A Method for Measuring Energy Consumption in IaaS Cloud

Subject Areas : Cloud, Cluster, Grid and P2P Computing

Derdus Kenga ¹ , Vincent Omwenga ² , Patrick Ogao ³

1 - Strathmore university
2 - Strathmore University
3 - Technical university of Kenya

Received: 2020-04-24 Accepted : 2020-07-15 Published : 2020-08-01

Keywords: Phoronix Test Suite, IaaS cloud, Energy measurement, RAPL, Energy efficiency,

Abstract :

The ability to measure the energy consumed by cloud infrastructure is a crucial step towards the development of energy efficiency policies in the cloud infrastructure. There are hardware-based and software-based methods of measuring energy usage in cloud infrastructure. However, most hardware-based energy measurement methods measure the energy consumed system-wide - including the energy lost in transit. In an environment such as the cloud, where energy consumption can be a result of different components, it is important to isolate the energy, which is consumed as a result of executing application workloads. This information can be crucial in making decisions such as workload consolidation. In this paper, we propose an experimental approach of measuring power consumption as a result of executing application workloads in IaaS cloud. This approach is based on Intel’s Running Average Power Limit (RAPL) interface. Application workload is obtained from Phoronix Test Suite (PTS)’ 7zip and aio-stress. To demonstrate the feasibility of this approach, we have described an approach, which can be used to study the effect of workload consolidation on CPU and I/O's power performance by varying the number of Virtual Machines (VMs) . Power is measured in watts. Performance of CPU is measured in Million Instructions per Second (MIPS) and I/O performance (as a result of processing data intensive) is measured in MB/s. Our results on the effect of workload consolidation has been compared with previous research and was found to be consistent. This shows that the proposed method of measuring power consumption is accurate.

References:

