Consumer behavior algorithm for cloud computing based on ant colony optimization algorithm
Wuling Ren, Huixiang Lv, Guoxin Jiang
Available Online March 2014.
- https://doi.org/10.2991/mce-14.2014.38How to use a DOI?
- Consumer preference; cloud computing; ant colony algorithm; consumer behavior; customer satisfaction
- 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.
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 -