Dynamic scheduling of independent tasks in cloud computing applying a new hybrid metaheuristic algorithm including Gabor filter, opposition-based learning, multi-verse optimizer, and multi-tracker optimization algorithms

2021 ◽  
Author(s):  
Ahmad Nekooei-Joghdani ◽  
Faramarz Safi-Esfahani
Keyword(s):  
Cloud Computing ◽  
Dynamic Scheduling ◽  
Gabor Filter ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithm ◽  
Hybrid Metaheuristic ◽  
Opposition Based Learning ◽  
Independent Tasks

scholarly journals Load Balancing Algorithms in Cloud Computing

2020 ◽  
Author(s):  
Vignesh Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Dynamic Scheduling ◽  
The Internet ◽  
Heterogeneous Environment ◽  
Computing Technology ◽  
Cloud Systems ◽  
Internet Users ◽  
Independent Tasks

Cloud computing plays an important role in enhancing the effective sharing of resources in virtual machines. Scheduling and load balancing are the two common concepts that cloud computing relies on ensuring that a prescribed task is assigned to the most appropriate virtual machine. Also, cloud computing should have the ability to handle multiple independent tasks that are arriving and execute them in the same or multiple nodes. In a heterogeneous environment, static and dynamic scheduling plays an important role by enhancing the allocation of tasks to the appropriate resources to satisfy the internet users' requests and making cloud computing technology more efficient. This work aims to evaluate and discuss important algorithms that will help improve the load balancing performance of cloud systems.

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