AI for next generation computing: Emerging trends and future directions
Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …
outcomes on their own, without the intervention of a human operator. Autonomic computing …
[HTML][HTML] Edge AI: a survey
Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …
refers to the practice of doing AI computations near the users at the network's edge, instead …
AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
[HTML][HTML] Modern computing: Vision and challenges
Over the past six decades, the computing systems field has experienced significant
transformations, profoundly impacting society with transformational developments, such as …
transformations, profoundly impacting society with transformational developments, such as …
Opportunities and challenges of artificial intelligence and distributed systems to improve the quality of healthcare service
S Aminizadeh, A Heidari, M Dehghan, S Toumaj… - Artificial Intelligence in …, 2024 - Elsevier
The healthcare sector, characterized by vast datasets and many diseases, is pivotal in
shaping community health and overall quality of life. Traditional healthcare methods, often …
shaping community health and overall quality of life. Traditional healthcare methods, often …
Edge AI: A taxonomy, systematic review and future directions
Abstract Edge Artificial Intelligence (AI) incorporates a network of interconnected systems
and devices that receive, cache, process, and analyse data in close communication with the …
and devices that receive, cache, process, and analyse data in close communication with the …
Enhancing healthcare in the digital era: A secure e-health system for heart disease prediction and cloud security
V Janarthanan, T Annamalai, M Arumugam - Expert Systems with …, 2024 - Elsevier
In the modern world, due to changing lifestyles, more people are infected by deadly
diseases, especially heart disorders. An early prognosis is the only possible way of …
diseases, especially heart disorders. An early prognosis is the only possible way of …
Federated learning based Covid‐19 detection
The world is affected by COVID‐19, an infectious disease caused by the SARS‐CoV‐2 virus.
Tests are necessary for everyone as the number of COVID‐19 affected individual's …
Tests are necessary for everyone as the number of COVID‐19 affected individual's …
High-Speed Network DDoS Attack Detection: A Survey
Having a large number of device connections provides attackers with multiple ways to attack
a network. This situation can lead to distributed denial-of-service (DDoS) attacks, which can …
a network. This situation can lead to distributed denial-of-service (DDoS) attacks, which can …
Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation
The Healthcare Internet-of-Things (H-IoT), commonly known as Digital Healthcare, is a data-
driven infrastructure that highly relies on smart sensing devices (ie, blood pressure monitors …
driven infrastructure that highly relies on smart sensing devices (ie, blood pressure monitors …