Resource allocation using Dynamic Pricing Auction Mechanism for supporting emergency demands in Cloud Computing

Abstract

Cloud resources provide various categories of (VM) virtual machine requests which is assigned with clients for an exact timespan. Currently, the method of VM scheduling within the Cloud environment is decided by a fixed-price scheduling algorithm, during which the user pays a fixed amount per unit time so as to obtain the resources. However, such a scheduling algorithm is not effective for Cloud even though the Cloud resources are dynamically allocated and released. To address this issue, the adaptive scheduling algorithm called as Dynamic pricing based Combinatorial Auction allocation mechanism is proposed. It will be used to increase the resource utilization as well as user satisfaction through dynamic pricing with the combinatorial auction. Our proposed market-based scheduling algorithm uses the principle of auction mechanism for the purpose of extends the satisfaction of Cloud suppliers and clients. This technique reconstructs the current preferences of resource allotment so as to allot resources in advance for emergent virtual machine demands. Then Collective-target augmentation numerical prototype is demonstrated, which forms the minimal execution equivalent range connecting physical machines with virtual machines, and the objective of resource allotment is to obtain minimal quantity of physical machines. The simulation experimental outcomes express that the proposed scheduling methodology and Collective-target augmentation numerical prototypes are capable to adequately increase the quality of service (QoS), improves profit of suppliers and resource utilization.