An Agile Pathway Towards Carbon-aware Clouds

被引:0
|
作者
Patel, Pratyush [1 ]
Gregersen, Theo [1 ]
Anderson, Thomas [1 ]
机构
[1] Univ Washington, Seattle, WA 98195 USA
来源
PROCEEDINGS OF THE 2ND ACM WORKSHOP ON SUSTAINABLE COMPUTER SYSTEMS, HOTCARBON 2023 | 2023年
关键词
cloud computing; carbon reduction; sustainability;
D O I
10.1145/3604930.3605722
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Climate change is a pressing threat to planetary well-being that can be addressed only by rapid near-term actions across all sectors. Yet, the cloud computing sector, with its increasingly large carbon footprint, has initiated only modest efforts to reduce emissions to date; its main approach today relies on cloud providers sourcing renewable energy from a limited global pool of options. We investigate how to accelerate cloud computing's efforts. Our approach tackles carbon reduction from a software standpoint by gradually integrating carbon awareness into the cloud abstraction. Specifically, we identify key bottlenecks to software-driven cloud carbon reduction, including (1) the lack of visibility and disaggregated control between cloud providers and users over infrastructure and applications, (2) the immense overhead presently incurred by application developers to implement carbon-aware application optimizations, and (3) the increasing complexity of carbon-aware resource management due to renewable energy variability and growing hardware heterogeneity. To overcome these barriers, we propose an agile approach that federates the responsibility and tools to achieve carbon awareness across different cloud stakeholders. As a key first step, we advocate leveraging the role of application operators in managing large-scale cloud deployments and integrating carbon efficiency metrics into their cloud usage workflow. We discuss various techniques to help operators reduce carbon emissions, such as carbon budgets, service-level visibility into emissions, and configurable-yet-centralized resource management optimizations.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Carbon-aware Online Operation Approach for Hydrogen-based Energy Systems
    Ren, Jingyi
    Chen, Zhiqiang
    Yu, Liang
    Yue, Dong
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 524 - 531
  • [32] CARE: carbon-aware computing for blockchain-enabled internet of medical things
    Ghosh, Pritam
    Mazumder, Anusua
    Banerjee, Partha Sarathi
    De, Debashis
    INNOVATIONS IN SYSTEMS AND SOFTWARE ENGINEERING, 2024, 20 (03) : 373 - 391
  • [33] Carbon-aware distributed cloud: multi-level grouping genetic algorithm
    Fereydoun Farrahi Moghaddam
    Reza Farrahi Moghaddam
    Mohamed Cheriet
    Cluster Computing, 2015, 18 : 477 - 491
  • [34] Carbon-aware distributed cloud: multi-level grouping genetic algorithm
    Moghaddam, Fereydoun Farrahi
    Moghaddam, Reza Farrahi
    Cheriet, Mohamed
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2015, 18 (01): : 477 - 491
  • [35] Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach
    Breukelman, Enno
    Hall, Sophie
    Belgioioso, Giuseppe
    Dorfler, Florian
    2024 EUROPEAN CONTROL CONFERENCE, ECC 2024, 2024, : 798 - 803
  • [36] Energy and carbon-aware initial VM placement in geographically distributed cloud data centers
    Khodayarseresht, Ehsan
    Shameli-Sendi, Alireza
    Fournier, Quentin
    Dagenais, Michel
    SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, 2023, 39
  • [37] Carbon-Aware Energy Cost Minimization for Distributed Internet Data Centers in Smart Microgrids
    Yu, Liang
    Jiang, Tao
    Cao, Yang
    Qi, Qi
    IEEE INTERNET OF THINGS JOURNAL, 2014, 1 (03): : 255 - 264
  • [38] Measuring the Effectiveness of Carbon-Aware AI Training Strategies in Cloud Instances: A Confirmation Study
    Vergallo, Roberto
    Mainetti, Luca
    FUTURE INTERNET, 2024, 16 (09)
  • [39] The Online Pause and Resume Problem: Optimal Algorithms and An Application to Carbon-Aware Load Shifting
    Lechowicz, Adam
    Christianson, Nicolas
    Zuo, Jinhang
    Bashir, Noman
    Hajiesmaili, Mohammad
    Wierman, Adam
    Shenoy, Prashant
    PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS, 2023, 7 (03)
  • [40] Peer-to-Peer Joint Electricity and Carbon Trading Based on Carbon-Aware Distribution Locational Marginal Pricing
    Lu, Zelong
    Bai, Linquan
    Wang, Jianxue
    Wei, Jingdong
    Xiao, Yunpeng
    Chen, Yang
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2023, 38 (01) : 835 - 852