QoS-Driven Self-adaptation for Critical IoT-Based Systems

Gatouillat, Arthur; Badr, Youakim; Massot, Bertrand

doi:10.1007/978-3-319-91764-1_8

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…This may involve the usage of a range of techniques, including dynamic resource allocation, load balancing, and adaptive control. A Quality-of-Service (QoS)-aware self-adaptive framework for critical IoT networks for e-health is presented in [40]. The proposed framework uses a discrete controller synthesis that relies on rules and labeled state transitions to monitor new contexts and monitoring requirements dynamically.…”

Section: E Self-*paradigmmentioning

confidence: 99%

Toward Autonomic Internet of Things: Recent Advances, Evaluation Criteria, and Future Research Directions

Ashraf

Tahir

Habaebi

et al. 2023

IEEE Internet Things J.

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With the rise of the Internet of Things (IoT), tiny devices capable of computation and data transmission are being deployed across various technological domains. Due to the wide deployment of these devices, manual setup and management are infeasible and inefficient. To address this inefficiency, intelligent procedures must be established to enable autonomy that allows devices and networks to operate efficiently with minimal human intervention. In the traditional client-server paradigm, autonomic computing has been proven effective in minimizing user intervention in computer systems management and will benefit IoT networks. However, IoT networks tend to be heterogeneous, distributed, and resource constrained, mandating the need for new approaches to implement autonomic principles compared to traditional approaches. We begin by introducing the basic principles of autonomic computing and its significance in IoT. We then discuss the self-* paradigm and monitor, analyze, plan, and execute (MAPE) loop from an IoT perspective, followed by recent works in IoT and key enabling technologies for enabling autonomic properties in IoT. Based on the self-* paradigm and MAPE loop analysis from the existing literature, we propose a set of qualitative characteristics for evaluating the autonomy of the IoT network. Finally, we provide a comprehensive list of challenges associated with achieving autonomic IoT and directions for future research.

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Section: E Self-*paradigmmentioning

confidence: 99%

Toward Autonomic Internet of Things: Recent Advances, Evaluation Criteria, and Future Research Directions

Ashraf

Tahir

Habaebi

et al. 2023

IEEE Internet Things J.

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show abstract

“…Portanto, o sistema só admite novas conexões após aplicar um algoritmo de avaliação do estado atual da rede e estimar o novo estado. WBAN Protocolo de escalonamento com priorização de dados, controle de admissão [Celdrán et al 2018] ICE Balanceamento [Guezguez et al 2018] WSN, WBAN Priorização de dados, controle de admissão, protocolo de roteamento [Zitta et al 2018] IoT Transmissão multicanal [Iranmanesh and Rizi 2018] WBAN Priorização de dados, controle de admissão, protocolo de roteamento, alocação de espaços de tempo [Wang et al 2018] WBAN Controle de energia [Gatouillat et al 2018] IoT Feedback e loop de controle [Sodhro et al 2019] Telemedicina Suavização de vídeo [Wang, Q. et al 2019] Telemedicina Priorização de dados [Al-Tarawneh 2019] Medical network Diferenciação de serviço, categorização e priorização de dados [Venkatesh et al 2019] SDN Diferenciação de serviço, protocolo de roteamento [Bai et al 2019] WBAN Sincronização de relógio [Khalil et al 2019] IoT Diferenciação de tráfego [Goyal et al 2020] WBAN Priorização de dados e adaptação de taxa de dados A elasticidade dos recursosé uma estratégia comum em ambientes de nuvem, e algumas pesquisas empregam essa ideia para fornecer QoS. Nessas estratégias, as soluções empregam técnicas de alocação e migração de máquinas virtuais para aumentar o desempenho de alguns módulos da arquitetura em situações de sobrecarga.…”

Section: Trabalhos Relacionadosunclassified

Unindo Aplicações Críticas e Sensores IoT com QoS Individual e Adaptativo em Hospitais Inteligentes

Rodrigues

Policarpo

Righi

et al. 2021

Anais Do XXI Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2021)

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Com a utilização de sensores inteligentes em hospitais, tomadas de decisões críticas podem ser realizadas baseadas no monitoramento em tempo real de pacientes e equipamentos. Porém, erros na geração e transmissão de dados podem causar falhas no resultado de aplicações que processam esses dados. Neste contexto, esse artigo propõem HealthStack, um middleware para salas cirúrgicas com estratégias de qualidade do serviço (QoS) e suporte a transmissão de dados em tempo real. O artigo propõe uma estratégia de QoS baseada em neurônios artiﬁciais para seleção dos componentes do middleware com baixa performance. Foi desenvolvido e testado um protótipo do modelo em uma sala de cirurgia real possibilitando redução de jitter médio em até 90,3%.

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“…some systems might have strong requirements on the response time, while some other systems might have requirements on global robustness or overall privacy). Authors of [32] proposed a QoS-based IoT self-adaptation framework, but the specification of control objectives is realised through a simple and unflexible rule-based language and implementation is not described further than simple simulation results.…”

Section: Related Work and Contextmentioning

confidence: 99%

Smart and safe self‐adaption of connected devices based on discrete controllers

2019

Self Cite

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The Internet-of-things, which designates the interconnection of physical objects, is a growing research area with many challenges. One of these challenges is the management of failures and unforeseen situations when using connected devices in real world applications. To this end, the authors propose a self-adaptation framework to deal with changes and take into account storage, computational and communication constraints. Their self-adaptation framework relies on constraints expressed in terms of quality of service (QoS) and event-driven rules to specify control objectives. Internally, the framework generates labelled transitions systems and builds on the fly synchronous controllers to guarantee QoS properties. Moreover, their framework has capabilities to concurrently deal with dynamic control objectives, monitoring and self-adaptation. To prove the practicality of their framework, they present a healthcare case-study to remotely monitor a patient at risk of myocardial infarction recurrence. The objective control rules easily specify how wearable devices should coordinate their behaviours to ensure safety, resilience and health-awareness factors. The implementation of their framework is fully distributed and scalable and include their development of a wearable, remotely configurable, QoS aware cardiac activity sensor.

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QoS-Driven Self-adaptation for Critical IoT-Based Systems

Cited by 9 publications

References 20 publications

Toward Autonomic Internet of Things: Recent Advances, Evaluation Criteria, and Future Research Directions

Toward Autonomic Internet of Things: Recent Advances, Evaluation Criteria, and Future Research Directions

Unindo Aplicações Críticas e Sensores IoT com QoS Individual e Adaptativo em Hospitais Inteligentes

Smart and safe self‐adaption of connected devices based on discrete controllers

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