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Contextual-Learning-Based Waveform scheduling for Wireless Power Transfer With Limited Feedback

IEEE INTERNET OF THINGS JOURNAL 2022年第17期9卷 15578-15592页

作者： Kim, Kyeong-Won Lee, Hyun-Suk Zhang, Rui Lee, Jang-Won Yonsei Univ Dept Elect & Elect Engn Seoul 03722 South Korea Sejong Univ Sch Intelligent Mechatron Engn Seoul 05006 South Korea Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

In this article, we study the waveform scheduling problem for a wireless power transfer (WPT) system consisting of a power beacon (PB) and multiple energy-harvesting-empowered Internet of Things (EH-IoT) devices. In each time slot, each device requests power to the PB if it needs power, and the PB transmits a WPT signal for which the waveform is designed based on the harvested power satisfaction rate of the power-requesting devices. Under this setup, we formulate an optimization problem that maximizes the average number of EH-IoT devices whose power requests are satisfied. We first solve this problem, assuming that the perfect channel state information (CSI) of all devices is known at the PB. Since the problem is difficult to solve even with perfect CSI, we transform it into a more tractable problem via proper approximations and propose an efficient algorithm to solve it. Next, to tackle the issue that it is practically difficult for the PB to acquire the perfect CSI of each device, we propose a contextual learning-based WPT waveform scheduling algorithm, requiring only 1-bit feedback from each device at one time. Numerical results show that our proposed waveform scheduling algorithm provides a higher satisfaction rate than existing algorithms under perfect CSI, and that with limited CSI feedback achieves performance close to the case with perfect CSI.

关键词： Array signal processing Rectennas Internet of Things scheduling algorithms scheduling Batteries Wireless communication Contextual-learning Internet of Things (IoT) limited feedback nonlinear rectifier time-varying channel waveform design wireless power transfer (WPT)

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Downlink Transmission scheduling With Data Sharing

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IEEE-ACM TRANSACTIONS ON NETWORKING 2022年第3期30卷 1193-1202页

作者： Shi, Hehuan Chen, Lin Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510275 Peoples R China

We formulate and analyze a fundamental downlink transmission scheduling problem in a wireless communication system, composed of a base station and a set of users, each requesting a packet to be served within a time window. Some packets are requested by several users and can be served simultaneously due to the broadcast nature of the wireless medium. The base station can choose from a set of transmission strategies, e.g., in terms of combination of data rate and coding scheme, to serve the users. Each request can be served by a subset of transmission strategies. We seek a downlink transmission scheduling algorithm generating maximum aggregated system-wide utility. In this paper, we develop approximation algorithms for the formulated downlink transmission scheduling problem in both offline and online settings. We first establish the NP-hardness of the offline scheduling problem and the approximation hardness and bound of the online scheduling problem in non-preemptive and preemptive-restart models, respectively. We then design approximation algorithms and derive the approximation and competitive ratios of our online and offline scheduling algorithms. Numerical simulations are performed to further evaluate our algorithms in a wide range of network settings.

关键词： scheduling Base stations Downlink Approximation algorithms Wireless communication scheduling algorithms Encoding Downlink transmission scheduling data sharing approximation algorithm design

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Performant, Multi-Objective scheduling of Highly Interleaved Task Graphs on Heterogeneous System on Chip Devices

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2022年第9期33卷 2148-2162页

作者： Mack, Joshua Arda, Samet E. Ogras, Umit Y. Akoglu, Ali Univ Arizona Elect & Comp Engn Dept Tucson AZ 85719 USA Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA Univ Wisconsin Elect & Comp Engn Dept Madison WI 53706 USA

