Hint Based Virtual Machine Placement in Cloud - Kadam, Pankaj; Alone, Nilesh (International Journal of Computer Sciences and Engineering, 2015)
the capacity of the cloud is allowing users to deploy complex infrastructure on the cloud due to huge pool of the resources offered by the cloud. In the infrastructure as service virtual machines are provided to the end users as the mean of the resource from the cloud. Complex application such as load balancing system or cluster system requires multiple virtual machines and their special connectivity for system realization. Current cloud providers do not allow users to deploy their complex workload. Users will need to deploy these virtual machines manually by selecting one at a time. In this paper we are proposing hint based virtual placement which accepts hints from the users and select the nodes from cloud. This system act as middleware between cloud provider and users and automate the complex workload deployment process. This system mutually understands the constraints placed by both users and cloud admins while deploying virtual machines. Such complex virtual machine deployment can be passed to the system using constraint like AssociateVM, DistantVM, BackupVM and PrivateNetVM. Cloud admins can also place constraints like out of service, backup node etc to influence the virtual machine placement. Our virtual machine scheduler considers these constraints from both the ends and selects the appropriate nodes on the basis of the constraints and scores assigned to the nodes. We have compared this strategy with available known cloud scheduler algorithms and found that available strategies do not allow any user passed hints while our algorithm allow users to pass such hints while deploying virtual machines.