Resource Allocation in Cloud Computing Using Online Auction Mechanism driven by popularity based allocation

Abstract

Cloud computing is a mode of rising, using and presenting related services as stated in the Internet. It normally is providing energetic, scalable and virtualized resources over the Internet. Due to the limitation we have in available resources, effective allocation of available virtual resources would be a biggest challenge in cloud computing. So Cloud providers are moving in the direction of auctioning cloud resources instead of leasing them with stabled prices. Unlike the usual auction mechanism, here we   predict the popular resource by using the concept of The Popular Compatible Auction Mechanism (PCAM) supports effective allocation of resources during auction. This mechanism enables to predict the populared resource in large dataset. The process involves following sequence of activities, i.e. prediction of popular resources using time series analysis, resource creation based on prediction and allocation of auction based resources using PCAM. The scheme anticipates increased traffic with popularity. We conduct an experiment to exhibit our method show that the adaptive auction-based scheduling is able to productively magnify the quality of service, profit of Cloud service provider and resource utilization.