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  • Open Access

    ARTICLE

    HOT WATER COOLED HEAT SINKS FOR EFFICIENT DATA CENTER COOLING: TOWARDS ELECTRONIC COOLING WITH HIGH EXERGETIC UTILITY

    Peter Kastena, Severin Zimmermanna, Manish K. Tiwaria, Bruno Michelb, Dimos Poulikakosa,*

    Frontiers in Heat and Mass Transfer, Vol.1, No.2, pp. 1-10, 2010, DOI:10.5098/hmt.v1.2.3006

    Abstract Electronic data center cooling using hot water is proposed for high system exergetic utility. The proof-of-principle is provided by numerically modeling a manifold micro-channel heat sink for cooling microprocessors of a data center. An easily achievable 0.5l/min per chip water flow, with 60°C inlet water temperature, is found sufficient to address the typical data center thermal loads. A maximum temperature difference of ~8°C was found between the solid and liquid, confirming small exergetic destruction due to heat transport across a temperature differential. The high water outlet temperature from the heat sink opens the possibility of waste heat recovery applications. More >

  • Open Access

    ARTICLE

    Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

    Shiyan Zhang1,*, Ruohan Xu2, Zhangbo Xu3, Cenhua Yu1, Yuyang Jiang1, Yuting Zhao4

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2287-2308, 2024, DOI:10.32604/cmc.2023.046550

    Abstract The 6th generation mobile networks (6G) network is a kind of multi-network interconnection and multi-scenario coexistence network, where multiple network domains break the original fixed boundaries to form connections and convergence. In this paper, with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness, this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration. Due to the conflict between the utility of different flows, the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions. Regarding the tradeoff between… More >

  • Open Access

    ARTICLE

    Performance Prediction Based Workload Scheduling in Co-Located Cluster

    Dongyang Ou, Yongjian Ren, Congfeng Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2043-2067, 2024, DOI:10.32604/cmes.2023.029987

    Abstract Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents a quality of service (QoS) prediction-based scheduling model (QPSM) for co-located workloads. The performance prediction of QPSM consists of two parts: the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on random forest. On-line service… More >

  • Open Access

    ARTICLE

    DATA CENTER ENERGY CONSERVATION BY HEAT PIPE BASED PRECOOLER SYSTEM

    Randeep Singh* , Masataka Mochizuki, Koichi Mashiko, Thang Nguyen*

    Frontiers in Heat and Mass Transfer, Vol.13, pp. 1-6, 2019, DOI:10.5098/hmt.13.24

    Abstract In the present paper, data center energy conservation systems based on the heat pipe heat exchanger (HPHE) pre-cooler to downsize the chiller capacity and working time has analysed, designed and discussed. The proposed system utilizes thermal diode character of heat pipe to transfer waste heat from source (pre-cooler coolant) to ambient and have been analyzed as per metrological conditions in New York. HPHE Pre cooler with 118 heat pipes and designed for 30 °C ambient temperature has been designed to effectively dissipate 30 kW or more datacenter heat throughout the year. The payback period of the HPHE Pre cooler is… More >

  • Open Access

    ARTICLE

    Virtual Machine Consolidation with Multi-Step Prediction and Affinity-Aware Technique for Energy-Efficient Cloud Data Centers

    Pingping Li*, Jiuxin Cao

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 81-105, 2023, DOI:10.32604/cmc.2023.039076

    Abstract Virtual machine (VM) consolidation is an effective way to improve resource utilization and reduce energy consumption in cloud data centers. Most existing studies have considered VM consolidation as a bin-packing problem, but the current schemes commonly ignore the long-term relationship between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in unnecessary VM migration and increased energy consumption. To address these limitations, a VM consolidation method based on multi-step prediction and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed method uses an improved linear… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Topologies for Multi-Domain Software-Defined Networking

    Jiangyuan Yao1, Weiping Yang1, Shuhua Weng1, Minrui Wang1, Zheng Jiang2, Deshun Li1,*, Yahui Li3, Xingcan Cao4

