Cloud Data Center (DC) service orchestration and resource management are important applications of the Software Defined Networking (SDN) paradigm. In this paper, we introduce a novel dynamic allocation strategy for Virtual Machine (VM) allocation called Enhanced multi-objective Worst Fit (E-WF). E-WF combines the multi-objective Best Fit and Worst Fit allocation strategies, and it exploits the history of the previous requests to limit the resource fragmentation. We allocate the VMs choosing jointly a server and the least power-consuming network path. We show in our simulations that E-WF performs better and allocates more VMs with respect to the other presented approaches, and the power-aware network path allocation reduces the power consumption of network devices with respect to the classical shortest path first routing algorithm.
A novel allocation strategy for virtual machines in software defined data center
Portaluri, Giuseppe
;Adami, Davide;Giordano, Stefano;Pagano, Michele
2017-01-01
Abstract
Cloud Data Center (DC) service orchestration and resource management are important applications of the Software Defined Networking (SDN) paradigm. In this paper, we introduce a novel dynamic allocation strategy for Virtual Machine (VM) allocation called Enhanced multi-objective Worst Fit (E-WF). E-WF combines the multi-objective Best Fit and Worst Fit allocation strategies, and it exploits the history of the previous requests to limit the resource fragmentation. We allocate the VMs choosing jointly a server and the least power-consuming network path. We show in our simulations that E-WF performs better and allocates more VMs with respect to the other presented approaches, and the power-aware network path allocation reduces the power consumption of network devices with respect to the classical shortest path first routing algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
