Details

Autor(en) / Beteiligte

• Jangiti, Saikishor
• E, Sriram
• Jayaraman, Rohith
• Ramprasad, Harini
• Sriram, V S Shankar

Titel

Resource ratio based virtual machine placement in heterogeneous cloud data centres

Ist Teil von

• Sadhana (Bangalore), 2019-12, Vol.44 (12), p.1-6, Article 236

Ort / Verlag

New Delhi: Springer India

Erscheinungsjahr

2019

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Server consolidation through virtualization improves resource utilization significantly in Cloud Data Centres (CDCs). We study the case of a CDC hosting heterogeneous Physical Machines (PMs) as a variable size vector bin-packing problem. The PMs have different configurations of multiple resources like CPU, RAM, Disk Storage and Network Bandwidth. In this paper, we propose PMNeAR-vector heuristic for PM selection in PM-heterogeneity aware Virtual Machine (VM) initial placement. The proposed heuristic is compared with well-known heterogeneity aware FFD-DRR and BFD bin centric heuristics using a dataset with random instances of both VMs and PMs of heterogeneous configurations. Fifty rounds of VM initial placement simulation experiments were conducted to validate the average resource wastage. The results show that on average FFD-DRR and BFD bin centric heuristics are wasting 22.62% and 37.27% more resource units compared to the proposed PMNeAR-vector heuristic.