Chirag Devendrakumar Parikh^*

Journal on Artificial Intelligence, Vol.7, pp. 571-584, 2025, DOI:10.32604/jai.2025.073765 - 01 December 2025

Abstract With the increasing complexity and scale of hyperscale data centers, the requirement for intelligent, real-time power delivery has never been more critical to ensure uptime, energy efficiency, and sustainability. Those techniques are typically static, reactive (since CPU and workload scaling is applied to performance events that occur after a request has been submitted, and is thus can be classified as a reactive response.), and require manual operation, and cannot cope with the dynamic nature of the workloads, the distributed architectures as well as the non-uniform energy sources in today’s data centers. In this paper, we… More >

Yifan Li^*, Congzhe Zhu, Rong Gao^*, Bin Yang

Energy Engineering, Vol.122, No.11, pp. 4523-4539, 2025, DOI:10.32604/ee.2025.068480 - 27 October 2025

Abstract The local overheating issue is a serious threat to the safe operation of data centers (DCs). The chip-level liquid cooling with pool boiling is expected to solve this problem. The effect of nano configuration and surface wettability on the boiling characteristics of copper surfaces is studied using molecular dynamics (MD) simulation. The argon is chosen as the coolant, and the wall temperature is 300 K. The main findings and innovations are as follows. (1) Compared to the smooth surface and fin surface, the cylindrical nano cavity obtains the superior boiling performance with earlier onset of… More > Graphic Abstract

Yifan Li¹, Congzhe Zhu¹, Zhihan Lyu^2,*, Bin Yang^1,3,*, Thomas Olofsson³

Energy Engineering, Vol.122, No.9, pp. 3525-3553, 2025, DOI:10.32604/ee.2025.067902 - 26 August 2025

Abstract The growth of computing power in data centers (DCs) leads to an increase in energy consumption and noise pollution of air cooling systems. Chip-level cooling with high-efficiency coolant is one of the promising methods to address the cooling challenge for high-power devices in DCs. Hybrid nanofluid (HNF) has the advantages of high thermal conductivity and good rheological properties. This study summarizes the numerical investigations of HNFs in mini/micro heat sinks, including the numerical methods, hydrothermal characteristics, and enhanced heat transfer technologies. The innovations of this paper include: (1) the characteristics, applicable conditions, and scenarios of… More >

Li Ling^*, Danhao Song, Qianlong Hu, Zihao Xiang, Zeyu Zhang

Energy Engineering, Vol.122, No.8, pp. 3309-3328, 2025, DOI:10.32604/ee.2025.065824 - 24 July 2025

Abstract Rack-level loop thermosyphons have been widely adopted as a solution to data centers’ growing energy demands. While numerous studies have highlighted the heat transfer performance and energy-saving benefits of this system, its economic feasibility, water usage effectiveness (WUE), and carbon usage effectiveness (CUE) remain underexplored. This study introduces a comprehensive evaluation index designed to assess the applicability of the rack-level loop thermosyphon system across various computing hub nodes. The air wet bulb temperature T_a,w was identified as the most significant factor influencing the variability in the combination of PUE, CUE, and WUE values. The results indicate… More >

Yiming Rongyang¹, Chengyu Ji¹, Xiangdong Ding^2,*, Jun Gao¹, Jianjian Wei^2,3

Frontiers in Heat and Mass Transfer, Vol.23, No.2, pp. 685-701, 2025, DOI:10.32604/fhmt.2025.063785 - 25 April 2025

Abstract The effect of gradient exhaust strategy and blind plate installation on the inhibition of backflow and thermal stratification in data center cabinets is systematically investigated in this study through numerical methods. The validated Re-Normalization Group (RNG) k-ε turbulence model was used to analyze airflow patterns within cabinet structures equipped with backplane air conditioning. Key findings reveal that server-generated thermal plumes induce hot air accumulation at the cabinet apex, creating a 0.8°C temperature elevation at the top server’s inlet compared to the ideal situation (23°C). Strategic increases in backplane fan exhaust airflow rates reduce server 1’s inlet… More >

Suheib Alhiyari, Siti Hafizah AB Hamid^*, Nur Nasuha Daud

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1087-1107, 2025, DOI:10.32604/cmc.2024.058953 - 03 January 2025

Abstract Link failure is a critical issue in large networks and must be effectively addressed. In software-defined networks (SDN), link failure recovery schemes can be categorized into proactive and reactive approaches. Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries. As SDN adoption grows, ensuring efficient recovery from link failures in the data plane becomes crucial. In particular, data center networks (DCNs) demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements. This paper proposes an efficient Decentralized Failure Recovery (DFR) model… More >

Jinlin Xu^1,2, Wansu Pan^1,*, Haibo Tan^1,2, Longle Cheng¹, Xiaofeng Li^1,2

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2709-2726, 2024, DOI:10.32604/cmc.2024.056925 - 18 November 2024

Abstract The traffic within data centers exhibits bursts and unpredictable patterns. This rapid growth in network traffic has two consequences: it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load. Consequently, persistent overload situations eventually result in network congestion. The Software Defined Network (SDN) technology is employed in data centers as a network architecture to enhance performance. This paper introduces an adaptive congestion control strategy, named DA-DCTCP, for SDN-based Data Centers. It incorporates Explicit Congestion Notification (ECN) and Round-Trip Time (RTT) to establish congestion awareness and an ECN marking model.… More >

Ahmad Nahar Quttoum^1,*, Muteb Alshammari²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4577-4601, 2024, DOI:10.32604/cmc.2024.054102 - 12 September 2024

Abstract Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when… More >

Yuming Zhao¹, Jing Wang¹, Bin Sun², Zhenshang Wang¹, Huashan Li², Jiongcong Chen^2,*

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1171-1188, 2024, DOI:10.32604/fhmt.2024.054594 - 30 August 2024

Abstract Data centers (DCs) are highly energy-intensive facilities, where about 30%–50% of the power consumed is attributable to the cooling of information technology equipment. This makes liquid cooling, especially in two-phase mode, as an alternative to air cooling for the microprocessors in servers of interest. The need to meet the increased power density of server racks in high-performance DCs, along with the push towards lower global warming potential (GWP) refrigerants due to environmental concerns, has motivated research on the selection of two-phase heat transfer fluids for cooling servers while simultaneously recovering waste heat. With this regard,… More >

Xialin Liu^1,2,3,*, Junsheng Wu⁴, Lijun Chen^2,3, Jiyuan Hu⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1601-1631, 2024, DOI:10.32604/cmc.2024.050626 - 18 July 2024

Abstract Virtual machine (VM) consolidation aims to run VMs on the least number of physical machines (PMs). The optimal consolidation significantly reduces energy consumption (EC), quality of service (QoS) in applications, and resource utilization. This paper proposes a prediction-based multi-objective VM consolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value. We use a hybrid model based on Auto-Regressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) (HPAS) as a prediction model and consolidate VMs to PMs based on prediction results by HPAS, aiming at minimizing the More >