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 …
AI-empowered fog/edge resource management for IoT applications: A comprehensive review, research challenges and future perspectives
The proliferation of ubiquitous Internet of Things (IoT) sensors and smart devices in several
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
Dynamic scheduling for stochastic edge-cloud computing environments using a3c learning and residual recurrent neural networks
The ubiquitous adoption of Internet-of-Things (IoT) based applications has resulted in the
emergence of the Fog computing paradigm, which allows seamlessly harnessing both …
emergence of the Fog computing paradigm, which allows seamlessly harnessing both …
From cloud to edge: a first look at public edge platforms
Public edge platforms have drawn increasing attention from both academia and industry. In
this study, we perform a first-of-its-kind measurement study on a leading public edge …
this study, we perform a first-of-its-kind measurement study on a leading public edge …
Clustering cloud workloads: K-means vs gaussian mixture model
E Patel, DS Kushwaha - Procedia computer science, 2020 - Elsevier
The growing heterogeneity due to diverse Cloud workloads such as Big Data, IoT and
Business Data analytics, requires precise characterization to design a successful capacity …
Business Data analytics, requires precise characterization to design a successful capacity …
A survey on device behavior fingerprinting: Data sources, techniques, application scenarios, and datasets
In the current network-based computing world, where the number of interconnected devices
grows exponentially, their diversity, malfunctions, and cybersecurity threats are increasing at …
grows exponentially, their diversity, malfunctions, and cybersecurity threats are increasing at …
BHyPreC: a novel Bi-LSTM based hybrid recurrent neural network model to predict the CPU workload of cloud virtual machine
With the advancement of cloud computing technologies, there is an ever-increasing demand
for the maximum utilization of cloud resources. It increases the computing power …
for the maximum utilization of cloud resources. It increases the computing power …
COSCO: Container orchestration using co-simulation and gradient based optimization for fog computing environments
Intelligent task placement and management of tasks in large-scale fog platforms is
challenging due to the highly volatile nature of modern workload applications and sensitive …
challenging due to the highly volatile nature of modern workload applications and sensitive …
HUNTER: AI based holistic resource management for sustainable cloud computing
The worldwide adoption of cloud data centers (CDCs) has given rise to the ubiquitous
demand for hosting application services on the cloud. Further, contemporary data-intensive …
demand for hosting application services on the cloud. Further, contemporary data-intensive …
OP-MLB: an online VM prediction-based multi-objective load balancing framework for resource management at cloud data center
The elasticity of cloud resources allows cloud clients to expand and shrink their demand for
resources dynamically over time. However, fluctuations in the resource demands and pre …
resources dynamically over time. However, fluctuations in the resource demands and pre …