Colocation data centers (colocations, for short) are developing rapidly and have become ideal participants for emergency demand response (EDR) programs. However, even colocation operators wish to save energy, they cannot achieve energy reduction without coordination from the tenants, because the servers in the colocations are owned and operated by the tenants. To solve the “uncoordinated relationship” issue between operators and tenants, some works have been done by way of incentivizing the tenants to reduce the energy consumption of their servers. However, apart from servers, the power consumption of the cooling system also accounts for a large portion in a colocation, which should be optimized as well. Unfortunately, the servers and the cooling system are controlled by tenants and operators separately in colocations, and thus “uncoordinated relationship” issue also exists between IT and cooling systems. In this paper, coarse-grained and fine-grained incentive mechanisms are proposed to solve these problems. Approximation algorithms are developed to optimize the energy-saving problems. Furthermore, Vickrey–Clarke–Groves (VCG) theory is introduced into our incentive mechanism design to guarantee the feasibility and truthfulness of the two mechanisms. Trace-driven simulations are performed to validate the effectiveness of the two incentive mechanisms. The results show that compared with the existing incentive mechanisms, up to 20.50% of the energy-saving cost can be reduced in the coarse-grained mechanism and 28.34% of the cost reduction can be achieved in the fine-grained mechanism.

托管数据中心（简称托管）正在迅速发展，并已成为应急需求响应（EDR）计划的理想参与者。但是，即使代管运营商也希望节省能源，他们也无法在没有租户协调的情况下实现节能，因为这些托管服务器是由租户拥有和运营的。为了解决运营商与租户之间的“不协调关系”问题，通过激励租户以减少其服务器的能耗来完成一些工作。但是，除了服务器之外，冷却系统的功耗在主机托管中也占很大一部分，这也应进行优化。不幸的是，服务器和冷却系统是由租户和运营商在同一地点分别控制的，因此，IT与冷却系统之间也存在“不协调的关系”问题。本文提出了粗粒度和细粒度激励机制来解决这些问题。开发了近似算法以优化节能问题。此外，Vickrey–Clarke–Groves（VCG）理论被引入我们的激励机制设计中，以确保这两种机制的可行性和真实性。进行跟踪驱动的仿真以验证这两种激励机制的有效性。结果表明，与现有的激励机制相比，在粗粒度机制中可以节省多达20.50％的节能成本，在细粒度机制中可以节省28.34％的成本。为了解决这些问题，提出了粗粒度和细粒度激励机制。开发了近似算法以优化节能问题。此外，Vickrey–Clarke–Groves（VCG）理论被引入我们的激励机制设计中，以确保这两种机制的可行性和真实性。进行跟踪驱动的仿真以验证这两种激励机制的有效性。结果表明，与现有的激励机制相比，在粗粒度机制中可以节省多达20.50％的节能成本，在细粒度机制中可以节省28.34％的成本。为了解决这些问题，提出了粗粒度和细粒度激励机制。开发了近似算法以优化节能问题。此外，Vickrey–Clarke–Groves（VCG）理论被引入我们的激励机制设计中，以确保这两种机制的可行性和真实性。进行跟踪驱动的仿真以验证这两种激励机制的有效性。结果表明，与现有的激励机制相比，在粗粒度机制中可以节省多达20.50％的节能成本，在细粒度机制中可以节省28.34％的成本。Vickrey–Clarke–Groves（VCG）理论被引入我们的激励机制设计中，以保证这两种机制的可行性和真实性。进行跟踪驱动的仿真以验证这两种激励机制的有效性。结果表明，与现有的激励机制相比，在粗粒度机制中可以节省多达20.50％的节能成本，在细粒度机制中可以节省28.34％的成本。Vickrey–Clarke–Groves（VCG）理论被引入我们的激励机制设计中，以保证这两种机制的可行性和真实性。进行跟踪驱动的仿真以验证这两种激励机制的有效性。结果表明，与现有的激励机制相比，在粗粒度机制中可以节省多达20.50％的节能成本，在细粒度机制中可以节省28.34％的成本。