Execution Time Compensation for Cloud Applications by Subtracting Steal Time based on Host-Level Sampling

Abstract

Accurate measurement of program execution time is indispensable to time-based charge systems and performance debugging in all computer systems. However, cloud application execution time cannot be measured properly because measurement in a virtual machine (VM) includes additional time called steal time. The steal time of each program in a VM is unrecognizable by existing standard operating system (OS) tools. Therefore, it is quite difficult for performance engineers to grasp the accurate execution time of each program in a VM. In this ongoing work, we show the novel point of steal in the broad sense and describe how to compensate for function-level execution time in each program in a VM. Our novel approach works by subtracting steal time, which is based on the time-series data of host-level sampling in each function. We implement our approach as a host-level kernel module based on hardware performance counters and some user-level analysis programs. Therefore, our method requires no modification of user applications, guest OSes, a virtual machine monitor (VMM) or a host OS. Finally, our results demonstrate accurate execution time of a function-level guest program, with an overhead lower than 1% for practical use.