The Android operating system has become one of the most popular platforms in mobile devices with a market share of 86.2 % in Q2 2016 [1]. This operating system supports a very large number of applications that are provided on application distributing sites by operating system developers [2], career services [3][4], and others. Monitoring application behavior is important for various reasons, such as security purposes [5] or the estimation of power consumption [6]. Battery-draining applications can be identified effectively by monitoring the number of times WakeLock is acquired and Alarm is set [7][8]. In addition, some application distributing sites conduct application analyses as a service for users [5]. In addition, monitoring application behavior is an important process used by application developers to verify their own applications. Therefore, it is important to actually execute an application when assessing its behavior. However, analyses based on actual executions are highly time consuming [6][7][8]. Naturally, monitoring the behavior of an application over the course of one day takes 24 hours. We previously proposed a method to overcome this problem by constructing an accelerated environment [9][10][11], which was achieved by modifying the implementation of time flow management in the operating system kernel. These studies demonstrated that this method was accurate for low acceleration ratios, such as twice the usual operating speed. However, the method has not been evaluated for high ratios, such as ten or one hundred times. This paper introduces an accelerating method and presents an evaluation of its stability and accuracy with high acceleration ratios. We then describe the problems associated with stability-based evaluation. We explore the causes of system instability and explain our findings, namely that timers in the system are one of the important reasons. Finally, we describe the results we obtained after disabling these timers and investigating the effect of this solution on the system stability.