A multi-agent approach to the monitoring of cloud computing system with dynamically changing configuration

Cloud based distributed systems rely on scheduling and resources allocation to function. In complex distributed systems a distribution of many jobs of different types is required. At the same time, a problem of virtual machines migration to physical servers must be solved. Therefore, configuration of a cloud system may be very dynamic, meaning that not only number of existing computational servers but also their location on physical servers might change. Optimal control strategies aimed to solve these problems are effective only when updated information about system's components is available. However, gathering this information from many distributed components of a cloud system, such as physical nodes or virtual machines may significantly decrease overall performance. These problems can be solved by applying different optimization techniques such as multi-agent approach. Agents decide if the information is outdated and needs to be updated by them. This paper describes a cloud system architecture that uses agents of different types. Agents' algorithms and their interaction schemes are defined. Software implementation in form of software environment is presented. Simulation experiments to compare performance of the system when using default monitoring methods and a multi-agent approach were conducted.