Gallant Ant Colony Optimized Machine Learning Framework (GACO-MLF) for Quality of Service Enhancement in Internet of Things-Based Public Cloud Networking

J Ramkumar, R Vadivel, B Narasimhan… - … Conference on Data …, 2023 - Springer
Load management is a crucial aspect of allocating resources inside a data center for use by
the Internet of Things-based public cloud networking (IoT-PCN). It'sa significant pain in the …

A swarm intelligence-based quality of service aware resource allocation for clouds

A Kumar, A Sharma, R Kumar - International Journal of Ad …, 2020 - inderscienceonline.com
The growing popularity of cloud computing results in very large data centres around the
world with vast amount of energy requirements and CO 2 emissions. These large sized data …

Management of cloud resources and social change in a multi-tier environment: a novel finite automata using ant colony optimization with spanning tree

M Aliyu, M Murali, ZJ Zhang, A Gital, S Boukari… - … Forecasting and Social …, 2021 - Elsevier
The enormous demand for computational resources due to rapid Cloud growth has led to
the creation of large-scale data centers (DC). Consequently, a tremendous amount of …

Artificial neural network based load balancing on software defined networking

S WilsonPrakash… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Cloud computing is an emerging area where all the network services are provided in the
form of pay per use. Utilizing the available resources efficiently is one of the challenge in the …

Mutative ACO based Load Balancing in Cloud Computing.

S Singhal, A Sharma - Engineering Letters, 2021 - search.ebscohost.com
With the increment in figuring advancements, Cloud computing has permitted the clients to
get to assets from anyplace whenever and to pay for the assets based on pay-peruse. Cloud …

COSCO2: AI‐augmented evolutionary algorithm based workload prediction framework for sustainable cloud data centers

R Karthikeyan, V Balamurugan, R Cyriac… - Transactions on …, 2023 - Wiley Online Library
Workload prediction is the necessary factor in the cloud data center for maintaining the
elasticity and scalability of resources. However, the accuracy of workload prediction is very …

RETRACTED ARTICLE: Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm

M Ashawa, O Douglas, J Osamor, R Jackie - Journal of Cloud Computing, 2022 - Springer
Allocating resources is crucial in large-scale distributed computing, as networks of
computers tackle difficult optimization problems. Within the scope of this discussion, the …

Minimized makespan based improved cat swarm optimization for efficient task scheduling in cloud datacenter

D Gabi, AS Ismail, NM Dankolo - Proceedings of the 2019 3rd High …, 2019 - dl.acm.org
Inefficient scheduling of tasks on cloud datacenter resources can result in underutilization
leading to poor revenue generation. To show efficient tasks scheduling on cloud datacenter …

Research on task scheduling strategy optimization based onaco in cloud computing environment

Z He, J Dong, Z Li, W Guo - 2020 IEEE 5th Information …, 2020 - ieeexplore.ieee.org
Cloud computing, as a general IT service model, effectively schedules various types of
request, which is very important in terms of saving resources, improving the service quality …

A bio-inspired hybrid algorithm for effective load balancing in cloud computing

R Kumar, T Prashar - International Journal of Cloud …, 2016 - inderscienceonline.com
Effective scheduling and load balancing are the key challenges of cloud computing
technology. A prominent task scheduler must be adaptable to the dynamic distributed …