Performance Analysis of QoS-Differentiated Pricing in Cloud Computing: An Analytical Approach

TL;DR

This paper introduces an analytical framework for QoS-differentiated pricing in cloud computing, optimizing SLA prices and server allocation to maximize provider revenue while maintaining usability.

Contribution

It presents the first analytical model for QoS-based resource management and pricing in cloud services, with optimal schemes for pricing and capacity planning.

Findings

Up to five-fold revenue increase with proposed scheme

Optimal SLA pricing and capacity allocation in polynomial time

Enhanced usability compared to standard pricing models

Abstract

A fundamental goal in the design of IaaS service is to enable both user-friendly and cost-effective service access, while attaining high resource efficiency for revenue maximization. QoS differentiation is an important lens to achieve this design goal. In this paper, we propose the first analytical QoS-differentiated resource management and pricing architecture in the cloud computing context; here, a cloud service provider (CSP) offers a portfolio of SLAs. In order to maximize the CSP's revenue, we address two technical questions: (1) how to set the SLA prices so as to direct users to the SLAs best fitting their needs, and, (2) determining how many servers should be assigned to each SLA, and which users and how many of their jobs are admitted to be served. We propose optimal schemes to jointly determine SLA-based prices and perform capacity planning in polynomial time. Our pricing model retains high usability at the customer's end. Compared with standard usage-based pricing schemes, numerical results show that the proposed scheme can improve the revenue by up to a five-fold increase.