Abstract
A hypervisor is a hardware virtualization technique that allows multiple guest operating systems to run on a single host machine at the same time. Each Virtual Machine (VM) or known as guest operating system emulates all interfaces and resources of a real computer system. Virtualization is beneficial as one of the educational tools to facilitate students’ hands-on experiences and research activities. However, the performance of VM needs to be taken into consideration. We investigate the performance of a set of VMs using Oracle VirtualBox on several host machines, each of which has its own system specifications. We observe the resource utilization of each host machine in terms of its CPU utilization, CPU speed as well as memory usage. Experimental results show that the CPU utilization averages are 51.78%, 60.7% and 62.57% for cases before memory allocation, 1/2 of memory capacity and 2/3 of memory capacity, respectively. It is indicate that the utilization of a host processor is directly proportional to the memory capacity assigned for a virtual machine.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Smith JE, Nair R (2007) Introduction to virtual machines. Virtual Machines. Elsevier, pp 1–26
Nabhen R, Maziero C (2006) Some experiences in using virtual machines for teaching computer networks. In: Education for the 21st century—impact of ICT and digital resources, pp 93–104
Mateljan V, Juricic V, Moguljak M (2014) Virtual machines in education. In: 37th International convention on information and communication technology, electronics and microelectronics (MIPRO), pp 603–607
Nieh J, Vaill C (2005) Experiences teaching operating systems using virtual platforms and linux. ACM SIGCSE Bull 37(1):520–524
Gulati A, Holler A, Ji M, Shanmuganathan G, Waldspurger C, Zhu X (2012) Vmware distributed resource management: Design, implementation, and lessons learned. VMware Tech J 1(1):45–64
Tao J, Furlinger K, Wang L, Marten H (2012) A performance study of virtual machines on multicore architectures. In: 2012 20th Euromicro international conference on parallel, distributed and network-based processing, pp 89–96
Chen PM, Noble BD (2001) When virtual is better than real [operating system relocation to virtual machines]. In: Proceedings eighth workshop on hot topics in operating systems, pp 133–138
Gilbert L et al (2005) Performance implications of virtualization and hyper-threading on high energy physics applications in a grid environment. In: 19th IEEE international parallel and distributed processing symposium, p 10
Hahm O, Baccelli E, Petersen H, Tsiftes N (2015) Operating systems for low-end devices in the internet of things: a survey. IEEE Internet Things J 3(5):720–734
Masdari M, Nabavi SS, Ahmadi V (2016) An overview of virtual machine placement schemes in cloud computing. J Netw Comput Appl 66:106–127
Joy AM (2015) Performance comparison between linux containers and virtual machines. In: 2015 International conference on advances in computer engineering and applications. IEEE, pp 342–346
Sharma P, Chaufournier L, Shenoy P, Tay YC (2016) Containers and virtual machines at scale: a comparative study. In: Proceedings of the 17th international middleware conference. ACM, p 1
Ahmad RW, Gani A, Hamid SHA, Shiraz M, Yousafzai A, Xia F (2015) A survey on virtual machine migration and server consolidation frameworks for cloud data centers. J Netw Comput Appl 52:11–25
Arianyan E, Taheri H, Sharifian S (2015) Novel energy and SLA efficient resource management heuristics for consolidation of virtual machines in cloud data centers. Comput Electric Eng 47:222–240
Piraghaj SF, Calheiros RN, Chan J, Dastjerdi AV, Buyya R (2015) Virtual machine customization and task mapping architecture for efficient allocation of cloud data center resources. Comput J 59(2):208–224
Khan MA, Paplinski A, Khan AM, Murshed M, Buyya R (2018) Dynamic virtual machine consolidation algorithms for energy-efficient cloud resource management: a review. In: Sustainable cloud and energy services. Springer, Cham, pp 135–165
Gupta MK, Amgoth T (2018) Resource-aware virtual machine placement algorithm for IaaS cloud. J Supercomput 74(1):122–140
Toosi AN, Sinnott RO, Buyya R (2018) Resource provisioning for data-intensive applications with deadline constraints on hybrid clouds using Aneka. Futur Gener Comput Syst 79:765–775
Acknowledgments
The authors express appreciation to the Ministry of Higher Education (MOHE) and Universiti Tun Hussein Onn Malaysia (UTHM). This research is supported by the Fundamental Research Grant Scheme (FRGS) grant (Vot 1640)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kamaludin, H., Jamal, M.Y., Rahman, N.H.A., Safar, N.Z.M., Ishak, S.A. (2020). Implementing Virtual Machine: A Performance Evaluation. In: Ghazali, R., Nawi, N., Deris, M., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2020. Advances in Intelligent Systems and Computing, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-030-36056-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-36056-6_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36055-9
Online ISBN: 978-3-030-36056-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)