An Improved Genetic Algorithm with Chromosome Replacement and Rescheduling for Task Offloading DOI Open Access
Hui Fu, Guangyuan Li, Han Fang

и другие.

International Journal of Advanced Computer Science and Applications, Год журнала: 2023, Номер 14(9)

Опубликована: Янв. 1, 2023

End-Edge-Cloud Computing (EECC) has been applied in many fields, due to the increased popularity of smart devices. But cooperation end devices, edge and cloud resources is still challenge for improving service quality resource efficiency EECC. In this paper, we focus on task offloading address challenge. We formulate problem as mixed integer nonlinear programming, solve it by Genetic Algorithm (GA). GA-based algorithm, each chromosome code a solution, evolution iteratively search global best solution. To improve performance offloading, integrate two improvement schemes into which are replacement rescheduling, respectively. The replace every individual its better offspring after crossing, substitutes selection operator population evolution. rescheduling rejected available resources, given solution from chromosome. Extensive experiments conducted, results show that our proposed algorithm can upto 32% user satisfaction, 12% efficiency, 35.3% processing compared with nine classical up-to-date algorithms.

Язык: Английский

Analyzing the risks of digital servitization in the machine tool industry DOI Creative Commons
Clarissa A. González Chávez, Gorka Unamuno, Mélanie Despeisse

и другие.

Robotics and Computer-Integrated Manufacturing, Год журнала: 2023, Номер 82, С. 102520 - 102520

Опубликована: Янв. 15, 2023

The machine tool industry plays a major role in the execution of high-quality and efficient complex manufacturing processes. adoption digital technologies can transform production systems into more connected, adaptive, efficient, potentially sustainable systems. A key enabler this transformation is servitization, business model that builds on digitalization data capture to deliver value through services. Digital services for tools typically use obtained highly connected environments, providing visibility lifecycles, enabling better decision-making. However, an understanding servitization support still emerging most industrial actors potential risks are unclear. findings study describe applications industry, synthesize identified from practitioners' perspectives, provide mitigation contingency activities. This contributes bridging gap between theory practice by clarifying companies' needed considerations before implementing industry.

Язык: Английский

Процитировано

19

Efficient Task Offloading Strategy for Energy-Constrained Edge Computing Environments: A Hybrid Optimization Approach DOI Creative Commons
Deafallah Alsadie

IEEE Access, Год журнала: 2024, Номер 12, С. 85089 - 85102

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

7

Prognostics and health management via long short-term digital twins DOI
Yicheng Sun, Yuqian Lu, Jinsong Bao

и другие.

Journal of Manufacturing Systems, Год журнала: 2023, Номер 68, С. 560 - 575

Опубликована: Май 30, 2023

Язык: Английский

Процитировано

17

A comprehensive review on internet of things task offloading in multi-access edge computing DOI Creative Commons

Wang Dayong,

Kamalrulnizam Bin Abu Bakar,

Babangida Isyaku

и другие.

Heliyon, Год журнала: 2024, Номер 10(9), С. e29916 - e29916

Опубликована: Апрель 22, 2024

With the rapid development of Internet Things (IoT) technology, Terminal Devices (TDs) are more inclined to offload computing tasks higher-performance servers, thereby solving problems insufficient capacity and battery consumption TD. The emergence Multi-access Edge Computing (MEC) technology provides new opportunities for IoT task offloading. It allows TDs access networks through multiple communication technologies supports mobility terminal devices. Review studies on offloading MEC have been extensive, but none them focus in MEC. To fill this gap, paper a comprehensive in-depth understanding algorithms mechanisms network. For each paper, main solved by mechanism, technical classification, evaluation methods, supported parameters extracted analyzed. Furthermore, shortcomings current research future trends discussed. This review will help potential researchers quickly understand panorama approaches find appropriate paths.

Язык: Английский

Процитировано

6

Energy index for evaluating machine tool energy performance: Classification, model and application DOI

Xintao Hu,

Yebing Tian, Jinling Wang

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 447, С. 141356 - 141356

Опубликована: Фев. 19, 2024

Язык: Английский

Процитировано

4

Data-driven AI algorithms for construction machinery DOI
Ke Liang,

Jiahao Zhao,

Zhiqing Zhang

и другие.

Automation in Construction, Год журнала: 2024, Номер 167, С. 105648 - 105648

Опубликована: Авг. 25, 2024

Язык: Английский

Процитировано

3

EDABTOS: Energy-Delay Aware Binary Task Offloading Strategy of IoT Devices in a Fog-Enabled Architecture DOI
Megha Sharma, Abhinav Tomar

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 128354 - 128354

Опубликована: Июнь 1, 2025

Язык: Английский

Процитировано

0

Application of Industrial Internet for Equipment Asset Management in Social Digitalization Platform Based on System Engineering Using Fuzzy DEMATEL-TOPSIS DOI Creative Commons
Yuguang Bao, Xianyu Zhang, Tongtong Zhou

и другие.

Machines, Год журнала: 2022, Номер 10(12), С. 1137 - 1137

Опубликована: Ноя. 29, 2022

In any industry, Equipment Asset Management (EAM) is at the core of production activities. With rapid development Industrial Internet technologies and platforms, EAM based on has become an important trend. Meanwhile, paradigm changing, from a single machine to integrated systems, phase using them end their lifecycle, breakdown maintenance predictive maintenance, local decision-making collaborative optimization. However, because lack unified understanding platforms (IIPs) comprehensive reference architecture detailed implementation framework, projects will face greater risks according special needs in different industries. Based method system engineering, this study proposes general model for Solution (I3EAM). Further, help enterprise evaluate select best-fit I3EAM scheme platform partner, we proposed set performance indicators schemes quantitative fuzzy DEMATEL-TOPSIS. Finally, case automated container terminals was conducted. multi-criteria decision environment with complex uncertainty, project group identified metrics priorities social digitalization that were more line actual terminal firms. The complexity time process dramatically reduced. terms feasibility validity, result positively verified by feedback implementation. given model, architecture, can create certain value various industrial enterprises carry out analysis top-level planning choose partner co-implementation. addition, research results have potential support construction standard systems optimization cross-domain platform, etc.

Язык: Английский

Процитировано

14

An edge intelligence-based model deployment method for CNC systems DOI
Zheng Zhou, Dong Man Yu, Meng Chen

и другие.

Journal of Manufacturing Systems, Год журнала: 2024, Номер 74, С. 716 - 751

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

3

Fusion method for digital twin model of a production line DOI
Xiaojun Liu,

Chongxin Wang,

Jiasheng Huang

и другие.

The International Journal of Advanced Manufacturing Technology, Год журнала: 2024, Номер 132(11-12), С. 6145 - 6167

Опубликована: Май 9, 2024

Язык: Английский

Процитировано

2