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Introduction to special section on formal methods in pervasive computing

Authors:

Mohamed Bakhouya,

Antonio Coronato,

Giuseppe de Pietro,

Anand RanganathanAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 7, Issue 1

Article No.: 6, Pages 1 - 9

https://doi.org/10.1145/2168260.2168266

Published: 04 May 2012 Publication History

Abstract

Ubiquitous and pervasive applications may present critical requirements from the point of view of functional correctness, reliability, availability, security, and safety. Unlike traditional safety-critical applications, the behavior of ubiquitous and pervasive applications is affected by the movements and location of users and resources. In this article, we first present emerging formal methods for the description of both entities and their behavior in pervasive computing environments; then, we introduce this special issue. Despite many previous works that have focused on modeling the entities, relatively few have concentrated on modeling or verifying behaviors; and almost none has dealt with combining techniques proposed in these two aspects. The articles accepted in this special issue cover some of the topics aforementioned and constitute a representative sample of the latest development of formal methods in pervasive computing environments.

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Index Terms

Introduction to special section on formal methods in pervasive computing

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Information & Contributors

Information

Published In

cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 7, Issue 1

Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms

April 2012

365 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/2168260

Issue’s Table of Contents

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 May 2012

Accepted: 01 February 2012

Revised: 01 April 2011

Received: 01 June 2010

Published in TAAS Volume 7, Issue 1

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Cited By

Naeem MCoronato A(2022)An AI-Empowered Home-Infrastructure to Minimize Medication ErrorsJournal of Sensor and Actuator Networks10.3390/jsan1101001311:1(13)Online publication date: 9-Feb-2022
https://doi.org/10.3390/jsan11010013
Shah SCoronato ANaeem MDe Pietro G(2022)Learning and Assessing Optimal Dynamic Treatment Regimes Through Cooperative Imitation LearningIEEE Access10.1109/ACCESS.2022.319349410(78148-78158)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3193494
Djoudi BBouanaka CZeghib N(2021)Formal Specification of Non-Functional Properties of Context-Aware SystemsInternational Journal of Organizational and Collective Intelligence10.4018/IJOCI.28617512:2(1-31)Online publication date: 10-Dec-2021
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Naeem MDe Pietro GCoronato A(2021)Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) SystemsSensors10.3390/s2201030922:1(309)Online publication date: 31-Dec-2021
https://doi.org/10.3390/s22010309
Naeem MCoronato AParagliola G(2019)Adaptive Treatment Assisting System for Patients Using Machine Learning2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS.2019.8931857(460-465)Online publication date: Oct-2019
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Paragliola GNaeem M(2019)Risk management for nuclear medical department using reinforcement learning algorithmsJournal of Reliable Intelligent Environments10.1007/s40860-019-00084-zOnline publication date: 14-May-2019
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Mahfooz Ul Haque HZulfiqar HAhmed AAli Y(2019)A context‐aware framework for modelling and verification of smart parking systems in urban citiesConcurrency and Computation: Practice and Experience10.1002/cpe.540133:2Online publication date: 20-Jun-2019
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Paragliola GCoronato ANaeem MDe Pietro G(2018)A Reinforcement Learning-Based Approach for the Risk Management of e-Health Environments: A Case Study2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)10.1109/SITIS.2018.00114(711-716)Online publication date: Nov-2018
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Djoudi BBouanaka CZeghib N(2016)A formal framework for context-aware systems specification and verificationJournal of Systems and Software10.5555/3044222.3051240122:C(445-462)Online publication date: 1-Dec-2016
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