Online Pricing and Resource Scheduling for Profit Maximization of Cloud Storage Providers

Abstract

There is increasing competition among cloud object storage service (COSS) providers as the demand for COSSs grows. However, existing pricing models offered by commercial COSS providers fail to effectively adapt to changing client demand and resource supply. Consequently, many COSS providers are still grappling with operational challenges in maximizing their profits, such as pricing policy, load balancing, server scheduling, and energy management. In this paper, we propose a novel approach called time-dependent pricing and scheduling ( TD-PnS ), which is based on the Lyapunov-drift-minus-profit technique. To maximize the profits of COSS providers, TD-PnS enables joint and dynamic decision-making across several key factors that have been dealt with separately so far: (i) service pricing, (ii) CPU clock scaling and encoding scheduling, (iii) network scheduling, and (iv) energy storage management. We propose an enhanced version of TD-PnS , called TD-PnS-Adv , further to improve other aspects, such as system stabilization. Finally, through trace-driven simulations utilizing a real dataset, we demonstrate the superior performance of the proposed algorithms compared to existing algorithms and pricing models in terms of profit maximization.