Autonomous computation offloading and auto-scaling the in the mobile fog computing: a deep reinforcement learning-based approach
F Jazayeri, A Shahidinejad… - Journal of Ambient …, 2021 - Springer
Abstract The Fog Computing (FC) paradigm is rapidly becoming an appropriate framework
for the infrastructure related to the Internet of Things (IoT). FC can be a good framework for …
for the infrastructure related to the Internet of Things (IoT). FC can be a good framework for …
Impact of mobile advertising wearout on consumer irritation, perceived intrusiveness, engagement and loyalty: A partial least squares structural equation modelling …
AAM Alwreikat, H Rjoub - South African Journal of Business Management, 2020 - sajbm.org
Purpose: Mobile and smart devices provide a platform for firms/brands to communicate
directly with past, present, or potential consumers (via online pop-ups, sponsored ads, ads …
directly with past, present, or potential consumers (via online pop-ups, sponsored ads, ads …
A cost-efficient auto-scaling mechanism for IoT applications in fog computing environment: a deep learning-based approach
The fog computing model has emerged as a viable infrastructure for serving IoT applications
in recent years. In the fog ecosystem, it is essential to manage resources for different …
in recent years. In the fog ecosystem, it is essential to manage resources for different …
A systematic literature review on soft computing techniques in cloud load balancing network
S Negi, DP Singh, MMS Rauthan - International Journal of System …, 2024 - Springer
Providing, an on-demand facility in the cloud network is one of the finest services for cloud
users. To maintain this dynamic and foremost service, a cloud network must pose the best …
users. To maintain this dynamic and foremost service, a cloud network must pose the best …
Object detection mechanism based on deep learning algorithm using embedded IoT devices for smart home appliances control in CoT
Object detection and recognition is commonly used in diverse computer vision based
applications and many algorithms are proposed in literature. However, application of object …
applications and many algorithms are proposed in literature. However, application of object …
Role-based access using partial homomorphic encryption for securing cloud data
Cloud computing has encountered accelerated growth and technological advancements in
recent times. However, Cloud computing is still perceived to be in its infancy and will unfold …
recent times. However, Cloud computing is still perceived to be in its infancy and will unfold …
Integration of RNN with GARCH refined by whale optimization algorithm for yield forecasting: a hybrid machine learning approach
Forecasting yield is a challenging task in all agricultural crops. So, it is imperative to develop
a machine learning hybrid model with available data for yield forecasting. The main …
a machine learning hybrid model with available data for yield forecasting. The main …
Congestion avoidance through fog computing in internet of vehicles
Recently, internet of vehicles (IoVs) is captivating a lot of interest due to a wide range of
applications in various domains. These applications rely on up-to-date information of …
applications in various domains. These applications rely on up-to-date information of …
The effect of task processing management on energy consumption at the edge of Internet of things network with using reinforcement learning method
In this paper, the task processing approach at the edge of the Internet of Things (IoT)
network in improving energy consumption was investigated. First, the subject of maximizing …
network in improving energy consumption was investigated. First, the subject of maximizing …
Deep embedding learning with auto-encoder for large-scale ontology matching
Ontology matching is an efficient method to establish interoperability among heterogeneous
ontologies. Large-scale ontology matching still remains a big challenge for its long time and …
ontologies. Large-scale ontology matching still remains a big challenge for its long time and …