​.) – and lead by the author. It is argued that these approaches fit well the current agile methods for development and operations that are popularized as DevOps.
Carlo Ghezzi
Mean-Field Limits Beyond Ordinary Differential Equations
Abstract
We study the limiting behaviour of stochastic models of populations of interacting agents, as the number of agents goes to infinity. Classical mean-field results have established that this limiting behaviour is described by an ordinary differential equation (ODE) under two conditions: (1) that the dynamics is smooth; and (2) that the population is composed of a finite number of homogeneous sub-populations, each containing a large number of agents. This paper reviews recent work showing what happens if these conditions do not hold. In these cases, it is still possible to exhibit a limiting regime at the price of replacing the ODE by a more complex dynamical system. In the case of non-smooth or uncertain dynamics, the limiting regime is given by a differential inclusion. In the case of multiple population scales, the ODE is replaced by a stochastic hybrid automaton.
Luca Bortolussi, Nicolas Gast
Modelling and Analysis of Collective Adaptive Systems with CARMA and its Tools
Abstract
Collective Adaptive Systems (CAS) are heterogeneous collections of autonomous task-oriented systems that cooperate on common goals forming a collective system. This class of systems is typically composed of a huge number of interacting agents that dynamically adjust and combine their behaviour to achieve specific goals.
This chapter presents Carma, a language recently defined to support specification and analysis of collective adaptive systems, and its tools developed for supporting system design and analysis. Carma is equipped with linguistic constructs specifically developed for modelling and programming systems that can operate in open-ended and unpredictable environments. The chapter also presents the Carma Eclipse plug-in that allows Carma models to be specified by means of an appropriate high-level language. Finally, we show how Carma and its tools can be used to support specification with a simple but illustrative example of a socio-technical collective adaptive system.
Michele Loreti, Jane Hillston
Spatial Representations and Analysis Techniques
Abstract
Space plays an important role in the dynamics of collective adaptive systems (CAS). There are choices between representations to be made when we model these systems with space included explicitly, rather than being abstracted away. Since CAS often involve a large number of agents or components, we focus on scalable modelling and analysis of these models, which may involve approximation techniques. Discrete and continuous space are considered, for both models of individuals and models of populations. The aim of this tutorial is to provide an overview that supports decisions in modelling systems that involve space.
Vashti Galpin
Spatial Logic and Spatial Model Checking for Closure Spaces
Abstract
Spatial aspects of computation are increasingly relevant in Computer Science, especially in the field of collective adaptive systems and when dealing with systems distributed in physical space. Traditional formal verification techniques are well suited to analyse the temporal evolution of concurrent systems; however, properties of space are typically not explicitly taken into account. This tutorial provides an introduction to recent work on a topology-inspired approach to formal verification of spatial properties depending upon (physical) space. A logic is presented, stemming from the tradition of topological interpretations of modal logics, dating back to earlier logicians such as Tarski, where modalities describe neighbourhood. These topological definitions are lifted to the more general setting of closure spaces, also encompassing discrete, graph-based structures. The present tutorial illustrates the extension of the framework with a spatial surrounded operator, leading to the spatial logic for closure spaces SLCS, and its combination with the temporal logic CTL, leading to STLCS. The interplay of space and time permits one to define complex spatio-temporal properties. Both for the spatial and the spatio-temporal fragment efficient model-checking algorithms have been developed and their use on a number of case studies and examples is illustrated.
Vincenzo Ciancia, Diego Latella, Michele Loreti, Mieke Massink
Quantitative Abstractions for Collective Adaptive Systems
Abstract
Collective adaptive systems (CAS) consist of a large number of possibly heterogeneous entities evolving according to local interactions that may operate across multiple scales in time and space. The adaptation to changes in the environment, as well as the highly dispersed decision-making process, often leads to emergent behaviour that cannot be understood by simply analysing the objectives, properties, and dynamics of the individual entities in isolation.
As with most complex systems, modelling is a phase of crucial importance for the design of new CAS or the understanding of existing ones. Elsewhere in this volume the typical workflow of formal modelling, analysis, and evaluation of a CAS has been illustrated in detail. In this chapter we treat the problem of efficiently analysing large-scale CAS for quantitative properties. We review algorithms to automatically reduce the dimensionality of a CAS model preserving modeller-defined state variables, with focus on descriptions based on systems of ordinary differential equations. We illustrate the theory in a tutorial fashion, with running examples and a number of more substantial case studies ranging from crowd dynamics, epidemiology and biological systems.
Andrea Vandin, Mirco Tribastone
Aggregate Programming: From Foundations to Applications
Abstract
We live in a world with an ever-increasing density of computing devices, pervading every aspect of our environment. Programming these devices is challenging, due to their large numbers, potential for frequent and complex network interactions with other nearby devices, and the open and evolving nature of their capabilities and applications. Aggregate programming addresses these challenges by raising the level of abstraction, so that a programmer can operate in terms of collections of interacting devices. In particular, field calculus provides a safe and extensible model for encapsulation, modulation, and composition of services. On this foundation, a set of resilient “building block” operators support development of APIs that can provide resilience and scalability guarantees for any service developed using them. We illustrate the power of this approach by discussion of several recent applications, including crowd safety at mass public events, disaster relief operations, construction of resilient enterprise systems, and network security.
Jacob Beal, Mirko Viroli
Backmatter
Metadata
Title
Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems
Editors
Marco Bernardo
Rocco De Nicola
Jane Hillston
Copyright Year
2016
Electronic ISBN
978-3-319-34096-8
Print ISBN
978-3-319-34095-1
DOI
https://doi.org/10.1007/978-3-319-34096-8

Premium Partner

    Image Credits