Extending Demand Response to Tenants in Cloud Data Centers via Non-intrusive Workload Flexibility Pricing

TL;DR

This paper introduces UPMR, a non-intrusive pricing mechanism for cloud data centers that incentivizes tenants to set workload deadlines, reducing energy costs and increasing profits without complex dynamic pricing.

Contribution

The paper proposes UPMR, a simple, long-term incentive mechanism that aligns tenant workload deadlines with energy cost savings in cloud data centers.

Findings

UPMR reduces energy costs by 12.9%.

UPMR increases CDC profit by 4.9%.

The mechanism is effective both analytically and empirically.

Abstract

Participating in demand response programs is a promising tool for reducing energy costs in data centers by modulating energy consumption. Towards this end, data centers can employ a rich set of resource management knobs, such as workload shifting and dynamic server provisioning. Nonetheless, these knobs may not be readily available in a cloud data center (CDC) that serves cloud tenants/users, because workloads in CDCs are managed by tenants themselves who are typically charged based on a usage-based or flat-rate pricing and often have no incentive to cooperate with the CDC operator for demand response and cost saving. Towards breaking such "split incentive" hurdle, a few recent studies have tried market-based mechanisms, such as dynamic pricing, inside CDCs. However, such mechanisms often rely on complex designs that are hard to implement and difficult to cope with by tenants. To address this limitation, we propose a novel incentive mechanism that is not dynamic, i.e., it keeps pricing for cloud resources unchanged for a long period. While it charges tenants based on a Usage-based Pricing (UP) as used by today's major cloud operators, it rewards tenants proportionally based on the time length that tenants set as deadlines for completing their workloads. This new mechanism is called Usage-based Pricing with Monetary Reward (UPMR). We demonstrate the effectiveness of UPMR both analytically and empirically. We show that UPMR can reduce the CDC operator's energy cost by 12.9% while increasing its profit by 4.9%, compared to the state-of-the-art approaches used by today's CDC operators to charge their tenants.