A QoS-based technique for load balancing in green cloud computing using an artificial bee colony algorithm
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Date
2023
Authors
Milan, Sara Tabagchi
Navimipour, Nima Jafari
Bavil, Hamed Lohi
Yalcin, Senay
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor & Francis Ltd
Abstract
Nowadays, high energy amount is being wasted by computing servers and personal electronic devices, which produce a high amount of carbon dioxide. Thus, it is required to decrease energy usage and pollution. Many applications are utilised by green computing to save energy. Scheduling of tasks acts as an important process to reach the mentioned goals. It is worth stating that the vital characteristic of task scheduling in green clouds is the load balancing of tasks on virtual machines. Efficient load balancing moves tasks from overloaded to underloaded virtual machines to maintain the Quality of Service (QoS). This issue is an NP-complete problem, so this research suggests a new technique based on the behavioural structure of artificial bee behaviour. This method aims to improve QoS while lowering energy usage in green computing. In addition, the honey bees are considered the removed tasks from overloaded virtual machines and a candidate for migrating selected tasks with the lowest priority. The CloudSim testing findings demonstrate that the technique is successful in QoS, makespan, and energy usage compared to other ways.
Description
Keywords
Scheduling Algorithm, Allocation, Framework, System, Tasks, 5g, Scheduling Algorithm, Allocation, Framework, Green computing, System, load balancing, Tasks, artificial bee colony, 5g, cloud computing
Turkish CoHE Thesis Center URL
Citation
0
WoS Q
N/A
Scopus Q
Q3
Source
Journal of Experimental & Theoretical Artificial Intelligence