Infrastructure Aware Heterogeneous-Workloads Scheduling for Data Center Energy Cost Minimization

Haghshenas, Kawsar; Taheri, Somayyeh; Goudarzi, Maziar; Mohammadi, Siamak

doi:10.1109/tcc.2020.2977040

Cited by 14 publications

(6 citation statements)

References 32 publications

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“…There is a vast body of literature about increasing the efficiency of data centers. These works mostly focus on the scheduling of the workload and its optimization, e.g., [26], [27]. The specific aspect of cooling has also attracted some attention and several reviews on cooling solutions for data centers have appeared.…”

Section: Literaturementioning

confidence: 99%

Enough Hot Air: The Role of Immersion Cooling

Haghshenas¹,

Setz²,

Bloch³

et al. 2022

Preprint

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Air cooling is the traditional solution to chill servers in data centers. However, the continuous increase in global data center energy consumption combined with the increase of the racks' power dissipation calls for the use of more efficient alternatives. Immersion cooling is one such alternative. In this paper, we quantitatively examine and compare air cooling and immersion cooling solutions. The examined characteristics include power usage efficiency (PUE), computing and power density, cost, and maintenance overheads. A direct comparison shows a reduction of about 50% in energy consumption and a reduction of about two-thirds of the occupied space, by using immersion cooling. In addition, the higher heat capacity of used liquids in immersion cooling compared to air allows for much higher rack power densities. Moreover, immersion cooling requires less capital and operational expenditures. However, challenging maintenance procedures together with the increased number of IT failures are the main downsides. By selecting immersion cooling, cloud providers must trade-off the decrease in energy and cost and the increase in power density with its higher maintenance and reliability concerns. Finally, we argue that retrofitting an air-cooled data center with immersion cooling will result in high costs and is generally not recommended.

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Section: Literaturementioning

confidence: 99%

Enough Hot Air: The Role of Immersion Cooling

Haghshenas¹,

Setz²,

Bloch³

et al. 2022

Preprint

Self Cite

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“…Different SG's functionalities especially demand response and dynamic pricing have been adopted using different architectures. Wang et al [19] formulate the dynamic in- Renewable Energy Sources Smart Microgrid -Cloud architecture Wang et al [19] X X Lu et al [20] X X Kawsar et al [21] X X X Gu et al [22] [23] X X X Yuan et al [24] X X X Ding et al [25] X X X X Yu et al [26] [27] X X X X Baris et al [28] X X Anis et al [29] X X X Anis et al [17] X X X X Zhou et al [30]…”

Section: A Literature Reviewmentioning

confidence: 99%

“…In addition to considering spatial and temporal price variations in Smart grid -Cloud (SG-C) architectures, various works have considered clean energies like solar or wind energies in order to minimize energy cost and reduce gas emissions for environmental effects. Kawsar et al [21] try to minimize the energy cost of DCs and propose an approach which schedules DCs workload, by considering available renewable energy, cooling subsystem and electricity rate structure. In the same context, in [22], Gu et al investigate a set of DCs, supplied with both self-generated renewable energy and grid power in a SG-C system.…”

Section: A Literature Reviewmentioning

confidence: 99%

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Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach

et al. 2022

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Data centers are becoming an important asset in today's connected and intelligent world. Indeed, with the emergence of 5G networks, the growth of Internet of Things (IoT) and cloud computing, the data centers are increasingly becoming an essential component in delivering our daily services. On the other hand, cloud data centers, are outfitted with power-hungry servers and electrical installations that require enormous quantities of energy. In addition, operating cloud data centers in microgrids can be more reliable and sustainable than having them managed directly by the smart grid operator. However, microgrids have to deal with the high energy cost that their data centers may incur. In this context, managing the power allocated to the data centers and minimizing microgrids energy cost is a challenging problem. In this paper, we model a two-stage optimization approach in a microgrid-cloud architecture. In the first stage, we consider that the cloud data centers are run by multiple providers and try to get as much power as possible from the microgrid, to store this energy and to be able to execute the maximum of users applications. Such a power behavior requires an optimal power assignment from the microgrid to mitigate the risk of blackouts and power outages. Thus, the data center's huge power demand was modeled as a non-cooperative game. The microgrid controller calculates the optimal power that will be assigned to each data center according to its Power Usage Effectiveness (PUE), number of real-time applications and its network bandwidth usage. In the second stage, the microgrids try to minimize their energy cost by optimally purchasing power from the main grid and the other migrogrids, and by selling back their stored energy. We compare our approach with three existing power minimization approaches: (i) our previously presented scheme called "Basic Game Scheme" (BGS), (ii) traditional and (iii) price-based approaches. Simulations results show that our two stage optimization approach is up to 25% more effective in terms of energy cost. In addition, our scheme promotes MGs green energy usage which significantly reduces power load rate and CO2 emission with a percentage up to 52% comparing to "BGS" and price-based scheme.INDEX TERMS Microgrids, Energy cost minimization, Game theory, Cloud data centers, Power assignment.

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“…As renewable energy becomes a solution to the data center's carbon footprint reduction, several works deal with this topic in the literature. [6] proposes a scheduler to define the workload placement, considering the renewable sources production, cooling subsystem, and electricity rate structure. The main objective is to reduce energy costs.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of Heuristics to Manage a Data Center Under Power Constraints

Nardin

Stolf

Caux

2022

2022 IEEE 13th International Green and Sustainable Computing Conference (IGSC)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Infrastructure Aware Heterogeneous-Workloads Scheduling for Data Center Energy Cost Minimization

Cited by 14 publications

References 32 publications

Enough Hot Air: The Role of Immersion Cooling

Enough Hot Air: The Role of Immersion Cooling

Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach

Evaluation of Heuristics to Manage a Data Center Under Power Constraints

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