Performance-, power-, and energy-aware scheduling techniques play an essential role in optimally utilizing processing elements (PEs) of heterogeneous systems. List schedulers, a class of low-complexity static schedulers, have commonly been used in static execution scenarios. However, list schedulers are not suitable for runtime decision making, particularly when multiple concurrent applications are interleaved dynamically. For such cases, the static task execution times and expectation of idle PEs assumed by list schedulers lead to inefficient system utilization and poor performance. To address this problem, we present techniques for optimizing execution of list scheduling algorithms in dynamic runtime scenarios via a family of algorithms inspired by the well-known heterogeneous earliest finish time (HEFT) list scheduler. Through dynamically arriving, realistic workload scenarios that are simulated in an open-source discrete event heterogeneous SoC simulator, we exhaustively evaluate each of the proposed algorithms across two SoCs modeled after the Xilinx Zynq Ultrascale+ ZCU102 and O-Droid XU3 development boards. Altogether, depending on the chosen variant in this family of algorithms, we are able to achieve an up to 39% execution time improvement, up to 7.24x algorithmic speedup, or up to 30% energy consumption improvement compared to the baseline HEFT implementation.

关键词： Task analysis Heuristic algorithms Runtime Dynamic scheduling scheduling algorithms Schedules Optimal scheduling scheduling and task partitioning heterogeneous (hybrid) systems energy-aware systems hardware simulation HEFT

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Design and Implementation of vCPU scheduling Architecture in Embedded Virtualization 4

Design and Implementation of vCPU Scheduling Architecture in...

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4th International Conference on Electronic Information Engineering and Computer Communication, EIECC 2024

作者： Wu, Yueyang Chai, Xiaoli The 32nd Research Institute China Electronics Technology Group Corporation Shanghai China

ISBN: (纸本)9798331534622

This paper presents a novel scheduling architecture designed for the independently developed Reworks hypervisor (Revmm), aimed at enhancing scheduling efficiency through static precomputation. The architecture integrates a configuration generation mechanism, enabling scheduling algorithms to leverage precomputed static results to assist dynamic scheduling decisions, thereby minimizing runtime overhead. Experimental results demonstrate that the statically precomputed Round-Robin algorithm surpasses traditional Round-Robin scheduling in terms of runtime efficiency and stability. To meet real-time requirements, the study also introduces a static priority-based, preemptible multicore VCPU scheduling algorithm (SPPM) for Revmm. Experiments confirm that this algorithm ensures stable real-time performance for the highest-priority RTOS. © 2024 IEEE.

关键词： scheduling algorithms

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Analysis and scheduling for Flexible Job Shop Problem based on Unreliable Degraded Machine Model and Finite Buffers

Analysis and Scheduling for Flexible Job Shop Problem based ...

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2024 China Automation Congress, CAC 2024

作者： Shangguan, Panpan Jia, Zhiyang Shi, Lengandong Yin, Sijie Duan, Minghao Zhang, Jianchao School of Automation Beijing Institute of Technology Beijing China Beijing Research Institute of Automation for Machinery Industry Co. Ltd Beijing China

ISBN: (纸本)9798350368604

In recent decades, the Flexible Job Shop scheduling Problem (FJSP) has been widely studied. From a theoretical perspective, the FJSP with a fixed number of jobs has attracted significant attention. In actual production environments, machine performance can fluctuate due to factors such as workload and maintenance status, and machine performance does not remain constant but changes with the processing of workpieces. Therefore, it is necessary to study a FJSP model based on unreliable degraded machines and finite buffers. In this paper, a model of unreliable degraded machine is established, and the processing time of workpieces on degraded machines is calculated based on this model. Using the accurate processing times, an improved genetic algorithm is employed to solve the scheduling problem in flexible job shop production. The effectiveness of the algorithm is verified through numerical experiments. © 2024 IEEE.

关键词： scheduling algorithms

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Perturbation Event Oriented Dynamic Task scheduling Algorithm for Parallel Testing of Control Systems

Perturbation Event Oriented Dynamic Task Scheduling Algorith...

