Chi-Chou Kao^1,*, Hung-Yi Lin²

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1581-1594, 2024, DOI:10.32604/csse.2024.055073 - 22 November 2024

Abstract Layout synthesis in quantum computing is crucial due to the physical constraints of quantum devices where quantum bits (qubits) can only interact effectively with their nearest neighbors. This constraint severely impacts the design and efficiency of quantum algorithms, as arranging qubits optimally can significantly reduce circuit depth and improve computational performance. To tackle the layout synthesis challenge, we propose an algorithm based on integer linear programming (ILP). ILP is well-suited for this problem as it can formulate the optimization objective of minimizing circuit depth while adhering to the nearest neighbor interaction constraint. The algorithm aims… More >

Jingbo Zhang¹, Qiong Wu^1,*, Pingyi Fan², Qiang Fan³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1953-1998, 2024, DOI:10.32604/cmc.2024.057006 - 18 November 2024

Abstract Federated Edge Learning (FEL), an emerging distributed Machine Learning (ML) paradigm, enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data. However, with the development of complex application scenarios such as the Internet of Things (IoT) and Smart Earth, the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands. Therefore, joint resource optimization may be the key solution to the scaling problem. This paper simultaneously addresses the multifaceted challenges of computation and communication, with the growing multiple resource demands. We… More >

Jingjing Bai¹, Yunpeng Cheng¹, Shenyun Yao^2,*, Fan Wu¹, Cheng Chen¹

Energy Engineering, Vol.121, No.11, pp. 3381-3400, 2024, DOI:10.32604/ee.2024.053683 - 21 October 2024

Abstract To mitigate the impact of wind power volatility on power system scheduling, this paper adopts the wind-storage combined unit to improve the dispatchability of wind energy. And a three-level optimal scheduling and power allocation strategy is proposed for the system containing the wind-storage combined unit. The strategy takes smoothing power output as the main objectives. The first level is the wind-storage joint scheduling, and the second and third levels carry out the unit combination optimization of thermal power and the power allocation of wind power cluster (WPC), respectively, according to the scheduling power of WPC and… More >

Jianhua Liu^*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >

Neng Wan^1,2, Guangping Zeng^1,*, Xianwei Zhou¹

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4281-4302, 2024, DOI:10.32604/cmc.2024.054794 - 12 September 2024

Abstract With the development of vehicles towards intelligence and connectivity, vehicular data is diversifying and growing dramatically. A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle (ICV) applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points (NCPs). Considering the amount of task data and the idle resources of NCPs, a computing resource scheduling model for NCPs is established. Taking the heterogeneous task execution delay threshold as a constraint, the optimization problem is described as the problem of maximizing the utilization of computing resources by NCPs. The… More >

Ahmad Nahar Quttoum^1,*, Muteb Alshammari²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4577-4601, 2024, DOI:10.32604/cmc.2024.054102 - 12 September 2024

Abstract Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when… More >

Ayesha Khaliq¹, Salman Afsar Awan¹, Fahad Ahmad^2,*, Muhammad Azam Zia¹, Muhammad Zafar Iqbal³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3221-3242, 2024, DOI:10.32604/cmc.2024.053488 - 15 August 2024

Abstract The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original integrity. Current approaches in Extractive Text Summarization (ETS) leverage the modeling of inter-sentence relationships, a task of paramount importance in producing coherent summaries. This study introduces an innovative model that integrates Graph Attention Networks (GATs) with Transformer-based Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA), further enhanced by Term Frequency-Inverse Document Frequency (TF-IDF) values, to improve sentence selection by capturing comprehensive topical information. Our… More >

Huanhuan Li^1,2,*, Hongchang Wei², Zheliang Chen², Yue Xu³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2199-2219, 2024, DOI:10.32604/cmc.2024.052155 - 15 August 2024

Abstract The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges, such as low user utilization, unbalanced resource allocation, and extended adaptive allocation time. We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues. This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components. It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes. Furthermore, this study analyzes the single-hop and multi-hop modes in… More >

Prasanna Kumar Kannughatta Ranganna¹, Siddesh Gaddadevara Matt², Chin-Ling Chen^3,4,*, Ananda Babu Jayachandra⁵, Yong-Yuan Deng^4,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2557-2578, 2024, DOI:10.32604/cmc.2024.051634 - 15 August 2024

Abstract In recent decades, fog computing has played a vital role in executing parallel computational tasks, specifically, scientific workflow tasks. In cloud data centers, fog computing takes more time to run workflow applications. Therefore, it is essential to develop effective models for Virtual Machine (VM) allocation and task scheduling in fog computing environments. Effective task scheduling, VM migration, and allocation, altogether optimize the use of computational resources across different fog nodes. This process ensures that the tasks are executed with minimal energy consumption, which reduces the chances of resource bottlenecks. In this manuscript, the proposed framework… More >

Sohail Muhammad¹, Muzammil Khan², Sarwar Shah Khan^2,3,*

Journal on Artificial Intelligence, Vol.6, pp. 193-209, 2024, DOI:10.32604/jai.2024.052099 - 07 August 2024

Abstract Retrieving information from evolving digital data collection using a user’s query is always essential and needs efficient retrieval mechanisms that help reduce the required time from such massive collections. Large-scale time consumption is certain to scan and analyze to retrieve the most relevant textual data item from all the documents required a sophisticated technique for a query against the document collection. It is always challenging to retrieve a more accurate and fast retrieval from a large collection. Text summarization is a dominant research field in information retrieval and text processing to locate the most appropriate… More >