Article
Engineering, Aerospace
Ting Cheng, Zhongzhu Li, Qianqian Tan, Shaoxing Wang, Chengyu Yue
Summary: An adaptive dwell scheduling algorithm based on the virtual dynamic template is proposed in this paper, which has certain application value in digital array radar (DAR). The proposed algorithm can achieve general pulse interleaving among tracking tasks with different numbers and repetition intervals of pulses, and it can realize real-time dwell scheduling in actual radar systems. By controlling the utilization ratio threshold, the scheduling performance and efficiency can be easily balanced.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Computer Science, Information Systems
Ghafour Ahani, Di Yuan, Sumei Sun
Summary: The research focuses on optimal scheduling of cache updates for a time-slotted system with varying content sizes. Theoretical results and methods for solving the combinatorial optimization problem are presented, and a scalable optimization algorithm is derived using repeated column generation. Performance evaluation shows the algorithm's strengths compared to a greedy schedule.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Xiao Ma, Ao Zhou, Shan Zhang, Qing Li, Alex X. Liu, Shangguang Wang
Summary: The cloud-assisted mobile edge computing system is an important architecture for processing computation-intensive and delay-sensitive mobile applications efficiently. The paper proposes a Water-filling Based Dynamic Task Scheduling algorithm to solve the dynamic task scheduling problem, aiming at minimizing average task response time within the resource budget limit.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Yi-Wen Zhang
Summary: Energy-aware real-time scheduling for mixed-criticality systems has gained attention. This study focuses on nonpreemptive dynamic priority scheduling, proposing an algorithm that consumes 25.72% less energy compared to existing ones. Extensive simulations validate the algorithm's performance.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2022)
Article
Automation & Control Systems
Biao Hu, Yinbin Shi, Zhengcai Cao
Summary: This article proposes an adaptive scheduling approach to minimize the energy consumption of vehicular edge computing servers. An auction-bid scheme is developed to decide which roadside unit (RSU) responds to a computing request based on the least energy consumption. The proposed approach effectively decomposes a computing request modeled as a directed acyclic graph (DAG) application and assigns tasks to servers' queues in a specific RSU using a deadline-aware queue jump algorithm.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Cui-Qin Dai, Chong Li, Shu Fu, Jian Zhao, Qianbin Chen
Summary: This paper proposes a real-time dynamic scheduling scheme to address the conflict between emergency tasks and common tasks in space data relay network in terms of antenna resource allocation, aiming to improve scheduling efficiency. Experimental results demonstrate that the proposed scheme can guarantee timely transmission of emergency tasks and enhance scheduling efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Md Anwarul Kaium Patwary, Saurabh Garg, Sudheer Kumar Battula, Byeong Kang
Summary: Partitioning a large-scale dynamic graph is crucial for overcoming memory bottleneck and balancing computational load. SDP method contributes novel vertex assigning method, communication-aware balancing method, and scaling technique to achieve efficient runtime performance.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Saravanan Muniswamy, Radhakrishnan Vignesh
Summary: This research presents a hybrid optimum and deep learning approach for dynamic scalable task scheduling (DSTS) in a container cloud environment. The proposed method improves the efficiency and performance of cloud resource workloads through enhanced optimization and neural network techniques.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Said Nabi, Muhammad Ibrahim, Jose M. Jimenez
Summary: In this research, a resource-aware dynamic task scheduling approach was proposed and implemented, which showed significant improvements in terms of achieved average resource utilization, Throughput, and Makespan compared to other scheduling approaches.
Article
Computer Science, Hardware & Architecture
Minyu Cui, Angeliki Kritikakou, Lei Mo, Emmanuel Casseau
Summary: This study proposes a task mapping approach to minimize energy consumption while meeting real-time and reliability constraints. A novel heuristic algorithm is used, consisting of a pruning phase and a mapping phase. The results show that the proposed heuristic achieves near-optimal results with low computation time and better energy consumption compared to other heuristic approaches.
JOURNAL OF SYSTEMS ARCHITECTURE
(2023)
Article
Automation & Control Systems
Huilong Fan, Jun Long, Limin Liu, Zhan Yang
Summary: This article proposes a dynamically updated microcloud structure based on digital twin and multiagent system technology to support various space mission requirements of the satellite information network. The proposed scheme can significantly improve task scheduling revenue and resource utilization, and it has specific enlightening significance for the innovation of satellite task scheduling methods in the future.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Lingjuan Ye, Yuanqing Xia, Liwen Yang, Ce Yan
Summary: In this article, a stochastic hybrid workflows scheduling problem in cloud container services is addressed by proposing a stochastic hybrid workflows scheduling algorithm (SHWSA) that aims to minimize costs and improve resource utilization. The proposed algorithm consists of a workflow analyzer, classifier, estimator, scheduler, and resource manager, demonstrating superiority over existing state-of-the-art algorithms through experiments using synthetic and real-world data.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Hardware & Architecture
Daniel Casini, Alessandro Biondi, Giorgio Carlo Buttazzo
Summary: The article proposes an approach to efficiently schedule dynamic real-time workloads on multiprocessor systems through semi-partitioned scheduling, utilizing the C=D splitting algorithm and a load-balancing algorithm to improve system performance, achieving considerable improvements in experiments.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
Article
Chemistry, Multidisciplinary
Dojin Choi, Hyeonwook Jeon, Jongtae Lim, Kyoungsoo Bok, Jaesoo Yoo
Summary: This paper proposes a dynamic task scheduling scheme that considers task deadlines and node resources, and balances node loads by using a heterogeneous cluster for dynamic scheduling. Through different task scheduling based on three defined load types, the proposed scheme outperforms conventional schemes in terms of task processing performance, as shown in diverse performance evaluations.
APPLIED SCIENCES-BASEL
(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)