Cost and deadline optimization along with resource allocation in cloud computing environment

Cloud computing is the technology of next generation which combines everything into one. In Cloud computing a large number of cloud users can request a number of cloud services at the same time. So there must be a way in which all the resources are made available to the requesting user in a good manner to satisfy their needs. The mechanism of allocating available resources to the needed cloud applications through the internet is called Resource Allocation. Resource Allocation when done in conjunction with user annotations as introduced in this paper can reduce the cost incurred for a user and hence it can attract more cloud users in future. User annotations like cost, deadline can be used. Users are allowed to submit the parameters during job submission. The user inserted parameters will then be considered while allocating resources to them. The main purpose of this paper is to increase information sharing among Cloud Users and Cloud Providers and thus provide benefits to users in terms of the user annotated parameters.

[1]  Gunho Lee,et al.  Resource Allocation and Scheduling in Heterogeneous Cloud Environments , 2012 .

[2]  Raouf Boutaba,et al.  Dynamic Resource Allocation for Spot Markets in Clouds , 2011, Hot-ICE.

[3]  Andrzej Kochut,et al.  Dynamic Placement of Virtual Machines for Managing SLA Violations , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[4]  Ronak Patel,et al.  Survey on Resource Allocation Strategies in Cloud Computing , 2013 .

[5]  Weijia Song,et al.  An Infrastructure-as-a-Service Cloud: On-Demand Resource Provisioning , 2013 .

[6]  Kwang Mong Sim,et al.  A Price- and-Time-Slot-Negotiation Mechanism for Cloud Service Reservations , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Zhen Xiao,et al.  Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment , 2013, IEEE Transactions on Parallel and Distributed Systems.