A Truthful and Efficient Incentive Mechanism for Demand Response in Green Datacenters

Zhou, Zhi; Liu, Fangming; Chen, Shutong; Li, Zongpeng

doi:10.1109/tpds.2018.2882174

Cited by 40 publications

(12 citation statements)

References 27 publications

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“…Power and thermal management in datacenters: Due to the rapid growth of cloud and edge computing, Internet of things, deep learning, etc., the power consumption of IT and cooling equipment in datacenters increases dramatically in recent years [23,37]. To improve the overall efficiency, many works pay close attention to power and thermal management in datacenters, such as workload management [34,40,49,53,57,72,113,115,116], hotspot elimination [41,55], underprovisioning [58,111], heat harvesting [14,54,118], and demand response [13,114]. In this section, we summarize some closely related works on the hotspot issue and/or cooling efficiency.…”

Section: Related Workmentioning

confidence: 99%

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Pei

Chen

Zhang

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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As the computing frontier drifts to the edge, edge datacenters play a crucial role in supporting various real-time applications. Different from cloud datacenters, the requirements of proximity to end-users, high density, and heterogeneity, present new challenges to cool the edge datacenters efficiently. Although warm water cooling has become a promising cooling technique for this infrastructure, the one-size-fits-all cooling control would lower the cooling efficiency considerably because of the severe thermal imbalance across servers, hardware, and even inside one hardware component in an edge datacenter. In this work, we propose CoolEdge, a hotspot-relievable warm water cooling system for improving the cooling efficiency and saving costs of edge datacenters. Specifically, through the elaborate design of water circulations, CoolEdge can dynamically adjust the water temperature and flow rate for each heterogeneous hardware component to eliminate the hardwarelevel hotspots. By redesigning cold plates, CoolEdge can quickly disperse the chip-level hotspots without manual intervention. We further quantify the power saving achieved by the warm water

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Section: Related Workmentioning

confidence: 99%

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Pei

Chen

Zhang

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

Self Cite

View full text Add to dashboard Cite

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“…Others have created markets that distribute the economic benefits of demandresponse to flexible customers-both datacenters [35] or tenants colocated in a datacenter [7,8,51,58]. In others, datacenter operators shift load across grids based on grid information about social welfare, optimizing social welfare across grids [61,63].…”

Section: Related Workmentioning

confidence: 99%

Evaluating Coupling Models for Cloud Datacenters and Power Grids

Lin

Zavala

Chien

2021

Proceedings of the Twelfth ACM International Conference on Future Energy Systems

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The rapid growth of datacenter (DC) loads can be leveraged to help meet renewable portfolio standard (RPS, renewable fraction) targets in power grids. The ability to manipulate DC loads over time (shifting) provides a mechanism to deal with temporal mismatch between non-dispatchable renewable generation (e.g. wind and solar) and overall grid loads, and this flexibility ultimately facilitates the absorption of renewables and grid decarbonization. To this end, we study DC-grid coupling models, exploring their impact on grid dispatch, renewable absorption, power prices, and carbon emissions. With a detailed model of grid dispatch, generation, topology, and loads, we consider three coupling approaches: fixed, datacenterlocal optimization (online dynamic programming), and grid-wide optimization (optimal power flow).Results show that understanding the effects of dynamic DC load management requires studies that model the dynamics of both load and power grid. Dynamic DC-grid coupling can produce large improvements: (1) reduce grid dispatch cost (-3%), (2) increase grid renewable fraction (+1.58%), and (3) reduce DC power cost (-16.9%). It also has negative effects: (1) increase cost for both DCs and non-DC customers, (2) differentially increase prices for non-DC customers, and (3) create large power-level changes that may harm DC productivity.

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“…Although significant recent studies have investigated the problem of DC management in DR programs, only a handful of works looked at the participation of geo-distributed DCs. In this regard, the work in [14] and [15] designed an auction mechanism to elicit the potential of the demand response from a geo-distributed cloud. [16] proposed a price-sensitivity aware geographical load balancing scheme for distributed Internet data centers taking into account the dynamic characteristics and actual physical constraints of the SG.…”

Section: A Geo-distributed Data Center Demand Responsementioning

confidence: 99%

On Coordination of Smart Grid and Cooperative Cloud Providers

Moghaddam¹,

Manshaei²,

Soorki³

et al. 2020

Preprint

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Cooperative cloud providers in the form of cloud federations can potentially reduce their energy costs by exploiting electricity price fluctuations across different locations. In this environment, on the one hand, the electricity price has a significant influence on the federations formed, and, thus, on the profit earned by the cloud providers, and on the other hand, the cloud cooperation has an inevitable impact on the performance of the smart grid. In this regard, the interaction between independent cloud providers and the smart grid is modeled as a two-stage Stackelberg game interleaved with a coalitional game in this paper. In this game, in the first stage the smart grid, as a leader chooses a proper electricity pricing mechanism to maximize its own profit. In the second stage, cloud providers cooperatively manage their workload to minimize their electricity costs. Given the dynamic of cloud providers in the federation formation process, an optimization model based on a constrained Markov decision process (CMDP) has been used by the smart grid to achieve the optimal policy. Numerical results show that the proposed solution yields around 28% and 29% profit improvement on average for the smart grid, and the cloud providers, respectively, compared to the noncooperative scheme.

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A Truthful and Efficient Incentive Mechanism for Demand Response in Green Datacenters

Cited by 40 publications

References 27 publications

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Evaluating Coupling Models for Cloud Datacenters and Power Grids

On Coordination of Smart Grid and Cooperative Cloud Providers

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