مقاله انگلیسی برآورد تلفات بافر برای رفع ازدحام در شبکه اینترنت اشیاء سلامتی
Abstract
Keywords
Introduction
Literature review: Congestion schemes for 6LoWPAN networks
Patient-centric IoHT architectures
Topological layout of IoHT for Remote Health Monitoring (RHM)
Modeling buffer loss for resource-restricted ioht
Analytical Model for Congestion in 6LoWPAN-IoHT Network
Results & discussions
Conclusion
CRediT authorship contribution statement
Declaration of Competing Interest
References
Vitae
Abstract
The Internet of Healthcare Things (IoHT) consists of a wide variety of resource-restricted, heterogeneous, IoT-enabled, wearable/non-wearable medical equipment (things) that connect over the internet to transform traditional healthcare into a smart, connected, proactive, patient-centric healthcare system. The pivotal functions of the 6LoWPAN protocol stack enable comprehensive integration of such networks from wearable wireless sensor networks (W-WSN) to IoHT, as TCP/IP does not suffice the requirements of IoHT networks. As a result, the congestion in the IoHT network increases with a growing number of devices, resulting in loss of critical medical information due to buffer loss and channel loss, which is unacceptable. In this paper, we explored different applications of patient-centric IoHT architectures to draw a realistic resource-limited topological layout of IoHT for congestion estimation. After critically reviewing existing congestion schemes for 6LoWPANs, we proposed an effective buffer-loss estimation model based on the Queuing Theory to determine the number of packets lost at the node’s buffer. The buffer is modeled as an M/M/1/K Markov Chain Queue. The M/M/1/K Queue equilibrium equation is used to establish a relationship between the probabilities of the buffer being empty or completely filled. We derived the expressions for total buffer-loss probability and expected mean packet delay for the resource-constraint IoHT network. Furthermore, to validate the buffer-loss estimation, an analytical model is used to compare buffer-loss probabilities, the number of packets dropped at leaf/intermediate nodes and the number of packets successfully received at the local sink node. The results show a close correlation between both the models on varying values of the number of leaf nodes, buffer size, offered packet load and available channel capacity. Thus, in resource-restrictive IoHT, the proposed model performs better than two related works.
Introduction
IPv6 over Low Power Wireless Personal Area Network (6LoWPAN) is an essential technology in the Internet of Things (IoT). A large number of IoT ‘Things’ are 6LoWPAN enabled motes [1,2]. The defined 6LoWPAN protocol stack helps to comprehensively integrate WSN (Wireless Sensor Network) nodes with IoT motes. Due to this, the application domain of 6LoWPAN becomes wider. These applications can be segregated based on data delivery mechanisms as (i) Eventbased; (ii) Query-based; (iii) Continuous; (iv) Hybrid applications. The IoT-enabled healthcare application is a hybrid kind of domain.In the IoHT application, wearable/non-wearable 6LoWPAN based medical sensing equipment is used to monitor and collect various patient health parameters. The captured data is transmitted towards personal digital devices (smartphone, laptop, tablet) that act as a local sink in the IoHT network. This transmission could be a direct one or through the multi-hop environment. These motes could be tiny in size and have minimal networking resources such as memory, computational capability, bandwidth and so on.