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  • Open Access

    ARTICLE

    A Virtual Probe Deployment Method Based on User Behavioral Feature Analysis

    Bing Zhang, Wenqi Shi*

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.067470 - 09 December 2025

    Abstract To address the challenge of low survival rates and limited data collection efficiency in current virtual probe deployments, which results from anomaly detection mechanisms in location-based service (LBS) applications, this paper proposes a novel virtual probe deployment method based on user behavioral feature analysis. The core idea is to circumvent LBS anomaly detection by mimicking real-user behavior patterns. First, we design an automated data extraction algorithm that recognizes graphical user interface (GUI) elements to collect spatio-temporal behavior data. Then, by analyzing the automatically collected user data, we identify normal users’ spatio-temporal patterns and extract their… More >

  • Open Access

    ARTICLE

    Cooperative Game Theory-Based Optimal Scheduling Strategy for Microgrid Alliances

    Zhiyuan Zhang1, Meng Shuai2, Bin Wang1, Ying He3, Fan Yang1, Liyan Ren4,*, Yuyuan Zhang4, Ziren Wang4

    Energy Engineering, Vol.122, No.10, pp. 4169-4194, 2025, DOI:10.32604/ee.2025.066793 - 30 September 2025

    Abstract With the rapid development of renewable energy, the Microgrid Coalition (MGC) has become an important approach to improving energy utilization efficiency and economic performance. To address the operational optimization problem in multi-microgrid cooperation, a cooperative game strategy based on the Nash bargaining model is proposed, aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization. First, each microgrid is regarded as a game participant, and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed, targeting the minimization of total operational cost under constraints such as More >

  • Open Access

    ARTICLE

    Hierarchical Optimal Scheduling Strategy for High Proportion New Energy Power Systems Considering Balanced Response to Grid Flexibility

    Cuiping Li1, Jiacheng Sun1, Qiang Li2, Qi Guo2, Junhui Li1,*, Shuo Yu2, Jingbo Wang2, Wenze Li2

    Energy Engineering, Vol.122, No.8, pp. 3055-3077, 2025, DOI:10.32604/ee.2025.064440 - 24 July 2025

    Abstract The penetration rate of new wind and photovoltaic energy in the power system has increased significantly, and the dramatic fluctuation of the net load of the grid has led to a severe lack of flexibility in the regional grid. This paper proposes a hierarchical optimal dispatch strategy for a high proportion of new energy power systems that considers the balanced response of grid flexibility. Firstly, various flexibility resource regulation capabilities on the source-load side are analyzed, and then flexibility demand and flexibility response are matched, and flexibility demand response assessment is proposed; then, a hierarchical… More >

  • Open Access

    ARTICLE

    Coordinated Charging Scheduling Strategy for Electric Vehicles Considering Vehicle Urgency

    Zhenhao Wang1, Hongwei Li1,*, Dan Pang2, Jinming Ge1

    Energy Engineering, Vol.122, No.8, pp. 3223-3242, 2025, DOI:10.32604/ee.2025.063615 - 24 July 2025

    Abstract Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles, this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use. First, considering the range loss characteristics, dynamic time-sharing tariff mechanism, and user incentive policy in the low-temperature environment of northern winter, a differentiated charging model is constructed for four types of vehicles: family cars, official cars, buses, and cabs. Then, we innovatively introduce the… More >

  • Open Access

    REVIEW

    A Survey of Spark Scheduling Strategy Optimization Techniques and Development Trends

    Chuan Li, Xuanlin Wen*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3843-3875, 2025, DOI:10.32604/cmc.2025.063047 - 19 May 2025

    Abstract Spark performs excellently in large-scale data-parallel computing and iterative processing. However, with the increase in data size and program complexity, the default scheduling strategy has difficulty meeting the demands of resource utilization and performance optimization. Scheduling strategy optimization, as a key direction for improving Spark’s execution efficiency, has attracted widespread attention. This paper first introduces the basic theories of Spark, compares several default scheduling strategies, and discusses common scheduling performance evaluation indicators and factors affecting scheduling efficiency. Subsequently, existing scheduling optimization schemes are summarized based on three scheduling modes: load characteristics, cluster characteristics, and matching More >

  • Open Access

    ARTICLE

    Research on Optimization of Hierarchical Quantum Circuit Scheduling Strategy

    Ziao Han, Hui Li*, Kai Lu, Shujuan Liu, Mingmei Ju

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5097-5113, 2025, DOI:10.32604/cmc.2025.059577 - 06 March 2025

    Abstract Traditional quantum circuit scheduling approaches underutilize the inherent parallelism of quantum computation in the Noisy Intermediate-Scale Quantum (NISQ) era, overlook the inter-layer operations can be further parallelized. Based on this, two quantum circuit scheduling optimization approaches are designed and integrated into the quantum circuit compilation process. Firstly, we introduce the Layered Topology Scheduling Approach (LTSA), which employs a greedy algorithm and leverages the principles of topological sorting in graph theory. LTSA allocates quantum gates to a layered structure, maximizing the concurrent execution of quantum gate operations. Secondly, the Layerwise Conflict Resolution Approach (LCRA) is proposed.… More >

  • Open Access

    ARTICLE

    Centralized-Distributed Scheduling Strategy of Distribution Network Based on Multi-Temporal Hierarchical Cooperative Game

    Guoqing Li, Jianing Li, Kefei Yan, Jing Bian*

    Energy Engineering, Vol.122, No.3, pp. 1113-1136, 2025, DOI:10.32604/ee.2025.059558 - 07 March 2025

    Abstract A centralized-distributed scheduling strategy for distribution networks based on multi-temporal and hierarchical cooperative game is proposed to address the issues of difficult operation control and energy optimization interaction in distribution network transformer areas, as well as the problem of significant photovoltaic curtailment due to the inability to consume photovoltaic power locally. A scheduling architecture combining multi-temporal scales with a three-level decision-making hierarchy is established: the overall approach adopts a centralized-distributed method, analyzing the operational characteristics and interaction relationships of the distribution network center layer, cluster layer, and transformer area layer, providing a “spatial foundation” for… More >

  • 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 >

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