Paper Info
Title
An Optimized Framework For Energy-Resource Allocation In A Cloud Environment Based On The Whale Optimization Algorithm
Abstract
Cloud computing offers the services to access, manipulate and configure data online over the web. The cloud term refers to an internet network which is remotely available and accessible at anytime from anywhere. Cloud computing is undoubtedly an innovation as the investment in the real and physical infrastructure is much greater than the cloud technology investment. The present work addresses the issue of power consumption done by cloud infrastructure. As there is a need for algorithms and techniques that can reduce energy consumption and schedule resource for the effectiveness of servers. Load balancing is also a significant part of cloud technology that enables the balanced distribution of load among multiple servers to fulfill users' growing demand. The present work used various optimization algorithms such as particle swarm optimization (PSO), cat swarm optimization (CSO), BAT, cuckoo search algorithm (CSA) optimization algorithm and the whale optimization algorithm (WOA) for balancing the load, energy efficiency, and better resource scheduling to make an efficient cloud environment. In the case of seven servers and eight server's settings, the results revealed that whale optimization algorithm outperformed other algorithms in terms of response time, energy consumption, execution time and throughput.
Year
DOI
Venue
2021
10.3390/s21051583
SENSORS
Keywords
DocType
Volume
load balancing, energy efficiency, resource scheduling, power consumption, cloud computing, whale optimization
Journal
21
Issue
ISSN
Citations 
5
1424-8220
1
PageRank 
References 
Authors
0.35
0
7
Name
Order
Citations
PageRank
Shanky Goyal110.35
Shashi Bhushan210.35
Yogesh Kumar310.35
Abu Ul Hassan S Rana410.35
Muhammad Raheel Bhutta510.69
Muhammad Fazal Ijaz6176.13
Youngdoo Son7111.25