An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks by Pengcheng Fu, Hongying Tang, Yongbo Cheng, Baoqing Li, Hanwang Qian, Xiaobing Yuan

“…Then, we put forward a novel energy-balanced sensor nodes scheduling algorithm, Greedy Balance Replace Heuristic Algorithm, to select a near-optimal task sensor set from the candidate sensor node set to balance tracking quality and network lifetime. …”
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Low cost network traffic measurement and fast recovery via redundant row subspace-based matrix completion by Kai Jin, Kun Xie, Jiazheng Tian, Wei Liang, Jigang Wen

“…Secondly, based on the identified subspace rows, we design our sampling scheduling algorithm, which takes full measurement samples in subspace rows while taking partial measurement samples in the remaining rows. …”
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Research on High-Reliability Energy-Aware Scheduling Strategy for Heterogeneous Distributed Systems by Ziyu Chen, Jing Wu, Lin Cheng, Tao Tao

“…First, based on a reliability-constrained model, we propose a topology-aware dynamic priority scheduling algorithm (EAWRS). This algorithm constructs a node priority function by incorporating in-degree/out-degree weighting factors and critical path analysis to enable multi-objective optimization. …”
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Dynamic Adaptation for Independent Task Scheduling Using Dynamic Programming in Multiprocessor Systems by Lotfi BENDIAF, Ahmed HARBOUCHE, Mohammed Amin TAHRAOUI

“…In this work, we propose DYnamic Task Allocation using dynamic programminG (DyTAg), a task scheduling algorithm based on dynamic programming, designed to support dynamic adaptation in HCS. …”
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A clustering-aided multi-agent deep reinforcement learning for multi-objective parallel batch processing machines scheduling in semiconductor manufacturing by Peng Zhang, Mengyu Jin, Ming Wang, Jie Zhang, Junjie He, Peng Zheng

“…Specifically, to achieve diverse nondominated solutions, an offline multi-objective scheduling algorithm named Multi-Subpopulation fast elitist Non-Dominated Sorting Genetic Algorithm (MS-NSGA-II) is firstly developed to obtain the Pareto Fronts, and a clustering algorithm based on cosine distance is employed to analyze the distribution of Pareto frontier solution, which would be used to guide reward functions design in multi-agent deep reinforcement learning. …”
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A Flow Shop Scheduling Method Based on Dual BP Neural Networks with Multi-Layer Topology Feature Parameters by Hui Mu, Zinuo Wang, Jiaqi Chen, Guoqiang Zhang, Shaocun Wang, Fuqiang Zhang

“…Secondly, a dual BP neural network scheduling algorithm is designed for determining an operations sequence involving the transport time. …”
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Data Aggregation and Scheduling to Optimize Information Freshness In Multi-Hop IoT Networks by Xueling Wu, Long Qu, Maurice J. Khabbaz

“…The RMP models data aggregation at Base Station (BS), while the PP incorporates an Energy-Aware Scheduling Algorithm (EASA) to generate feasible scheduling solutions. …”
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Enhancing task execution: a dual-layer approach with multi-queue adaptive priority scheduling by Mansoor Iqbal, Muhammad Umar Shafiq, Shouzab Khan, Obaidullah, Saad Alahmari, Zahid Ullah

“…Efficient task execution is critical to optimize the usage of computing resources in process scheduling. Various task scheduling algorithms ensure optimized and efficient use of computing resources. …”
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Joint Resource Scheduling of the Time Slot, Power, and Main Lobe Direction in Directional UAV Ad Hoc Networks: A Multi-Agent Deep Reinforcement Learning Approach by Shijie Liang, Haitao Zhao, Li Zhou, Zhe Wang, Kuo Cao, Junfang Wang

“…To ensure transmission fairness and the total count of transmitted data packets for the DUANET under dynamic data transmission demands, a scheduling algorithm for the time slot, power, and main lobe direction based on multi-agent deep reinforcement learning (MADRL) is proposed. …”
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Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…Cloud can accomplish this using efficient scheduling algorithm. This article focuses on task scheduling policy which aims to improve the performance in real-time with the least execution time, network cost and execution cost-effective at the same time. …”
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Energy-Aware Task Allocation for Multi-Cloud Networks by Sambit Kumar Mishra, Sonali Mishra, Ahmed Alsayat, N Z Jhanjhi, Mamoona Humayun, Kshira Sagar Sahoo, Ashish Kr. Luhach

