Online Auctions in IaaS Clouds : Welfare and Profit Maximization with Server Costs

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Online Auction in laaS Clouds Welfare and Profit Maximization With Server Costs

Online Auctions in IaaS Clouds : Welfare and Profit Maximization with Server Costs

Abstract

In this project Online Auctions in IaaS Clouds: Welfare and Profit Maximization Cloud users bid for resources in the future to assemble customized VMs with desired occupancy, possibly located in different data centers.The cloud provider dynamically packages multiple resource types into the requested VMs on heterogeneous physical machines (servers).Social welfare and the net profit of the cloud provider shall be maximized over the running span of the system.

Introduction

AS Infrastructure-as – a-Service(IaaS) clouds are proliferating in today’s Internet as a major model in cloud computing services. Online Auctions in IaaS Clouds Major IaaS providers today typically offer pre-configured instances of fixed types of VM.

While the granularity of resource provisioning continues to improve, fixed pricing remain dominant in practice.Despite the apparent simplicity, fixed price policies inherently lack market agility and efficiency, jeopardizing the profit of the provider and the utility of customers.

Auctions have recently been designed to improve market-based pricing for cloud resource allocation.

Online Auctions in IaaS Clouds: Welfare and Profit Maximization With Server Costs

Conclusion

Our primal-dual framework adopts a new Fenchel duality application and handles various convex server cost functions. It also allows request departures and resource recycling while ensuring good competitive ratios.

In order to maximize profit, we are introducing a new online primal-dual analysis to obtain good competitive ratios with super-linear server costs, which is new in the literature.Welfare maximization and profit maximization for cloud providers.

In This project Our primal-dual framework adopts a new Fenchel duality application and handles different convex server cost functions.