Resource Monitoring for Cloud Computing Environment
Li Ju · Shuxue de shijian yu renshi · 2014
To guarantee the reliability of the cloud platform,by employing Eucalyptus cloud platform,this paper proposes a resource monitoring model based on Ganglia for loud platform.The overall structure,work flow,and the prototype system performance evaluation are expatiated in detail.An algorithm which dynamically replaces cluster head for Ganglia is also proposed.Analysis and evaluation results show that the proposed system can be applied to real-time monitoring and warning of the resource information in a cloud environment with characteristics of low system overhead and user interface friendly,the system and virtual machine load information are accurately reflected,and it helps to prompt system service reliability.The proposed algorithm can discover the failing cluster head and replace it with robust virtual machine to guarantee monitoring system normally operating.