“…However, the average energy consumption improved through <italic>ETAMCN</italic> is approximately 14&#x0025;, 6.3&#x0025;, and 2.8&#x0025; in opposed to the random allocation algorithm, Cloud Z-Score Normalization (<italic>CZSN</italic>) algorithm, and multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS), respectively. …”
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Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China by Zhaocai Wang, Zhihua Zhu, Hualong Luan, Tunhua Wu

“…In complex basins with multiple converging rivers, the ''dimensional catastrophe'' effect increases with more decision variables, requiring improved robustness and optimization of the scheduling algorithm. In this study, an improved multi-objective sparrow search algorithm (IMOSSA) is proposed to solve the problem, which overcome the classical SSA solution efficiency instability and easy to fall into the local optimal solution through Tent mapping, levy flight, Gaussian variation, and a strategy combining slime mold algorithm (SMA). …”
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Enhancing electric vehicle charging infrastructure: A framework for efficient charging point management by Prajeesh C B, Krishna Priya R, Anju S Pillai, Ahmed S Khwaja, Alagan Anpalagan

“…The framework is integrated with advanced dynamic demand scheduling algorithm (ADDSA), which utilizes real-time charging data collected from Trivandrum, Kerala state, India. …”
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Model Reduction and Chattering Mitigation in Multi-Model Predictive Control for Quadrotor UAVs by Ghulam E. Mustafa Abro, Sufyan Ali Memon, Saddaf Rubab, Kaznah Alshammari, Faheem Khan

“…To improve performance, we implement an adaptive gain scheduling algorithm to mitigate the chattering effect frequently seen in multi-model approaches. …”
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Multi Objective Prioritized Workflow Scheduling Using Deep Reinforcement Based Learning in Cloud Computing by Sudheer Mangalampalli, Syed Shakeel Hashmi, Amit Gupta, Ganesh Reddy Karri, K. Varada Rajkumar, Tulika Chakrabarti, Prasun Chakrabarti, Martin Margala

“…In order to effectively schedule complex workflows i.e. with more task dependencies, we propose a novel multi objective workflow scheduling algorithm using Deep reinforcement Learning. Initially, priorities of all workflows calculated based on their dependencies and then calculated priorities of VMs based on electricity cost at datacenters to map workflows onto precise VMs. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Joint Optimization of Computation Offloading and Task Scheduling Using Multi-Objective Arithmetic Optimization Algorithm in Cloud-Fog Computing by Asad Ali, Nazia Azim, Mohamed Tahar Ben Othman, Ateeq Ur Rehman, Masoud Alajmi, Mosleh Hmoud Al-Adhaileh, Faheem Ullah Khan, Mamyrbayev Orken, Habib Hamam

“…To this end, we propose a Multi-objective Arithmetic Optimization-based joint computation offloading and task scheduling algorithm, aiming to minimize energy consumption and transmission latency. …”
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A Privacy-Preserving Polymorphic Heterogeneous Security Architecture for Cloud–Edge Collaboration Industrial Control Systems by Yukun Niu, Xiaopeng Han, Chuan He, Yunfan Wang, Zhigang Cao, Ding Zhou

“…The architecture introduces three key innovations: (1) a hybrid event–time triggered scheduling algorithm with credibility assessment and heterogeneity metrics to mitigate common-mode escape scenarios, (2) an adaptive privacy budget allocation mechanism that balances privacy protection effectiveness with system availability based on attack activity levels, and (3) a unified framework that organically integrates privacy-preserving arbitration with heterogeneous redundancy management. …”
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Automatic Scheduling Method for Customs Inspection Vehicle Relocation Based on Automotive Electronic Identification and Biometric Recognition by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Jinchao Xiao, Jingfeng Yang

“…The automatic scheduling algorithm is detailed, encompassing vehicle prioritization criteria, dynamic path planning, and real-time driver assignment. …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…In addition, the proposed single-device scheduling algorithm is also extended to multi-device scheduling scenarios. …”
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