[1]     I. Salam, R. Karim and M. Ali, "Proactive dynamic virtual-machine consolidation for energy conservation in cloud data centres," Journal of Cloud ComputingAdvances, Systems and Applications, vol. 7, no. 1, 2018. 
[2]     D. Sara and M. Hicham, "An Adaptive Autonomic Framework for Optimizing Energy Consumption in the Cloud Data Centers," International Journal of Intelligent Engineering and Systems, vol. 12, no. 4, pp. 111-129, 2019. 
[3]     I. Azlan, "Energy-driven cloud simulation: existing surveys, simulation supports, impacts and challenges," Cluster Computing - Springer, 2020. 
[4]     Y. Maede, G. R. Akbar and H. F. Mohammad, "emperature and energy-aware consolidation algorithms in cloud computing.," Journal of Cloud Computing , vol. 8, no. 13, 2019. 
[5]     M. Made and B. Behzad, "A Simplified Method of Measurement of Energy Consumptionin Cloud and Virtualized Environment," in International Conference on Big Data and Cloud Computing, Sydney, 2014. 
[6]     A. Noureddine, "Adel Noureddine. Towards a Better Understanding of the Energy Consumption of Software Systems.," Lille University of Science and Technology, Lille , 2014.
[7]     G. Chaima, "Energy efficient resource allocation in cloud computing Enviroment," Institut National des T´el´ecommunications, Paris, France , 2014.
[8]     J. Smith and I. Sommerville, "Workload Classification & Software Energy Measurement for Efficient Scheduling on Private Cloud Platforms," in Conference’10 University of St Andrews, 2011. 
[9]     N. K. Kashif, M. Hirki, N. Tapio, N. Jukka and O. Zhonghong, "RAPL in Action:Experiences in Using RAPL for Power measurements," ACM Transactions on Modeling and Performance Evaluation of Computing Systems, vol. 9, 2018. 
[10]     F. Muhammad, S. Arsalan, R. M. Ravi and L. Alexey, "A Comparative Study of Methods for Measurement of Energy of Computing," Energies - mdpi, vol. 12, no. 11, 2019. 
[11]     Phoronix Test Suite, "Phoronix Test Suite - Linux Testing and Benchmarking Platform, Automated Testing, Open-Source Benchmarking," Phoronix Media, 2018. [Online]. Available: https://www.phoronix-test-suite.com/. [Accessed 01 February 2020].
[12]     Phoronix Test Suite, "7-Zip Compression Test profile," Phoronix Test Suite, 2020. [Online]. Available: https://openbenchmarking.org/test/pts/compress-7zip. [Accessed March 01 2020].
[13]     Phoronix Media, "AIO-Stress test profile," Phoronix Media, 2020. [Online]. Available: https://openbenchmarking.org/test/pts/aio-stress. [Accessed May 05 2020].
[14]     G. Rishu and T. S., "A systematic review on the various approaches used for achieving Energy consumption in Cloud," Test Engineering and Management, vol. 82, pp. 3936 - 3953, 2020. 
[15]     M. Alexis and M.-M. Vania, "Automatic benchmark profiling through advanced workflow-based trace analysis," Practice and Experience, Wiley, vol. 48, no. 6, pp. 1195-1217, 2018. 
[16]     M. Made and Y. Pujianto, "Evaluating Energy Consumption in a Different Virtualization within a Cloud System," in 4th International Conference on Science and Technology , Yogyakarta, Indonesia, 2018. 
[17]     CSC, "Taito supercluster," CSC, 2020. [Online]. Available: https://research.csc.fi/guides. [Accessed 15 MArch 2020].
[18]     S. Yu, H. Yang, R. Wang, Z. Luan and D. Qian, "Evaluating architecture impact on system energy efficiency," PLoS ONE, vol. 12, no. 11, 2017. 
[19]     A. Ibrahim, D. Karim, A. Django and K. Richard, "Energy-Aware Profiling for Cloud Computing Environments," Electronic Notes in Theoretical Computer Science, vol. 318, pp. 91-108, 2015. 
[20]     Zabbix LLC, "Zabbix:: The Enterprise-Class Open Source Network Monitoring Solution," Zabbix , 2020. [Online]. Available: https://www.zabbix.com/. [Accessed March 01 2020].
[21]     T. Makris, "Measuring and Analyzing Energy Consumption," Aalto University, Espoo, Finland, 2017.
[22]     Phoronix Test Suite , "Phoronix Test Suite - Benchmarking Linux with Phoronix Test Suite - Lots of command line examples," Phoronix Test Suite , 2018. [Online]. Available: https://wiki.mikejung.biz/Phoronix_Test_Suite . [Accessed March 01 2020].
[23]     Phoronix Test Suite, "Phoromatic: Automated Linux Benchmark Management & Test Orchestration," Phoronix Test Suite, 2018. [Online]. Available: http://www.phoronix-test-suite.com/index.php?k=phoromatic#phoromatic. [Accessed 01 March 2020].
[24]     C.-Z. Mar, S. Lavinia, O. Anne-Cécile and P. Guillaume, "An experiment-driven energy consumption model for virtual machine management systems," Sustainable Computing: Informatics and Systems, vol. 18, pp. 163-174, 2018. 
[25]     C. HeeSeok, L. JongBeom, Y. Heonchang and E. Lee, "Task Classification Based Energy-Aware Consolidation in Clouds," Scientific Programming , vol. 2016, 2016. 
[26]     A. Mirabel and R. Siddiqui, "Energy Aware Consolidation in Cloud Computing," California State University, 2015.
[27]    M. David, G. Brian and W. Thomas, "PowerNap: Eliminating Server Idle Power," in Proceedings of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2009, Washington, DC, USA, 2009. 
[28]    X. Chen, L. Rupprecht, R. Osman, P. Pietzuch, F. Franciosi and W. Knottenbelt, "CloudScope: Diagnosing and Managing Performance Interference in Multi-tenant Clouds," in 2015 IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2015