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  • 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… 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.… 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… 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 More >

  • Open Access

    ARTICLE

    Exploring High-Performance Architecture for Data Center Networks

    Deshun Li1, Shaorong Sun2, Qisen Wu2, Shuhua Weng1, Yuyin Tan2, Jiangyuan Yao1,*, Xiangdang Huang1, Xingcan Cao3

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 433-443, 2023, DOI:10.32604/csse.2023.034368

    Abstract As a critical infrastructure of cloud computing, data center networks (DCNs) directly determine the service performance of data centers, which provide computing services for various applications such as big data processing and artificial intelligence. However, current architectures of data center networks suffer from a long routing path and a low fault tolerance between source and destination servers, which is hard to satisfy the requirements of high-performance data center networks. Based on dual-port servers and Clos network structure, this paper proposed a novel architecture to construct high-performance data center networks. Logically, the proposed architecture is constructed… More >

  • Open Access

    ARTICLE

    Replication Strategy with Comprehensive Data Center Selection Method in Cloud Environments

    M. A. Fazlina, Rohaya Latip*, Hamidah Ibrahim, Azizol Abdullah

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 415-433, 2023, DOI:10.32604/cmc.2023.020764

    Abstract As the amount of data continues to grow rapidly, the variety of data produced by applications is becoming more affluent than ever. Cloud computing is the best technology evolving today to provide multi-services for the mass and variety of data. The cloud computing features are capable of processing, managing, and storing all sorts of data. Although data is stored in many high-end nodes, either in the same data centers or across many data centers in cloud, performance issues are still inevitable. The cloud replication strategy is one of best solutions to address risk of performance… More >

  • Open Access

    ARTICLE

    Load-Aware VM Migration Using Hypergraph Based CDB-LSTM

    N. Venkata Subramanian1, V. S. Shankar Sriram2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3279-3294, 2023, DOI:10.32604/iasc.2023.023700

    Abstract

    Live Virtual Machine (VM) migration is one of the foremost techniques for progressing Cloud Data Centers’ (CDC) proficiency as it leads to better resource usage. The workload of CDC is often dynamic in nature, it is better to envisage the upcoming workload for early detection of overload status, underload status and to trigger the migration at an appropriate point wherein enough number of resources are available. Though various statistical and machine learning approaches are widely applied for resource usage prediction, they often failed to handle the increase of non-linear CDC data. To overcome this issue,

    More >

  • Open Access

    ARTICLE

    An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

    Mohammad Aldossary1,*, Hatem A. Alharbi2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3175-3193, 2022, DOI:10.32604/cmc.2022.026041

    Abstract Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve net-zero carbon by 2060, NEOM city has been proposed to be the “Saudi hub” for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Energy Aware Virtual Machine Placement in Cloud Data Center

    B. Gomathi1, B. Saravana Balaji2, V. Krishna Kumar3, Mohamed Abouhawwash4,5,*, Sultan Aljahdali6, Mehedi Masud6, Nina Kuchuk7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1771-1785, 2022, DOI:10.32604/iasc.2022.024052

    Abstract Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, Cloud infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints to environment. Hence, there should be focus on optimal assignment of Virtual Machines (VM) to Physical Machines (PM) to ensure the energy efficiency and service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed to improve the energy efficiency and minimize the Service Level Agreement (SLA) violation in… More >

  • Open Access

    ARTICLE

    A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

    Denghui Zhang1,*, Guocai Yin2

    Journal on Internet of Things, Vol.3, No.4, pp. 149-157, 2021, DOI:10.32604/jiot.2021.016936

    Abstract Cloud data centers face the largest energy consumption. In order to save energy consumption in cloud data centers, cloud service providers adopt a virtual machine migration strategy. In this paper, we propose an efficient virtual machine placement strategy (VMP-SI) based on virtual machine selection and integration. Our proposed VMP-SI strategy divides the migration process into three phases: physical host state detection, virtual machine selection and virtual machine placement. The local regression robust (LRR) algorithm and minimum migration time (MMT) policy are individual used in the first and section phase, respectively. Then we design a virtual More >

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