A New Feature in Mysejahtera Application to Monitoring the Spread of COVID-19 Using Fog Computing

Abdali, Taj-Aldeen Naser; Hassan, Rosilah; Aman, Azana Hafizah Mohd

doi:10.1109/crc50527.2021.9392534

Cited by 9 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2020) studied the safety and operability of the Mysejahtera from a technological background. Abdali et al. (2021) brought up optimization proposals on Mysejahtera regarding its technology.…”

Section: Literature Reviewmentioning

confidence: 99%

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world

Jiang

Mohamed²

2022

Heliyon

View full text Add to dashboard Cite

Section: Literature Reviewmentioning

confidence: 99%

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world

Jiang

Mohamed²

2022

Heliyon

View full text Add to dashboard Cite

“…Several studies have considered the reliability and its facilities. For instance, in the study of Melnik et al [114], a new approach was proposed, termed control system reliability enhancement, to solve the complexity of the problems by the optimization method, and the problems were proposed as follows: the estimation for computational complexity, and the distribution of fog layers.…”

Section: Reliability Optimizationmentioning

confidence: 99%

Fog Computing Advancement: Concept, Architecture, Applications, Advantages, and Open Issues

et al. 2021

Self Cite

View full text Add to dashboard Cite

Internet of Things (IoT) is proliferating in our real world, and it is a promising technology that serves a very comfortable service to the users. IoT's underlying technology is to connect to central Cloud Computing (CC), which is a huge data center collecting the generated data by IoT devices, and it is located in different areas on demand. However, cloud computing lacks data transmission because of the infrastructure and limitations of networks which enormously decrease its performance. Therefore, a new paradigm has been founded to act as a middleware between the Cloud and IoT, termed Fog Computing (FC) Technology. Considering Fog as a cloud extension that provides computing service at the edge of the network, Fog Computing placement enables this technology to deal with numerous data locally. In this study, we surveyed Fog computing with in-depth analysis and covered the latest studies to address and overcome the existing challenges in FC. We reviewed fog computing technology conceptually and defined it based on the existing studies in the literature, together with its architecture, applications, advantages, and open issues with optimization methods being performed to obtain the optimal services. INDEX TERMS Fog Computing Applications, Fog Computing Concept, Fog Computing Open Issues, Cloud computing, Internet of Things (IoT).

show abstract

“…Doctors can guide patients with the right decisions by monitoring a person with Coronavirus disease 2019 (COVID-19)in real-time. 32,33 For example, El- Rashidy et al proposed an end-to-end deep-learning framework for monitoring COVID-19 patients in real-time. The proposed system has been declared effective regarding quarantine and remote care of patients with COVID-19.…”

Section: Introductionmentioning

confidence: 99%

A fog-assisted information model based on priority queue and clinical decision support systems

Yazdani

Dashti

Safdari

2023

Health Informatics J

View full text Add to dashboard Cite

Objectives Telehealth monitoring applications are latency-sensitive. The current fog-based telehealth monitoring models are mainly focused on the role of the fog computing in improving response time and latency. In this paper, we have introduced a new service called “priority queue” in fog layer, which is programmed to prioritize the events sent by different sources in different environments to assist the cloud layer with reducing response time and latency. Material and Methods We analyzed the performance of the proposed model in a fog-enabled cloud environment with the IFogSim toolkit. To provide a comparison of cloud and fog computing environments, three parameters namely response time, latency, and network usage were used. We used the Pima Indian diabetes dataset to evaluate the model. Result The fog layer proved to be very effective in improving the response time while handling emergencies using priority queues. The proposed model reduces response time by 25.8%, latency by 36.18%, bandwidth by 28.17%, and network usage time by 41.4% as compared to the cloud. Conclusion By combining priority queues, and fog computing in this study, the network usage, latency time, bandwidth, and response time were significantly reduced as compared to cloud computing.

show abstract

A New Feature in Mysejahtera Application to Monitoring the Spread of COVID-19 Using Fog Computing

Cited by 9 publications

References 13 publications

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world

Fog Computing Advancement: Concept, Architecture, Applications, Advantages, and Open Issues

A fog-assisted information model based on priority queue and clinical decision support systems

Contact Info

Product

Resources

About