A Bidirectional Ant Colony Optimization Algorithm for Cloud Load Balancing

• Main Authors: Li, Shin-Hung, 李欣鴻
• Other Authors: Hwang, Jen-Ing G.
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/92027290136220313256

碩士 === 輔仁大學 === 資訊工程學系碩士班 === 101 === The cloud computing is a technology that provides convenient, on demand network access to share computing resources. Although the cloud computing has many advantages, there exist some issues to be resolved such as load balancing. Load balancing is a technique and provides the mechanism to allocate an appropriate workload for each server in the system, and to maintain the stability if a node in the system fails. The Cloud environment is dynamic where tasks can be started and finished anytime. A dynamic response to the dynamic environment is required to consider, for example: how to effectively deal with a sudden and massive influx of tasks. Thus, our main goal of this thesis is to propose an effective scheduling for task allocation in Cloud environment. In recent years, some researches have used the Ant Colony Optimization (ACO) to resolve the load balancing problem in Cloud environment. In this thesis, we modify Li’s and Nishant’s methods to improve the ACO algorithm. Experiment results show that the proposed method indeed provides an efficient ACO to solve the load balancing problem in the Cloud.