Sensor Initiated Healthcare Packet Priority in Congested IoT Networks

Besher, Kedir Mamo; Beitelspacher, Sara; Hipólito, Juan Iván Nieto

doi:10.1109/jsen.2020.3012519

Cited by 12 publications

(6 citation statements)

References 20 publications

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“…We consider various domains of IoT applications such as Multimedia, Industrial IoT, Military, Healthcare and Transportation applications. QoS metrics of these applications are listed as the followings : jitter [100], [101], [102], latency [100], [103], packet loss [100], [104], [101], [105], [106], [107], [108], throughput [104], [101], [109], [103], [110], [106], [107], [111], [108], [112], [102], delay [113], [114], [104], [109], [105], [106], [107], [111], [108], [112], [102], reliability [114], [115], [110], [116], [112], [117], [118], availability [113], [116], [118], scalability [115], energy [109],…”

Section: A Qos Metrics and Iot Applicationsmentioning

confidence: 99%

“…Moreover, each application seems to focus on different group of QoS metrics. For example, healthcare applications [106], [107], [111], [108] are mainly concerned over QoS like packet loss, delay and throughput because nature of healthcare applications require low delay and packet loss. Loss of little information can highly affect patients or doctors who use the applications.…”

Section: A Qos Metrics and Iot Applicationsmentioning

confidence: 99%

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QoE-Driven IoT Architecture: A Comprehensive Review on System and Resource Management

et al. 2022

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Internet of Things (IoT) services have grown substantially in recent years. Consequently, IoT service providers (SPs) are emerging in the market and competing to offer their services. Many IoT applications utilize these services in an integrated manner with different Quality-of-Service (QoS) requirements. Thus, the provisioning of end-to-end QoS is getting more indispensable for IoT platforms. However, provisioning the system by using only QoS metrics without considering user experiences is not sufficient. Recently, Quality of Experience (QoE) model has become a promising approach to quantify actual user experiences of services. A holistic design approach that considers constraints of various QoS/QoE metrics together is needed to satisfy requirements of these applications and services. Besides, IoT services may operate in environments with limited resources. Therefore, effective management of services and system resources is essential for QoS/QoE support. This paper provides a comprehensive survey for the state-of-the-art studies on IoT services with QoS/QoE perspective. Our contributions are threefold: (1) QoEdriven architecture is demonstrated by classifying vital components according to QoE-related functions in prior studies, (2) QoE metrics and QoE optimization objectives are classified by corresponding system and resource control problems in the architecture, and (3) QoE-aware resource management e.g., QoE-aware offloading, placement and data caching policies with recent Machine Learning approaches are extensively reviewed. INDEX TERMSInternet of Things, Quality of Service, Quality of Experience, IoT services, IoT applications, QoS for IoT services, QoS metrics, QoE metrics, IoT architecture Recently, emerging IoT architectures with multi-layers, e.g., Mobile Edge Computing (MEC), Fog Computing and Cloud Computing, have been proposed to improve user experiences.

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Section: A Qos Metrics and Iot Applicationsmentioning

confidence: 99%

Section: A Qos Metrics and Iot Applicationsmentioning

confidence: 99%

QoE-Driven IoT Architecture: A Comprehensive Review on System and Resource Management

et al. 2022

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“…Según (Lloret et al, 2016), la cantidad de información útil (payload) de un paquete con información de salud puede alcanzar un tamaño promedio de 104 bytes. Asimismo, en (Besher et al, 2020) y (Beitelspacher et al, 2020), se muestra que el tamaño de un paquete de datos biométricos es de 79 bytes y 50 bytes respectivamente, las diferencias se dan debido al número de sensores, tipo de sensores y frecuencia de recolección de datos.…”

Section: Trabajos Relacionadosunclassified

“…Con ello, se definió el valor de data rate en 100 kbps constantes (CBR), de acuerdo a los valores observados en los trabajos relacionados, ver Tabla 1. De la misma forma se estableció el tamaño del paquete en 100 bytes, debido a que es un valor que estuvo en el rango descrito por los autores (Beitelspacher et al, 2020;Besher et al, 2020;Lloret et al, 2016). Por último, se escogió UDP como protocolo de transporte debido a que comparado con TCP éste es más rápido, simple y eficiente.…”

Section: Materiales Y Métodosunclassified

Análisis del rendimiento de los protocolos OLSR, DSDV y AODV en una Red MANET

Romero

Picón

Martínez

2021

rte

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Este artículo presenta una propuesta de análisis y comparación entre los protocolos de enrutamiento proactivo OLSR y DSDV, y reactivo AODV en una red MANET. Se definen dos escenarios: el primero representando un equipo de fútbol atacando y el segundo defendiendo. Se varía el área de movimiento de los nodos para simular cada escenario. Para ello, se realiza una investigación sobre los problemas que presentan estos algoritmos de enrutamiento para redes Ad Hoc en diferentes ámbitos. De esta forma, obtener un panorama de las estrategias y soluciones que existen actualmente. A partir de la información recopilada, se propone realizar una simulación utilizando NS3, para obtener resultados que se asemejen a la realidad. La comparación se realiza a base de las métricas de throughput, PDR y Delay. En cada simulación, la velocidad de los nodos y la posición inicial se ajustan según el comportamiento de un jugador de fútbol real. Los nodos se mueven en una trayectoria aleatoria dentro del área específica, y uno de éstos envía datos a un nodo fijo situado en el borde del campo. El tráfico transmitido está caracterizado para simular datos biométricos realistas. A partir de los resultados, se concluye que AODV y DSDV tienen un mejor rendimiento que OLSR y el intervalo óptimo de transmisión es de 20 segundos. Además, con una potencia de transmisión de 10 dBm se garantiza el 100% del throughput en el receptor.

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“…However, several technical challenges must be overcome before IoT technologies can be implemented in healthcare settings. Providing quality of service (QoS) is one of the most significant challenges [ 9 , 10 , 11 , 12 , 13 , 14 ]. Furthermore, considering the use of wireless networks and the presence of network congestion, this challenge becomes more difficult to solve [ 9 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Buenrostro-Mariscal

Santana-Mancilla

Montesinos‐López

et al. 2023

Sensors

Self Cite

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Real-life implementation of the Internet of Things (IoT) in healthcare requires sufficient quality of service (QoS) to transmit the collected data successfully. However, unsolved challenges in prioritization and congestion issues limit the functionality of IoT networks by increasing the likelihood of packet loss, latency, and high-power consumption in healthcare systems. This study proposes a priority-based cross-layer congestion control protocol called QCCP, which is managed by communication devices’ transport and medium access control (MAC) layers. Unlike existing methods, the novelty of QCCP is how it estimates and resolves wireless channel congestion because it does not generate control packets, operates in a distributed manner, and only has a one-bit overhead. Furthermore, at the same time, QCCP offers packet scheduling considering each packet’s network load and QoS. The results of the experiments demonstrated that with a 95% confidence level, QCCP achieves sufficient performance to support the QoS requirements for the transmission of health signals. Finally, the comparison study shows that QCCP outperforms other TCP protocols, with 64.31% higher throughput, 18.66% less packet loss, and 47.87% less latency.

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Sensor Initiated Healthcare Packet Priority in Congested IoT Networks

Cited by 12 publications

References 20 publications

QoE-Driven IoT Architecture: A Comprehensive Review on System and Resource Management

QoE-Driven IoT Architecture: A Comprehensive Review on System and Resource Management

Análisis del rendimiento de los protocolos OLSR, DSDV y AODV en una Red MANET

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

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