Internet of Things integration to a Multi Agent System based manufacturing environment

Alexakos, Christos; Καλογεράς, Αθανάσιος

doi:10.1109/etfa.2015.7301415

Cited by 18 publications

(13 citation statements)

References 15 publications

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“…Observing one or more agent communities operating in IoT and CPS scenarios can unveil an apparently unlimited potential. For example, the application domains that received more contributions are healthcare [25,27,31,52,61,62], smart environments (e.g., office, home city [4,6,44,58]), smart cities (e.g., mobility [32,44], urban safety [73], water distribution [4, 45], transportation [13], and energy [13,54,73]), industrial scenarios (e.g., manufacturing [4], workflow and process management [13,73]) and assisted living [6,20,21,58]. See [70] for a recent survey of MAS applications.…”

Section: Mas: a Dai Expressionmentioning

confidence: 99%

“…Moreover, in IoT and CPS solutions, the agents have been associated with real-time related services/tasks, representing a fascinating cross-domain class to be analyzed in more depth. For example, in "smart" and other relevant domains, several applications require features compliant with real-time-like constraints, such as sharing information [45], awareness of environmental changes [13], decision support [45], perception of provided energy [54], information sharing in manufacturer processes [4], security controls [75], and on time activities execution in production lines [42]. Such services are receiving increasing scientific attention, and the MAS, if extended with the above-mentioned real-time services, represent a notable overlap among the IoT and CPS systems.…”

Section: Mas: a Dai Expressionmentioning

confidence: 99%

“…For example, in the case of algorithms such as EDF and CBS U lub = 1 4. in the case where the period T k and deadline D k are equal.…”

mentioning

confidence: 99%

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Real-time multi-agent systems: rationality, formal model, and empirical results

Calvaresi

Cid

Marinoni

et al. 2021

Auton Agent Multi-Agent Syst

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Since its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. As AI applications matured, the interest for employing them into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among the most relevant approaches fostering the development of intelligent systems. In numerous scenarios, MAS boosted distributed autonomous reasoning and behaviors. However, many real-world applications (e.g., CPS) demand the respect of strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason “about time” and are incapable of acting “in time” guaranteeing any timing predictability. This paper analyzes the MAS compliance with strict timing constraints (real-time compliance)—crucial for safety-critical applications such as healthcare, industry 4.0, and automotive. Moreover, it elicits the main reasons for the lack of real-time satisfiability in MAS (originated from current theories, standards, and implementations). In particular, traditional internal agent schedulers (general-purpose-like), communication middlewares, and negotiation protocols have been identified as co-factors inhibiting real-time compliance. To pave the road towards reliable and predictable MAS, this paper postulates a formal definition and mathematical model of real-time multi-agent systems (RT-MAS). Furthermore, this paper presents the results obtained by testing the dynamics characterizing the RT-MAS model within the simulator MAXIM-GPRT. Thus, it has been possible to analyze the deadline miss ratio between the algorithms employed in the most popular frameworks and the proposed ones. Finally, discussing the obtained results, the ongoing and future steps are outlined.

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Section: Mas: a Dai Expressionmentioning

confidence: 99%

Section: Mas: a Dai Expressionmentioning

confidence: 99%

See 1 more Smart Citation

Real-time multi-agent systems: rationality, formal model, and empirical results

Calvaresi

Cid

Marinoni

et al. 2021

Auton Agent Multi-Agent Syst

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“…In the litterature, there exist works on formal modeling of communication protocols entended for IoT systems [40], [41]. There exists also proposals for modeling IoT systems using Multi Agent Systems [42], [43]. In a previous work, we propose a formal model for our ReDy architecture entended for IoT systems [44]- [46].…”

Section: Iot Challengesmentioning

confidence: 99%

Overview on Internet of Things (IoT) Architectures, Enabling Technologies and Challenges

Hafdi¹,

Kriouile²

2019

JCP

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IoT systems are known for being complex, heterogeneous, distributed, resources constrained, integrating probably moving devices or services in a highly dynamic environment. This is a non exhaustive set of characteristics that an IoT system should satisfy. Designing an IoT system according to a given architecture in order to satisfy a set of required characteristics is a priority in order to meet principal requirements of the system according to the specific application field. In this paper, we give an overview of main existing categories of IoT architectures. We identify principally software IoT architecture, hardware IoT architecture, and general IoT architecture. Based on this study, we propose an end-to-end IoT architecture designed according to a five layered model. We propose a summary of different enabling technologies presented according to the end-to-end architecture. We finally exhibit main challenges of IoT systems that can be raised at different contexts and applications.

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“…On the other hand, in Kamiski et al (2016) and Nieves et al (2017) are presented the modeling of IoT scenarios also employing software agents (Kaminski, Murphy, & Marchetti, 2016;Nieves & Andrade, Daniel, 2017). Finally, Alexakos et al (2015) and Leong et al (2014) addressed their research for managing IoT ecosystems by means of Multi-agent Systems (MASs) (Alexakos & Kalogeras, 2015;Leong & Lu, 2014). However, the integration of applications developed under these paradigms is still a challenge that the IoA must solve.…”

Section: The Internet Of Agents Approachmentioning

confidence: 99%

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

et al. 2018

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Recently, the scientific community has demonstrated a special interest in the process related to the integration of the agent-oriented technology with Internet of Things (IoT) platforms. Then, it arises a novel approach named Internet of Agents (IoA) as an alternative to add an intelligence and autonomy component for IoT devices and networks. This paper presents an analysis of the main benefits derived from the use of the IoA approach, based on a practical point of view regarding the necessities that humans demand in their daily life and work, which can be solved by IoT networks modeled as IoA infrastructures. It has been presented 24 study cases of the IoA approach at different domains --smart industry, smart city and smart health wellbeing--in order to define the scope of these proposals in terms of intelligence and autonomy in contrast to their corresponding generic IoT applications. Keywords:Internet of Things, agents, smart industry, smart city, smart health wellbeing. RESUMENEn los últimos años, la comunidad científica ha mostrado un interés especial en torno al proceso de integración de la tecnología orientada a agentes sobre plataformas de Internet de las Cosas (IoT, por sus siglas en inglés). Surge así, un nuevo enfoque denominado Internet de los Agentes (IoA, por sus siglas en inglés) como una alternativa para añadir un componente de inteligencia y autonomía sobre los dispositivos y redes de IoT. El presente trabajo muestra un análisis de los principales beneficios derivados del uso del enfoque del IoA, visto desde las actuales necesidades que el ser humano demanda en su trabajo y vida cotidiana, las cuales pueden ser resueltas por redes de IoT modeladas como infraestructuras de IoA. Se plantea un total de 24 casos prácticos de aplicaciones de IoA en diferentes dominios --industria, ciudad, y salud y bienestar inteligente--a fin de determinar el alcance de dichas aplicaciones en términos de inteligencia y autonomía respecto a sus correspondientes aplicaciones genéricas de IoT.Palabras clave: Internet de las Cosas, agentes, industria inteligente, ciudad inteligente, salud y bienestar inteligente.

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Internet of Things integration to a Multi Agent System based manufacturing environment

Cited by 18 publications

References 15 publications

Real-time multi-agent systems: rationality, formal model, and empirical results

Real-time multi-agent systems: rationality, formal model, and empirical results

Overview on Internet of Things (IoT) Architectures, Enabling Technologies and Challenges

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

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