Article
Automation & Control Systems
N. Bagheri Rad, J. Behnamian
Summary: The changing market environment necessitates the use of job shop systems based on real-time data. Intelligent factories, created through the integration of physical-virtual systems, offer higher quality and faster production speed compared to traditional methods. Radio Frequency Identification System is employed for virtual connections between factories, allowing quick and careful decision-making regarding events such as new job arrivals and machine breakdowns. This research addresses the real-time scheduling problem in multi-agent production networks distributed in smart factories, highlighting its importance in today's industry.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Yi Zhao, Zheng Yang, Xiaowu He, Xinjun Cai, Xin Miao, Qiang Ma
Summary: Real-time mobile video analysis is crucial for household applications like AR, cognitive assistance, and smart homes, but the heaviness of DNN models limits the feasibility of mobile devices. Cloud offloading has high latency, while direct edge offloading requires powerful edge servers that are not practical for home scenarios. To address this challenge, we propose Trine, a cloud-edge-device cooperation framework, which offloads complex computation tasks from devices to the cloud with the edge as a coordinating bond. Additionally, we introduce a profile-based algorithm to customize trackers for different edge devices. Our experiments show that Trine achieves 8-36% higher real-time accuracy and 25-89% higher robustness than state-of-the-art solutions.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Automation & Control Systems
Lixiang Zhang, Chen Yang, Yan Yan, Yaoguang Hu
Summary: In this study, a distributed real-time scheduling (DRTS) framework with cloud-edge collaboration is proposed to optimize the weighted tardiness by considering both processing services sequencing and logistics services assignment. Experimental results demonstrate the significant potential of this method for efficient real-time decision-making in cloud manufacturing.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Wenbin Gu, Yuxin Li, Dunbing Tang, Xianliang Wang, Minghai Yuan
Summary: This paper proposes a cyber-physical architecture and a communication protocol for smart factory, and introduces a multiagent-system-based dynamic scheduling mechanism using contract net protocol. The proposed mechanism combines genetic programming, self-organizing mapping neural network, and clustering algorithm to efficiently cluster production data and optimize scheduling decisions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Xiaojin Ma, Huahu Xu, Honghao Gao, Minjie Bian
Summary: The paper proposes a real-time multiple-workflow scheduling scheme that dynamically schedules workflows with minimum cost under different deadline constraints, outperforming other algorithms in terms of total rental cost, resource utilization, success rate, and deadline deviation. By dividing the scheduling process into three stages and allocating tasks based on subdeadlines and virtual machine costs, delay fluctuations can be effectively reduced.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2021)
Article
Automation & Control Systems
Shunmei Meng, Weijia Huang, Xiaochun Yin, Mohammad R. Khosravi, Qianmu Li, Shaohua Wan, Lianyong Qi
Summary: This article proposes a security-aware dynamic scheduling method for real-time resource allocation in ICS. A three-level security model is designed for tasks and cloud resources in ICS, and a two-tier heterogeneous cloud architecture is introduced. A security-aware scheduling method based on distributed particle swarm optimization is presented for resource allocation, with a dynamic scheduling mechanism based on dynamic workflow model to address the dynamics of edge resources and mobile industrial applications.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Hardware & Architecture
Luca Abeni, Alessandro Biondi, Enrico Bini
Summary: This paper discusses and presents a set of partitioning algorithms, including mathematical optimization and heuristics, to tackle the problem of online admission control and partitioning. An experimental evaluation shows that some of the heuristic algorithms can effectively partition complex task sets in practical settings.
