Agent-Based Systems for Telerehabilitation: Strengths, Limitations and Future Challenges

Calvaresi, Davide; Schumacher, Michael; Marinoni, Mauro; Hilfiker, Roger; Dragoni, Aldo Franco; Buttazzo, Giorgio

doi:10.1007/978-3-319-70887-4_1

Cited by 20 publications

(10 citation statements)

References 44 publications

(41 reference statements)

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“…applications of the WSNs is security. [93][94][95] Personal health data and the business information of the organizations are their privacy and should not be in public or semi-public. Therefore, it is vital to keep the granularity of organizations/people private and secure while transferring over the WSNs.…”

Section: The First Challenge Of the Mass In Almost Allmentioning

confidence: 99%

A review on the applications of multiagent systems in wireless sensor networks

Derakhshan

Yousefi

2019

International Journal of Distributed Sensor Networks

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Nowadays, the efficiency of multiagent systems in wireless sensor networks prompts the researchers to use these emerging mobile software packets in different simulated approaches or real-world applications. Heterogeneous and distributed wireless sensor networks could be integrated with the multiagent systems to map the real-world challenges into the artificial intelligence world. The multiagent systems have been applied from simulated approaches like object detection/ tracking, healthcare, control/assistant, and security systems to real-world applications, including medical/human-care systems and unmanned aerial vehicles. Furthermore, the integration of wireless sensor networks with multiagent systems have emerged novel application, which is known as mobile robots. However, the extensive use of mobile agents in wireless sensor networks has posed different challenges for researchers, including security, resource, and timing limitation. In this work, we review recent simulated approaches and real-world applications of multiagent systems in wireless sensor networks, in which a set of common factors about the things that have been studied are extracted and compared to analyze the performance of mobile agent-based systems in the wireless sensor networks, as well. This analysis provides new research directions about multiagent systems in wireless sensor networks for interested researchers. Finally, a novel framework for dealing with the challenges of multiagent-based applications in the wireless sensor networks which have been mentioned is suggested.

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Section: The First Challenge Of the Mass In Almost Allmentioning

confidence: 99%

A review on the applications of multiagent systems in wireless sensor networks

Derakhshan

Yousefi

2019

International Journal of Distributed Sensor Networks

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“…Employing BCT in different healthcare scenarios has already been proposed in [50,51,52], and several prototypes exist [53,45]. Principles of MAS are as well often applied in healthcare domain [28,54,55]. Possibility to combine MAS and BCT to improve healthcare management has already been mentioned in [33].…”

Section: Open Challenges Of Bct Towards Mas Application Scenariosmentioning

confidence: 99%

Multi-Agent Systems and Blockchain: Results from a Systematic Literature Review

Calvaresi

Dubovitskaya

Calbimonte

et al. 2018

Lecture Notes in Computer Science

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Multi-Agent Systems (MAS) technology is widely used for the development of intelligent distributed systems that manage sensitive data (e.g., ambient assisted living, healthcare, energy trading). To foster accountability and trusted interactions, recent trends advocate the use of blockchain technologies (BCT) for MAS. Although most of these approaches have only started exploring the topic, there is an impending need for establishing a research road-map, as well as identifying scientific and technological challenges in this scope. As a first necessary step towards this goal, this paper presents a systematic literature review of studies involving MAS and BCT as reconciling solutions. Aiming at providing a comprehensive overview of their application domains, we analyze motivations, assumptions, requirements, strengths, and limitations presented in the current state of the art. Moreover, discussing the future challenges, we introduce our vision on how MAS and BCT could be combined in different application scenarios.technical and scientific challenges. Despite many attempts and previous works aiming at developing models and mechanisms to guarantee communications security and trust in MAS [4,5,6], such requirements have not been fully satisfied yet.Recent trends [7,8,9,10] nourish the promising idea of integrating MAS and blockchain technologies (BCT) [11,12], with the expectation of providing BCT features in use-cases where agent systems require them. However, employing a new technology such as blockchain "as-is" and by itself in dynamic and quickly evolving scenarios can represent an unlucky choice. This may be due to several reasons, spanning from fundamental properties of BCT, to application/domain specific constraints. As an example, consider the modification of blockchain code, which can happen through majority consensus. Reaching consensus in a distributed multi-stakeholder network with possible unaligned interests can be considerably complex, and new issues might be introduced as a result [13]. Although effective, some strategic decisions can hinder the evolution of the technology from academic institutions to real-world problems [14].Nevertheless, combining BCT and MAS can represent a win-win solution if properly managed: On the one hand, the adoption and adaption of BCT may fix the security limitations broadly known in MAS literature. On the other hand, BCT can also contribute with features missing in some MAS scenarios (e.g., flexibility). For example, cloud computing systems dealing with potentially "very large datasets" are going towards a process of agentification, exploiting the crucial support of blockchain technology [8]. Considering agents as atomic entities populating P2P communities, the design of a fair scheduling and a general protection of the whole cluster against abusive or malfunctioning nodes is currently one of the main challenges [15]. In particular, in distributed master-less systems with reputation rating across the cluster, the application of multi-level principles of cryptocurrencies has...

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“…Such an assumption is naive and too optimistic, thus resulting in being unacceptable for safety-critical applications [8]. For example, in the case of a telerehabilitation system, a delayed, wrong, or miss-aligned (in terms of content -time) feedback may cause severe injuries to the patient [3]. Nevertheless, almost all the agent-based platforms present and have implement at least one local scheduler.…”

Section: Local Scheduling In Agent-based Frameworkmentioning

confidence: 99%

“…Data are collected through distributed sensors, locally or remotely processed, possibly composing feedback to be sent to other entities, or triggering actions directly affecting the physical world (e.g., via actuators). In domains such as e-health [1,2], telerehabilitation [3], manufacturing [4], retails [5], and automotive [6], regardless of dimensions and distribution, the safety of the system and its users is the major requirement. Assuming there is an absence of hardware failures and errors in the design phase [7], to operate in safety-critical scenarios, a system has to be able to guarantee its correct execution and the compliance with strict timing constraints even in the worst-case scenario [7].…”

Section: Introductionmentioning

confidence: 99%

Local Scheduling in Multi-Agent Systems: Getting Ready for Safety-Critical Scenarios

Calvaresi

Marinoni

Lustrissimini

et al. 2018

Multi-Agent Systems and Agreement Technologies

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Multi-Agent Systems (MAS) have been supporting the development of distributed systems performing decentralized thinking and reasoning, automated actions, and regulating component interactions in unpredictable and uncertain scenarios. Despite the scientific literature is plenty of innovative contributions about resource and tasks allocation, the agents still schedule their behaviors and tasks by employing traditional general-purpose scheduling algorithms. By doing so, MAS are unable to enforce the compliance with strict timing constraints. Thus, it is not possible to provide any guarantee about the system behavior in the worst-case scenario. Thereby, as they are, they cannot operate in safetycritical environments. This paper analyzes the agents' local schedulers provided by the most relevant agent-based frameworks from a cyberphysical systems point of view. Moreover, it maps a set of agents' behaviors on task models from the real-time literature. Finally, a practical case-study is provided to highlight how such "MAS reliability" can be achieved.

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Agent-Based Systems for Telerehabilitation: Strengths, Limitations and Future Challenges

Cited by 20 publications

References 44 publications

A review on the applications of multiagent systems in wireless sensor networks

A review on the applications of multiagent systems in wireless sensor networks

Multi-Agent Systems and Blockchain: Results from a Systematic Literature Review

Local Scheduling in Multi-Agent Systems: Getting Ready for Safety-Critical Scenarios

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