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] AI augmented Edge and Fog computing: Trends and challenges
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
A review on task scheduling techniques in cloud and fog computing: Taxonomy, tools, open issues, challenges, and future directions
Efficient task scheduling on the cloud is critical for optimal utilization of resources in data
centers. It became even more challenging with the emergence of 5G and IoT applications …
centers. It became even more challenging with the emergence of 5G and IoT applications …
FlexiBERT: Are current transformer architectures too homogeneous and rigid?
The existence of a plethora of language models makes the problem of selecting the best one
for a custom task challenging. Most state-of-the-art methods leverage transformer-based …
for a custom task challenging. Most state-of-the-art methods leverage transformer-based …
Latency-aware task scheduling for IoT applications based on artificial intelligence with partitioning in small-scale fog computing environments
JB Lim - Sensors, 2022 - mdpi.com
The Internet of Things applications have become popular because of their lightweight nature
and usefulness, which require low latency and response time. Hence, Internet of Things …
and usefulness, which require low latency and response time. Hence, Internet of Things …
SimTune: Bridging the simulator reality gap for resource management in edge-cloud computing
Industries and services are undergoing an Internet of Things centric transformation globally,
giving rise to an explosion of multi-modal data generated each second. This, with the …
giving rise to an explosion of multi-modal data generated each second. This, with the …
A scalable modified deep reinforcement learning algorithm for serverless IoT microservice composition infrastructure in fog layer
ME Khansari, S Sharifian - Future Generation Computer Systems, 2024 - Elsevier
Nowadays many modern and Artificial Intelligence (AI) enabled Internet of Things (IoT)
applications consist of chains connecting microservices distributed across the fog and cloud …
applications consist of chains connecting microservices distributed across the fog and cloud …
Energy saving strategy of cloud data computing based on convolutional neural network and policy gradient algorithm
D Yang, J Yu, X Du, Z He, P Li - Plos one, 2022 - journals.plos.org
Cloud Data Computing (CDC) is conducive to precise energy-saving management of user
data centers based on the real-time energy consumption monitoring of Information …
data centers based on the real-time energy consumption monitoring of Information …
Carol: Confidence-aware resilience model for edge federations
In recent years, the deployment of large-scale Inter-net of Things (IoT) applications has
given rise to edge federations that seamlessly interconnect and leverage resources from …
given rise to edge federations that seamlessly interconnect and leverage resources from …
Optimizing the performance of fog computing environments using ai and co-simulation
This tutorial presents a performance engineering approach for optimizing the Quality of
Service (QoS) of Edge/Fog/Cloud Computing environments using AI and Coupled …
Service (QoS) of Edge/Fog/Cloud Computing environments using AI and Coupled …