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.031531

    Abstract Software-defined networking (SDN) is widely used in multiple types of data center networks, and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers. However, the network topology of each control domain of SDN will affect the performance of the multi-domain network, so performance evaluation is required before the deployment of the multi-domain SDN. Besides, there is a high cost to build real multi-domain SDN networks with different topologies, so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network. As there is a lack of… More >

  • Open Access

    ARTICLE

    THERMAL MANAGEMENT OF DATA CENTERS UNDER STEADY AND TRANSIENT CONDITIONS

    Yogesh Jaluriaa,*, Arvindh Sundera, Jingru Z. Bennerb

    Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-12, 2020, DOI:10.5098/hmt.15.12

    Abstract Data centers are of crucial importance today in the storage and retrieval of large amounts of data. Most organizations and firms, ranging from banks and online retailers to government departments and internet companies, use data centers to store information that can be recovered efficiently and rapidly. As the deployment of data centers has increased, along with their capacity for data storage, the demands on thermal management have also increased. It is necessary to remove the energy dissipated by the electronic circuitry since the temperature of the components must not rise beyond acceptable levels that could damage them or affect their… More >

  • Open Access

    ARTICLE

    Energy Cost Minimization Using String Matching Algorithm in Geo-Distributed Data Centers

    Muhammad Imran Khan Khalil1, Syed Adeel Ali Shah1, Izaz Ahmad Khan2, Mohammad Hijji3, Muhammad Shiraz4, Qaisar Shaheen5,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6305-6322, 2023, DOI:10.32604/cmc.2023.038163

    Abstract Data centers are being distributed worldwide by cloud service providers (CSPs) to save energy costs through efficient workload allocation strategies. Many CSPs are challenged by the significant rise in user demands due to their extensive energy consumption during workload processing. Numerous research studies have examined distinct operating cost mitigation techniques for geo-distributed data centers (DCs). However, operating cost savings during workload processing, which also considers string-matching techniques in geo-distributed DCs, remains unexplored. In this research, we propose a novel string matching-based geographical load balancing (SMGLB) technique to mitigate the operating cost of the geo-distributed DC. The primary goal of this… More >

  • Open Access

    ARTICLE

    Data Center Traffic Scheduling Strategy for Minimization Congestion and Quality of Service Guaranteeing

    Chunzhi Wang, Weidong Cao*, Yalin Hu, Jinhang Liu

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4377-4393, 2023, DOI:10.32604/cmc.2023.037625

    Abstract According to Cisco’s Internet Report 2020 white paper, there will be 29.3 billion connected devices worldwide by 2023, up from 18.4 billion in 2018. 5G connections will generate nearly three times more traffic than 4G connections. While bringing a boom to the network, it also presents unprecedented challenges in terms of flow forwarding decisions. The path assignment mechanism used in traditional traffic scheduling methods tends to cause local network congestion caused by the concentration of elephant flows, resulting in unbalanced network load and degraded quality of service. Using the centralized control of software-defined networks, this study proposes a data center… More >

  • Open Access

    ARTICLE

    Congestion Control Using In-Network Telemetry for Lossless Datacenters

    Jin Wang1, Dongzhi Yuan1, Wangqing Luo1, Shuying Rao1, R. Simon Sherratt2, Jinbin Hu1,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1195-1212, 2023, DOI:10.32604/cmc.2023.035932

    Abstract In the Ethernet lossless Data Center Networks (DCNs) deployed with Priority-based Flow Control (PFC), the head-of-line blocking problem is still difficult to prevent due to PFC triggering under burst traffic scenarios even with the existing congestion control solutions. To address the head-of-line blocking problem of PFC, we propose a new congestion control mechanism. The key point of Congestion Control Using In-Network Telemetry for Lossless Datacenters (ICC) is to use In-Network Telemetry (INT) technology to obtain comprehensive congestion information, which is then fed back to the sender to adjust the sending rate timely and accurately. It is possible to control congestion… More >

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