Task scheduling algorithms for energy optimization in cloud environment: a comprehensive review
R Ghafari, FH Kabutarkhani, N Mansouri - Cluster Computing, 2022 - Springer
Cloud computing is very popular because of its unique features such as scalability, elasticity,
on-demand service, and security. A large number of tasks are performed simultaneously in a …
on-demand service, and security. A large number of tasks are performed simultaneously in a …
EA-MSCA: An effective energy-aware multi-objective modified sine-cosine algorithm for real-time task scheduling in multiprocessor systems: Methods and analysis
M Abdel-Basset, R Mohamed, M Abouhawwash… - Expert systems with …, 2021 - Elsevier
With the significant growth of multiprocessor systems (MPS) to deal with complex tasks and
speed up their execution, the energy generated as a result of this growth becomes one of …
speed up their execution, the energy generated as a result of this growth becomes one of …
Energy-aware whale optimization algorithm for real-time task scheduling in multiprocessor systems
M Abdel-Basset, D El-Shahat, K Deb… - Applied Soft …, 2020 - Elsevier
Abstract The growth of Multiprocessing Systems (MPS) has become a necessity for dealing
with complex tasks and speeding up their execution. Increasing the number of processing …
with complex tasks and speeding up their execution. Increasing the number of processing …
A survey of low-energy parallel scheduling algorithms
High energy consumption is one of the biggest obstacles to the rapid development of
computing systems, and reducing energy consumption is quite urgent and necessary for …
computing systems, and reducing energy consumption is quite urgent and necessary for …
A quick review of ML algorithms
G Chitralekha, JM Roogi - 2021 6th International Conference …, 2021 - ieeexplore.ieee.org
Machine Learning is considered to be an offset of artificial intelligence that is associated with
the design and development of algorithms that will make computers to learn behaviors …
the design and development of algorithms that will make computers to learn behaviors …
A genetic-based approach for service placement in fog computing
N Sarrafzade, R Entezari-Maleki, L Sousa - The Journal of …, 2022 - Springer
The combination of cloud computing with the Internet of Things has made fundamental
changes in areas from industry, healthcare, traffic, and transportation to home appliances …
changes in areas from industry, healthcare, traffic, and transportation to home appliances …
Using informative features in machine learning based method for COVID-19 drug repurposing
Abstract Coronavirus disease 2019 (COVID-19) is caused by a novel virus named Severe
Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus induced a large …
Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus induced a large …
Hybrid fuzzy-based deep remora reinforcement learning based task scheduling in heterogeneous multicore-processor
In recent times, heterogeneous multicore processors have played a critical role in many
applications because they provide better performance in adapting power constraints with …
applications because they provide better performance in adapting power constraints with …
Reliability-aware task scheduling for energy efficiency on heterogeneous multiprocessor systems
Z Deng, D Cao, H Shen, Z Yan, H Huang - The Journal of Supercomputing, 2021 - Springer
Recent studies mainly focus on high performance or low power consumption for task
scheduling on heterogeneous multiprocessor systems (HMSs). Dynamic voltage and …
scheduling on heterogeneous multiprocessor systems (HMSs). Dynamic voltage and …
A bi-objective workflow scheduling in virtualized fog-cloud computing using NSGA-II with semi-greedy initialization
Abstract Virtualized Fog-Cloud Computing (VFCC) has emerged as a promising computing
model in both research and industry. Its inherent characteristics, such as real-time service …
model in both research and industry. Its inherent characteristics, such as real-time service …