Energy Efficient Dynamic Resource Scheduling for Cloud Data Center
Massive scale cloud data centers host many applications and comprise of millions of servers thus consuming more power than ever. In order to efficiently manage the power usage of these data centers, Green computing offers schemes like load balancing across physical machines, live migration of virtual machines and Sever Consolidation which aims at minimizing the number of Active Physical Machines (APM) Server consolidation is a result of Virtual Machine (VM) scheduling which involves VM selection, VM placement and VM placement re optimization. In this paper, we present a VM placement optimization technique used in green cloud, particularly based on the classical problem of Bin Packing. Bin packing is inspired by the NP Hard knapsack problem and reduces the total number of Active Physical Machines (APM) Further these placements are optimized using Rank based VM scheduling algorithm. The proposed approach subsequently reduces the energy consumption and provides improved server consolidation. Keywords Cloud Computing, Data Center, Load Balancing, Server Consolidation, Virtual Machine