Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering

Consumer behavior algorithm for cloud computing based on ant colony optimization algorithm

Authors
Wuling Ren, Huixiang Lv, Guoxin Jiang
Corresponding Author
Wuling Ren
Available Online March 2014.
DOI
https://doi.org/10.2991/mce-14.2014.38How to use a DOI?
Keywords
Consumer preference; cloud computing; ant colony algorithm; consumer behavior; customer satisfaction
Abstract
In the current and social market economy of our country, cloud computing is gradually get better development. However, there is no charges related to cloud computing, cost directly affects the resource utilization of enterprises and satisfaction of users. Load the network situation of the ant colony algorithm to simulate the operation of the network, but to solve the balance and traffic load of the network congestion is incapable of action. For the above problems, the author puts forward an improved ant colony algorithm, the relevant data for consumer behavior in the use of ant colony algorithm, scheduling, use of consumer behavior to help to solve the problem of network load, so as to achieve the goal of rational use of cyber source. The improved algorithm mentioned in this article, on-time performance is better than the ant colony algorithm. Meanwhile, the authors introduced a consumer preference factor, making scheduling more flexible cloud computing and intelligent. In addition to the authors propose a new model that can help users more involved in the cloud were to go, so to find a maximization of their own interests.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2014
ISBN
978-94-62520-31-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/mce-14.2014.38How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wuling Ren
AU  - Huixiang Lv
AU  - Guoxin Jiang
PY  - 2014/03
DA  - 2014/03
TI  - Consumer behavior algorithm for cloud computing based on ant colony optimization algorithm
BT  - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
PB  - Atlantis Press
SP  - 173
EP  - 177
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.38
DO  - https://doi.org/10.2991/mce-14.2014.38
ID  - Ren2014/03
ER  -