Real Time Metering of Cloud Resource Reading Accurate Data Source Using Optimal Message Serialization and Format

In this paper the technology of collecting the logs and the logs message format is considered in addition to investigating multiple log data sources as an input to the cloud management system. A comparison between message exchange technologies (JSON, XML) is evaluated with the latest message format technology (Google Protocol Buffer) when used in combination with the message transmission protocols (XML-RPC, REST, Network Socket). In addition, the sampling rate that gives the accurate reading of resource usage is investigated, which is used to select among different log data sources to achieve the accurate log update time. Logs sampling rate of 1.0 second is found to be the best with "xentop" data source. The result of the experiment shows using Protocol Buffer with Socket protocol gives the best results in reducing message size. Network socket with JSON gives the best processing delay and traveling time.