برنامه ریزی منابع چندگانه و شبیه سازی قدرت برای محاسبات ابر

Resource scheduling and energy consumption are the two of most significant problems in cloud computing. Owing to the scale and complexity of various resources, it is often difficult to conduct the theoretical analysis of the performance and power consumption of scheduling and resource provisioning algorithms on Cloud testbeds. Thus, simulation frameworks are becoming important ways to complete evaluation. CloudSim is one of the most popular and powerful simulation platforms for cloud computing. However, it requires much improvement to enable CloudSim to perform multi-resource or energy-aware simulations. To overcome this problem, we have extended CloudSim with a multi-resource scheduling and power consumption model, which allows more accurate valuation of power consumption in dynamic multi-resource scheduling. Extensive experiments on six combinations of task assignment algorithms and resource allocation algorithms demonstrate the powerful functionality and superior convenience of the extended CloudSim, MultiRECloudSim. Different task assignment and resource scheduling policies will bring about very different energy cost. We could easily repeat the experiment to find out the efficiency and the power consumption of the algorithms under diverse arguments with MultiRECloudSim.