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 >

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 >

Jiangyuan Yao¹, Weiping Yang¹, Shuhua Weng¹, Minrui Wang¹, Zheng Jiang², Deshun Li^1,*, 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 >

Yogesh Jaluria^a,*, Arvindh Sunder^a, Jingru Z. Benner^b

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 >

Muhammad Imran Khan Khalil¹, Syed Adeel Ali Shah¹, Izaz Ahmad Khan², Mohammad Hijji³, Muhammad Shiraz⁴, Qaisar Shaheen^5,*

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 >

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 >

Jin Wang¹, Dongzhi Yuan¹, Wangqing Luo¹, Shuying Rao¹, R. Simon Sherratt², Jinbin Hu^1,*

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 >

Deshun Li¹, Shaorong Sun², Qisen Wu², Shuhua Weng¹, Yuyin Tan², Jiangyuan Yao^1,*, 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 by inserting a dual-port server… More >

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 degradation in the cloud environment.… More >

N. Venkata Subramanian¹, V. S. Shankar Sriram^2,*

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, a novel Hypergrah based Convolutional… More >