Luyao Liu^*, Xiao Liao, Yiqian Li, Shaofeng Zhang

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.072631 - 27 January 2026

Abstract Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions. In the context of carbon neutrality, the integration of data centers with renewable energy has become a prevailing trend. To advance the renewable energy integration in data centers, it is imperative to thoroughly explore the data centers’ operational flexibility. Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulation within data center micro-grids. This paper identifies and categorizes delay-tolerant computing workloads into three types (long-running non-interruptible, long-running interruptible, and short-running) and develops… More >

Bing Wei, Yubin Li, Yi Wu^*, Ming Zhong, Ning Luo

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4773-4804, 2025, DOI:10.32604/cmc.2025.065090 - 30 July 2025

Abstract Metadata prefetching and data placement play a critical role in enhancing access performance for file systems operating over wide-area networks. However, developing effective strategies for metadata prefetching in environments with concurrent workloads and for data placement across distributed networks remains a significant challenge. This study introduces novel and efficient methodologies for metadata prefetching and data placement, leveraging fine-grained control of prefetching strategies and variable-sized data fragment writing to optimize the I/O bandwidth of distributed file systems. The proposed metadata prefetching technique employs dynamic workload analysis to identify dominant workload patterns and adaptively refines prefetching policies, More >

Rohollah Fallah Madvari¹, Hamideh Bidel², Ahmad Mehri³, Fatema Babaee⁴, Fereydoon Laal^5,*

Sound & Vibration, Vol.58, pp. 119-131, 2024, DOI:10.32604/sv.2024.048861 - 19 March 2024

Abstract Noise is one of the environmental factors with mental and physical effects. The workload is also the multiple mental and physical demands of the task. Therefore, his study investigated the relationship between noise exposure and mood states at different levels of workload. The study recruited 50 workers from the manufacturing sector (blue-collar workers) as the exposed group and 50 workers from the office sector (white-collar workers) as the control group. Their occupational noise exposure was measured by dosimetry. The Stress-Arousal Checklist (SACL) and the NASA Task Load Index (NASA-TLX) were used to measure mood and… More >

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 - 29 January 2024

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… More >

Anju Shukla¹, Mohammad Zubair Khan², Shishir Kumar^3,*, Abdulrahman Alahmadi², Reem Ibrahim A. Altamimi², Ahmed H. Alahmadi²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2281-2297, 2023, DOI:10.32604/iasc.2023.031931 - 05 January 2023

Abstract Integrated CloudIoT is an emerging field of study that integrates the Cloud and the Internet of Things (IoT) to make machines smarter and deal with real-world objects in a distributed manner. It collects data from various devices and analyses it to increase efficiency and productivity. Because Cloud and IoT are complementary technologies with distinct areas of application, integrating them is difficult. This paper identifies various CloudIoT issues and analyzes them to make a relational model. The Interpretive Structural Modeling (ISM) approach establishes the interrelationship among the problems identified. The issues are categorised based on driving… More >

Sunhwa Annie Nam¹, Kyungwoon Cho², Hyokyung Bahn^3,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6823-6833, 2023, DOI:10.32604/cmc.2023.035481 - 28 December 2022

Abstract AI (Artificial Intelligence) workloads are proliferating in modern real-time systems. As the tasks of AI workloads fluctuate over time, resource planning policies used for traditional fixed real-time tasks should be re-examined. In particular, it is difficult to immediately handle changes in real-time tasks without violating the deadline constraints. To cope with this situation, this paper analyzes the task situations of AI workloads and finds the following two observations. First, resource planning for AI workloads is a complicated search problem that requires much time for optimization. Second, although the task set of an AI workload may… More >

M. Hema^1,*, S. Kanaga Suba Raja²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 143-156, 2023, DOI:10.32604/csse.2023.024895 - 01 June 2022

Abstract In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario.… More >

Juan Fang^1,*, Kuan Zhou¹, Mengyuan Zhang¹, Wei Xiang^2,3

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1621-1635, 2022, DOI:10.32604/cmc.2022.027147 - 18 May 2022

Abstract In recent years, with the development of processor architecture, heterogeneous processors including Center processing unit (CPU) and Graphics processing unit (GPU) have become the mainstream. However, due to the differences of heterogeneous core, the heterogeneous system is now facing many problems that need to be solved. In order to solve these problems, this paper try to focus on the utilization and efficiency of heterogeneous core and design some reasonable resource scheduling strategies. To improve the performance of the system, this paper proposes a combination strategy for a single task and a multi-task scheduling strategy for… More >

V. Roopa^1,*, K. Malarvizhi², S. Karthik³

Computer Systems Science and Engineering, Vol.43, No.2, pp. 657-669, 2022, DOI:10.32604/csse.2022.022173 - 20 April 2022

Abstract In cloud environment, an efficient resource management establishes the allocation of computational resources of cloud service providers to the requests of users for meeting the user’s demands. The proficient resource management and work allocation determines the accomplishment of the cloud infrastructure. However, it is very difficult to persuade the objectives of the Cloud Service Providers (CSPs) and end users in an impulsive cloud domain with random changes of workloads, huge resource availability and complicated service policies to handle them, With that note, this paper attempts to present an Efficient Energy-Aware Resource Management Model (EEARMM) that… More >

Faisal Bahadur^1,*, Arif Iqbal Umar¹, Insaf Ullah², Fahad Algarni³, Muhammad Asghar Khan², Samih M. Mostafa⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1483-1493, 2022, DOI:10.32604/cmc.2022.024936 - 24 February 2022

Abstract Scalability is one of the utmost nonfunctional requirement of server applications, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) has been used extensively as a middleware service in server applications. The size of thread pool is the most significant factor, that affects the overall performance of servers. Determining the optimal size of thread pool dynamically on runtime is a challenging problem. The most widely used and simple method to tackle this problem is to keep the size of thread… More >