Open AccessFine Tuning of Rank Based VM Placement and Scheduling Strategies on Opennebula Based Cloud
Author(s) -
Shreesudha Kembhavi*,
S. P. Nigam
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e4836.018520
Subject(s) - computer science , cloud computing , hypervisor , scheduling (production processes) , leverage (statistics) , virtual machine , distributed computing , virtualization , host (biology) , computer network , operating system , engineering , ecology , operations management , machine learning , biology
The HPC Clouds are good option over deploying actual physical infrastructure. This helps in running applications efficiently and in cost effective manner as applications leverage resources in pay as you go manner. But HPC clouds suffer performance issues due to Hypervisor layer. This work addresses the issue by coming up with a VM placement strategy considering the intensity of the applications and also resources available in the host machines and avoid performance degradation of parallel running applications. This placement strategy identifies the and ranks the available host machines and places the maximum possible VMs in highest ranking nodes. This avoids communication over the network since the VMs use shared memory for communication.