Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data Centers Article Swipe
Shuang Wang
,
He Zhang
,
Tianxing Wu
,
Yueyou Zhang
,
Wei Emma Zhang
,
Quan Z. Sheng
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/tsc.2025.3562325
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/tsc.2025.3562325
Worldwide, Geo-distributed Data Centers (GDCs) provide computing and storage services for massive workflow applications, resulting in high electricity costs that vary depending on geographical locations and time. How to reduce electricity costs while satisfying the deadline constraints of workflow applications is important in GDCs, which is determined by the execution time of servers, power, and electricity price. Determining the completion time of workflows with different server frequencies can be challenging, especially in scenarios with heterogeneous computing resources in GDCs. Moreover, the electricity price is also different in geographical locations and may change dynamically. To address these challenges, we develop a geo-distributed system architecture and propose an Electricity Cost aware Multiple Workflows Scheduling algorithm (ECMWS) for servers of GDCs with fixed frequency and power. ECMWS comprises four stages, namely workflow sequencing, deadline partitioning, task sequencing, and resource allocation where two graph embedding models and a policy network are constructed to solve the Markov Decision Process (MDP). After statistically calibrating parameters and algorithm components over a comprehensive set of workflow instances, the proposed algorithms are compared with the state-of-the-art methods over two types of workflow instances. The experimental results demonstrate that our proposed algorithm significantly outperforms other algorithms, achieving an improvement of over 15\% while maintaining an acceptable computational time. The source codes are available at https://gitee.com/public-artifacts/ecmws-experiments.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tsc.2025.3562325
- OA Status
- green
- Cited By
- 1
- References
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4409685320Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tsc.2025.3562325Digital Object Identifier
- Title
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Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data CentersWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-22Full publication date if available
- Authors
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Shuang Wang, He Zhang, Tianxing Wu, Yueyou Zhang, Wei Emma Zhang, Quan Z. ShengList of authors in order
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https://doi.org/10.1109/tsc.2025.3562325Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2504.20105Direct OA link when available
- Concepts
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Computer science, Workflow, Minification, Electricity, Distributed database, Data modeling, Distributed computing, Database, World Wide Web, Engineering, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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39Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works_count | 39 |
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