JOURNAL OF SYSTEMS ARCHITECTURE
(2022)
Article
Computer Science, Information Systems
Chia-Cheng Hu
Summary: This study proposes a strategy to maximize the profit of joint issue in C-RAN, using ILP and an algorithm with bounded approximation ratio for solving it. Simulation results show the algorithm's solution is very close to the ILP's optimal one, and another algorithm is introduced to control the tradeoff between performance and robustness of the solution.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Amanjot Kaur, Nitin Auluck, Omer Rana
Summary: Cloud computing is not always suitable for latency constrained data processing. Fog computing brings processing closer to data generation sources, making it a viable alternative for real-time tasks. We propose a scheduling algorithm (RTHS)-S-2 for real-time tasks on a heterogeneous fog-cloud architecture. The algorithm is validated using simulation and a lab-based testbed.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Huangke Chen, Xiaomin Zhu, Guipeng Liu, Witold Pedrycz
Summary: This study focuses on improving the performance of cloud service platforms by minimizing uncertainty propagation in scheduling workflow applications. A novel scheduling architecture is designed to control the count of waiting tasks on service instances, and an uncertainty-aware Online Scheduling Algorithm (ROSA) is developed to schedule dynamic and multiple workflows with deadlines. Comparative simulation experiments show that ROSA outperforms five typical algorithms in terms of costs, deviation, resource utilization, and fairness.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Long Cheng, Archana Kalapgar, Amogh Jain, Yue Wang, Yongtai Qin, Yuancheng Li, Cong Liu
Summary: Hybrid cloud computing allows enterprises to leverage the benefits of both private and public cloud models. This paper proposes a deep reinforcement learning-based approach for scheduling real-time jobs in hybrid cloud, with a focus on optimizing monetary cost while ensuring high quality of service and low response time. The experimental results show that this method is more cost-efficient compared to current approaches.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Zhongjin Li, Victor Chang, Haiyang Hu, Hua Hu, Chuanyi Li, Jidong Ge
Summary: This paper proposes a real-time and dynamic fault-tolerant scheduling algorithm for executing scientific workflows in the cloud, which can simultaneously handle different types of failures and improve resource utilization.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Mark Szalay, Peter Matray, Laszlo Toka
Summary: This paper presents an analytical model and a heuristic partitioning scheduling algorithm for real-time FaaS platforms of multi-node clusters, and proposes three conceptual designs to enable necessary real-time communications.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Liang Dong, Zheng Yang, Xinjun Cai, Yi Zhao, Qiang Ma, Xin Miao
Summary: This paper proposes three novel techniques, including Deep RoI Encoding, Prioritized Parallel Offloading, and Fine-grained Offloading Strategy, to achieve real-time, robust, and low-cost object detection for open-air AI applications. Experimental results show that under LTE networks, WAVE realizes high-accuracy real-time object detection and face recognition and significantly outperforms state-of-the-art systems.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Biao Hu, Zhengcai Cao, Mengchu Zhou
Summary: This article presents an energy-efficient scheduling algorithm to address the cost issue caused by energy consumption in cloud computing platforms. The algorithm optimizes the tradeoff between energy consumption and task execution time to meet real-time requirements.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Engineering, Industrial
R. Brits, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2016)
Review
Engineering, Industrial
M. Yoon, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2017)
Article
Engineering, Industrial
M. Walters, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2017)
Article
Management
Moonyoung Yoon, James Bekker
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Engineering, Electrical & Electronic
B. G. Lindner, R. Brits, J. H. van Vuuren, J. Bekker
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2018)
Article
Management
James Bekker, Chris Aldrich
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2011)
Article
Engineering, Industrial
J. Bekker
INTERNATIONAL JOURNAL OF SIMULATION MODELLING
(2013)
Article
Engineering, Industrial
T. Bamporiki, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2018)
Article
Computer Science, Interdisciplinary Applications
Moonyoung Yoon, James Bekker
Summary: Three indifference-zone multi-objective ranking and selection procedures are presented in this paper. The statistical validity of the procedures is shown using a Bayesian inference model, and they are compared to multi-objective budget allocation procedures. The proposed procedures performed well in numerical experiments and the concept of relaxed Pareto optimality is introduced.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
J. M. Laubscher, J. Bekker, S. Ackerman
Summary: This study investigates the suitability of discrete-event simulation for modeling forestry supply chains. Two simulation models with bi-objective optimization were developed for the South African pulpwood and saw-timber supply chains. The models were verified and validated to be realistic representations of the supply chains and demonstrated the ability to perform scenario analysis and bi-objective optimization. The study also highlights the successful collaboration between industrial engineering and forestry science.
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
M. Droomer, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2020)
Article
Engineering, Industrial
M. van Niekerk, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2014)
Article
Engineering, Industrial
L. Engelbrecht, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2012)
Article
Engineering, Industrial
A. J. du Plessis, J. Bekker
SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING
(2010)