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  • Open Access

    ARTICLE

    A Two-Layer Optimal Scheduling Strategy for Rural Microgrids Accounting for Flexible Loads

    Guo Zhao1,2, Chi Zhang1,2,*, Qiyuan Ren1,2

    Energy Engineering, Vol.121, No.11, pp. 3355-3379, 2024, DOI:10.32604/ee.2024.053130 - 21 October 2024

    Abstract In the context of China’s “double carbon” goals and rural revitalization strategy, the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids. Considering the operational characteristics of rural microgrids and their impact on users, this paper establishes a two-layer scheduling model incorporating flexible loads. The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid, while the lower-layer aims to minimize the total electricity cost for rural users. An Improved Adaptive Genetic Algorithm (IAGA) is proposed to solve the model. Results show that the two-layer scheduling model with More >

  • Open Access

    ARTICLE

    Dynamic Offloading and Scheduling Strategy for Telematics Tasks Based on Latency Minimization

    Yu Zhou1, Yun Zhang1, Guowei Li1, Hang Yang1, Wei Zhang1, Ting Lyu2, Yueqiang Xu2,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1809-1829, 2024, DOI:10.32604/cmc.2024.050975 - 15 August 2024

    Abstract In current research on task offloading and resource scheduling in vehicular networks, vehicles are commonly assumed to maintain constant speed or relatively stationary states, and the impact of speed variations on task offloading is often overlooked. It is frequently assumed that vehicles can be accurately modeled during actual motion processes. However, in vehicular dynamic environments, both the tasks generated by the vehicles and the vehicles’ surroundings are constantly changing, making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios. Taking into account the actual dynamic vehicular scenarios, this paper considers the real-time… More >

  • Open Access

    ARTICLE

    Optimal Scheduling Strategy of Source-Load-Storage Based on Wind Power Absorption Benefit

    Jie Ma1, Pengcheng Yue2, Haozheng Yu1, Yuqing Zhang3, Youwen Zhang1, Cuiping Li3, Junhui Li3,*, Wenwen Qin3, Yong Guo1

    Energy Engineering, Vol.121, No.7, pp. 1823-1846, 2024, DOI:10.32604/ee.2024.048225 - 11 June 2024

    Abstract In recent years, the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing, but the peak regulation capacity of the power grid in the three north regions of China is limited, resulting in insufficient local wind power consumption capacity. Therefore, this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid's wind power consumption capacity. The objective of the upper model is to minimize the peak-valley difference of the system load, which is mainly to optimize the system… More >

  • Open Access

    ARTICLE

    Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

    Yang Li1,2, Jianjun Zhao2, Xiaolong Yang2, He Wang1,*, Yuyan Wang1

    Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784 - 30 April 2024

    Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established,… More >

  • Open Access

    ARTICLE

    Urban Drainage Network Scheduling Strategy Based on Dynamic Regulation: Optimization Model and Theoretical Research

    Xiaoming Fei*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1293-1309, 2023, DOI:10.32604/iasc.2023.038607 - 21 June 2023

    Abstract With the acceleration of urbanization in China, the discharge of domestic sewage and industrial wastewater is increasing, and accidents of sewage spilling out and polluting the environment occur from time to time. Problems such as imperfect facilities and backward control methods are common in the urban drainage network systems in China. Efficient drainage not only strengthens infrastructure such as rain and sewage diversion, pollution source monitoring, transportation, drainage and storage but also urgently needs technical means to monitor and optimize production and operation. Aiming at the optimal control of single-stage pumping stations and the coordinated… 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 - 31 March 2023

    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

    Resource Scheduling Strategy for Performance Optimization Based on Heterogeneous CPU-GPU Platform

    Juan Fang1,*, Kuan Zhou1, Mengyuan Zhang1, Wei Xiang2,3

    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 >

  • Open Access

    ARTICLE

    An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes

    Yinghang Jiang1, Qi Liu2,3,*, Williams Dannah1, Dandan Jin2, Xiaodong Liu3, Mingxu Sun4,*

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 713-729, 2020, DOI:10.32604/cmc.2020.04604

    Abstract Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes. “Straggling” tasks, however, have a serious impact on task allocation and scheduling in a Hadoop system. Speculative Execution (SE) is an efficient method of processing “Straggling” Tasks by monitoring real-time running status of tasks and then selectively backing up “Stragglers” in another node to increase the chance to complete the entire mission early. Present speculative execution strategies meet challenges on misjudgement of “Straggling” tasks and improper selection of backup nodes, which leads to inefficient implementation of speculative executive processes. This paper… More >

  • Open Access

    ARTICLE

    A Spark Scheduling Strategy for Heterogeneous Cluster

    Xuewen Zhang1, Zhonghao Li1, Gongshen Liu1,*, Jiajun Xu1, Tiankai Xie2, Jan Pan Nees1

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 405-417, 2018, DOI:10.3970/cmc.2018.02527

    Abstract As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling More >

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