Monitoring is a precondition for intelligent management in cloud computing environment, such as dynamic resource allocation. Typically, working as an auxiliary tool, a monitoring system is expected to incur the least additional resource usage, thus the strategies to improve the efficiency of monitoring mechanisms become significant. Yet the scale and monitoring requirement of different data centers vary, we cannot determine whether a monitoring mechanism would work well in a new data center before it serves the data center. To evaluate monitoring mechanisms, we propose SimMon, a toolkit for simulating monitoring mechanisms in cloud computing environments. SimMon is designed to simulate the topologies, actions, and strategies in data collection, dissemination, storage, and management processes. SimMon provides a controllable and repeatable way to evaluate monitoring mechanisms. In this paper, we describe the requirements analysis, design, implementation, and evaluation of SimMon. We simulate several different monitoring systems and compare their cost on time and resource to evaluate the efficiency of SimMon. We reproduce two usage scenarios from former literatures to demonstrate the effectiveness of SimMon on monitoring mechanisms simulation and evaluation. We build a real-world working environment to validate the capability of SimMon on mimicking the characteristics of cloud monitoring systems. knowledge with the least additional cost [4]. For ease of presentation, we will use monitoring mechanism to uniformly represent the architecture and strategies employed in cloud monitoring systems in the rest of this paper.Fueled up by the explosive growth of services in cloud computing environment, traditional predesigned and suit-to-all monitoring mechanisms are not efficient enough for cloud monitoring systems for three reasons: (1) The number of monitoring target becomes huge, which makes the traditional centralized monitoring structure incapable to efficiently coordinate dispersed collection agents. An efficient and distributed structure for collection agents management is required to ensure the performance of monitoring systems [5].(2) The volume of data that are disseminated across data centers is large, which incurs much more extra network pressure [6]. To eliminate the network pressure, intelligent strategies (e.g., dynamic change on the monitoring target, monitoring interval, and data poll strategy) are necessary to process the monitoring data [7]. (3) In cloud computing environment, services are located on different infrastructures across several different areas, which makes the underlying network structure complex. It is imperative to design new protocols to provide efficient solutions for monitoring data storage and requisition to ensure the high performance and high availability of cloud monitoring systems [8].Considering the aforementioned reasons, it is vital to design intelligent and effective mechanisms for cloud monitoring systems according to the network structure, load characteristics, resource constra...