Performance Evaluation of Job Scheduling Techniques Incorporating the Ondemand Governor Policy

온디맨드 거버너 정책에 따른 작업 스케줄링 기법의 성능 평가

  • Received : 2015.05.19
  • Accepted : 2015.07.10
  • Published : 2015.08.20


The ondemand governor used in android-based smartphone platforms is a CPU frequency scaling technique. The ondemand governor sets the CPU operating frequency depending on the CPU utilization rate. Job scheduling affects the CPU utilization rate. The power consumption is proportional to the value of operating frequency. Consequently, CPU frequency scaling and CPU utilization rate have an effect on power consumption in a smartphone. In this paper, we evaluated the performance of job scheduling techniques incorporating the ondemand governor in terms of CPU utilization, power consumption, and job deadline miss ratio.


Ondemand governor;Android;Smartphone;Power consumption;Job scheduling


  1. R. Murmuria, J. Medsger, A. Stavrou, and J.M.Voas, “Mobile application and device power usage measurements,” in Proceedings of International Conference on Software Security and Reliability, Gaithersburg:USA, pp. 147-156, 2012.
  2. K. Nagata, S. Yamaguchi, and H. Ogawa, “A Power Saving Method with Consideration of Performance in Android Terminals,” in Proceedings of International Conference on Autonomic & Trusted Computing, Fukuoka:Japan, pp. 578-585, 2012.
  3. F. Cottet, J. Delacroix, C. Kaiser, and Z. Mammeri, Scheduling in Real-Time Systems, Wiley, 2002.
  4. A. Mazouz, A. Laurent, B. Pradelle, and W. Jalby, “Evaluation of CPU frequency transition latency,” Computer Science - Research and Development, vol. 29, no. 3-4, pp. 187-195, Aug. 2014.
  5. V. Pallipadi and A. Starikovskiy, “The Ondemand Governor,” in Proceedings of Linux Symposium, Ottawa, Canada, pp. 223-228, 2006.
  6. P. Pillai and K.G. Shin, “Real-Time dynamic voltage scaling for low-power embedded operating systems,” in Proceedings of ACM symposium on Operating Systems Principles, pp. 89-102, 2001.
  7. S. Tak, “Performance evaluation of real-time power-aware scheduling techniques incorporating idle time distribution policies,” Journal of the Korea Institute of Information and Communication Engineering, vol. 18, no. 7, pp. 1704-1712.
  8. M. Kim, Y. Kim, S. Chung, and C. Kim, “Measuring variance between smartphone energy consumption and battery life,” IEEE Computer Magazine, vol. 47, no. 7, pp.59-65, 2014.
  9. D. Brodowski and N. Golde, Linux CPUFreq Governors [Internet]. Available:
  10. M.J. Johnson, and K.A. Hawick, “Optimizing energy management of mobile computing devices,” in Proceedings of International Conference on Computer Design, Las Vegas, USA, pp. 1-7, 2012.