Bulk-bin-packing based migration management of reserved virtual machine requests for green cloud computing

Abstract

The dynamic consolidation of Virtual Machines (VMs) into a minimum number of Physical Machines (PMs) is a key energy-efficient practice in a cloud data centre, to reduce the running PMs and save electricity costs. We proposed a migration based VM consolidation approach for reserved requests. Real Dataset EC2 was used in the simulation experiments. The proposed BBPMM has demonstrated the elastic capability of adjusting the running PMs and it reduced 38% of running PMs in a reservation transition period.

Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers

“…In our recent works, we proposed the following VM placement heuristics FFD-Aggregated rank [15], MCBVP [16], PMNeAR-Vector [17], BBPMM [18] and ENSEMBLE-HIDE-SPADE [19]. Best Fit Decreasing algorithm sorts the VM requests in descending order and allocates the largest VM first to active PM that gives the minimum residue.…”

Master-Slave TLBO Algorithm for Constrained Global Optimization Problems

“…Jangiti et al used a heuristic approach to perform virtual machine placement in the heterogeneous cloud data centre [8]. Jangiti et al presented bulk-bin-packing based migration management approach to address the reserved virtual machine request problem in green cloud computing [9]. Tian et al have used a heuristic approach for scheduling of virtual machine reservations in cloud data centres [10].…”