MOTS‐ACO: An improved ant colony optimiser for multi‐objective task scheduling optimisation problem in cloud data centres
Abstract Task scheduling in cloud data centres is an optimisation problem that aims to minimise power consumption and task makespan as well as ensures the quality of service delivered to cloud consumers. Although there are several existing task scheduling approaches, these methods mainly focus on op...
Main Authors: | Elsayed Elsedimy, Fahad Algarni |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-03-01
|
Series: | IET Networks |
Subjects: | |
Online Access: | https://doi.org/10.1049/ntw2.12033 |
Similar Items
-
HWACOA Scheduler: Hybrid Weighted Ant Colony Optimization Algorithm for Task Scheduling in Cloud Computing
by: Chirag Chandrashekar, et al.
Published: (2023-03-01) -
The Unrelated Parallel Machine Scheduling with a Dependent Time Setup using Ant Colony Optimization Algorithm
by: Farida Pulansari, et al.
Published: (2021-06-01) -
Multi objective trust aware task scheduling algorithm in cloud computing using whale optimization
by: Sudheer Mangalampalli, et al.
Published: (2023-02-01) -
Effective task scheduling based on interactive autodidactic school algorithm for cloud computing
by: G. Senthilkumar, et al.
Published: (2024-01-01) -
A Novel Fault-Tolerant Aware Task Scheduler Using Deep Reinforcement Learning in Cloud Computing
by: Mallu Shiva Rama Krishna, et al.
Published: (2023-11-01)