SAACO: A Self Adaptive Ant Colony Optimization in Cloud Computing

2015 ◽  
Author(s):  
Weifeng Sun ◽  
Zhenxing Ji ◽  
Jianli Sun ◽  
Ning Zhang ◽  
Yan Hu
Keyword(s):  
Cloud Computing ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Self Adaptive

Task allocation based on ant colony optimization in cloud computing

2013 ◽  
Vol 32 (5) ◽  
pp. 1418-1420
Author(s):  
Chun-yan ZHANG ◽  
Qing-lin LIU ◽  
Ke MENG
Keyword(s):  
Cloud Computing ◽  
Ant Colony Optimization ◽  
Task Allocation ◽  
Ant Colony

A Novel Approach of Load Balancing and Task Scheduling Using Ant Colony Optimization Algorithm

2019 ◽  
Vol 7 (2) ◽  
pp. 9-20 ◽  
Author(s):  
Selvakumar A. ◽  
Gunasekaran G.
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Novel Approach ◽  
Productive Asset ◽  
Reduce Energy Consumption ◽  
Set Up

Cloud computing is a model for conveying data innovation benefits in which assets are recovered from the web through online devices and applications, instead of an immediate association with a server. Clients can set up and boot the required assets and they need to pay just for the required assets. Subsequently, later on giving a component to a productive asset administration and the task will be a vital target of Cloud computing. Load balancing is one of the major concerns in cloud computing, and the main purpose of it is to satisfy the requirements of users by distributing the load evenly among all servers in the cloud to maximize the utilization of resources, to increase throughput, provide good response time and to reduce energy consumption. To optimize resource allocation and ensure the quality of service, this article proposes a novel approach for load-balancing based on the enhanced ant colony optimization.

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