Statistical analysis of CARMA models: an advanced tutorial

Vashti Galpin; Anastasis Georgoulas; Michele Loreti; Andrea Vandin

doi:10.1109/WSC.2018.8632456

Statistical analysis of CARMA models: an advanced tutorial

Vashti Galpin, Anastasis Georgoulas, Michele Loreti, Andrea Vandin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

CARMA (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A CARMA model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a CARMA model are given by a continuous-time Markov chain which can be simulated using the CARMA Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the Multi-VeStA tool. This advanced tutorial will introduce some of the theory behind CARMA and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.

Original language	English
Title of host publication	2018 Winter Simulation Conference (WSC)
Publisher	Institute of Electrical and Electronics Engineers
Pages	395-409
Number of pages	15
ISBN (Electronic)	978-1-5386-6572-5
ISBN (Print)	978-1-5386-6573-2
DOIs	https://doi.org/10.1109/WSC.2018.8632456
Publication status	E-pub ahead of print - Dec 2018
Event	Winter Simulation Conference - Gothenburg, Sweden Duration: 9 Dec 2018 → 12 Dec 2018 http://meetings2.informs.org/wordpress/wsc2018/

Publication series

Name
Publisher	IEEE
ISSN (Print)	0891-7736
ISSN (Electronic)	1558-4305

Conference

Conference	Winter Simulation Conference
Abbreviated title	WSC 2018
Country/Territory	Sweden
City	Gothenburg
Period	9/12/18 → 12/12/18
Internet address	http://meetings2.informs.org/wordpress/wsc2018/

Access to Document

10.1109/WSC.2018.8632456

Statistical Analysis of carma models an advanced tutorialAccepted author manuscript, 653 KB

https://ieeexplore.ieee.org/document/8632456

QUANTICOL - A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours (RTD)
Hillston, J. & Gilmore, S.
EU government bodies
1/04/13 → 31/03/17
Project: Research

Cite this

@inproceedings{75dc8dc908194fe8937373c693cce555,

title = "Statistical analysis of CARMA models: an advanced tutorial",

abstract = "CARMA (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A CARMA model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a CARMA model are given by a continuous-time Markov chain which can be simulated using the CARMA Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the Multi-VeStA tool. This advanced tutorial will introduce some of the theory behind CARMA and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.",

author = "Vashti Galpin and Anastasis Georgoulas and Michele Loreti and Andrea Vandin",

year = "2018",

month = dec,

doi = "10.1109/WSC.2018.8632456",

language = "English",

isbn = "978-1-5386-6573-2",

publisher = "Institute of Electrical and Electronics Engineers",

pages = "395--409",

booktitle = "2018 Winter Simulation Conference (WSC)",

address = "United States",

note = "Winter Simulation Conference, WSC 2018 ; Conference date: 09-12-2018 Through 12-12-2018",

url = "http://meetings2.informs.org/wordpress/wsc2018/",

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TY - GEN

T1 - Statistical analysis of CARMA models: an advanced tutorial

AU - Galpin, Vashti

AU - Georgoulas, Anastasis

AU - Loreti, Michele

AU - Vandin, Andrea

PY - 2018/12

Y1 - 2018/12

N2 - CARMA (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A CARMA model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a CARMA model are given by a continuous-time Markov chain which can be simulated using the CARMA Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the Multi-VeStA tool. This advanced tutorial will introduce some of the theory behind CARMA and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.

AB - CARMA (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A CARMA model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a CARMA model are given by a continuous-time Markov chain which can be simulated using the CARMA Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the Multi-VeStA tool. This advanced tutorial will introduce some of the theory behind CARMA and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.

U2 - 10.1109/WSC.2018.8632456

DO - 10.1109/WSC.2018.8632456

M3 - Conference contribution

SN - 978-1-5386-6573-2

SP - 395

EP - 409

BT - 2018 Winter Simulation Conference (WSC)

PB - Institute of Electrical and Electronics Engineers

T2 - Winter Simulation Conference

Y2 - 9 December 2018 through 12 December 2018

ER -

Statistical analysis of CARMA models: an advanced tutorial

Abstract / Description of output

Publication series

Conference

Access to Document

Fingerprint

Projects

QUANTICOL - A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours (RTD)

Cite this