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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2024

作者： Chen, Jingyi Wang, Shenhang Tong, Xiaoxuan Xiang, Gang Yu, Yang Zhan, Ziyuan School of Electronic and Information Engineeer Harbin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute System Design Department Beijing China Beijing Aerospace Automatic Control Institute Beijing China Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China

ISBN: (纸本)9798350388855

Task scheduling algorithms are key to research and practice in parallel testing techniques, especially in control system applications. The complexity of control system testing requires higher scheduling efficiency. However, perturbation events caused by test equipment problems, data transmission obstacles, or task changes are almost unavoidable and may reduce the scheduling effectiveness or even lead to system crashes. Therefore, in this paper, based on the analysis of the dynamic test scheduling model, a disturbance factor is designed to judge the urgency of disturbance events for evaluating the dynamic scheduling cycle. On this basis, based on the comprehensive rescheduling index, a suitable adjustment strategy is selected to formulate the dynamic test scheduling scheme. The experimental results show that the algorithm proposed in this paper can achieve fast response capability for different disturbance events and exhibit good adaptivity. © 2024 IEEE.

关键词： scheduling algorithms

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Research on Cloud-Fog Computing Task scheduling Based on Classification Mining 4

Research on Cloud-Fog Computing Task Scheduling Based on Cla...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Liu, Lindong Zeng, Xiaoning Qin, Yuehai Guangdong University of Education School of Computer Science Guangzhou China Guangdong University of Education School of Mathematics Guangzhou China

ISBN: (纸本)9798350363586

In the Fog Computing environment, it is necessary to study the task scheduling problem of Cloud-fog in order to meet the resource requirements of task scheduling, reduce data transmission during task scheduling, and improve the throughput of Fog Computing systems. By improving and optimizing the classification mining algorithm, the classification mining algorithm is integrated into the Cloud and Fog task scheduling model, integrating the characteristics of Fog and Cloud. A Cloud-Fog fusion task scheduling model based on classification mining and CFCM task scheduling algorithm are proposed in the paper. The algorithm first schedules the corresponding tasks directly to the Fog layer or Cloud layer based on the generated classification rules, and then transfers the tasks to specific computing nodes of Cloud layers or Fog layer. Simulation experiments showed that the CFCM algorithm has better performance in reducing task execution time and average waiting time compared to similar algorithms. © 2024 IEEE.

关键词： scheduling algorithms

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Research on traffic scheduling algorithm and parameter optimization based on load balancing in time-sensitive network 4

Research on traffic scheduling algorithm and parameter optim...

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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Chen, Zhao Beijing Institute of Mechanical Equipment Beijing China

ISBN: (数字)9781510680265

ISBN: (纸本)9781510680258

Time-sensitive network (TSN) guarantees deterministic delivery of traffic by prioritizing it differently. Commonly used traffic scheduling algorithm is time-aware shaper (TAS) combined with credit-based shaper (CBS). Aiming at the problem of excessive reserved bandwidth for stream reservation (SR) traffic during CBS scheduling, a traffic scheduling strategy based on load balancing was proposed. And the reserved bandwidth parameters of the SR traffic were optimized after completing the modeling of its delay problem. This strategy sliced and encapsulated the SR traffic packets into equal-length data frames at the end nodes and made them uniformly transmitted during the sending cycle. It reduced the end-to-end worst response time of the SR traffic due to packet congestion. After that the delay model was solved using simulated annealing algorithm to get the optimal reserved bandwidth. Simulation results showed that the proposed SR traffic scheduling strategy effectively reduced the reserved bandwidth and the delay of traffic transmission inside the switch on the basis of satisfying the traffic schedulability. © 2024 SPIE.

关键词： scheduling algorithms

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Optimized scheduling of Virtual Power Plant Based on Multiple Target Particle Swarm 4

Optimized Scheduling of Virtual Power Plant Based on Multipl...

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4th International Conference on Smart Grid and Energy Internet, SGEI 2024

作者： Li, Haowei Qian, Sujin Zhang, Xuesong Hu, Man Wang, Nan Chen, Wenlun Chen, Zhengda Jiang, Tong School of Electrical and Electronic Engineering North China Electric Power University Beijing China Beijing E-techstar Co. Ltd Beijing China

ISBN: (纸本)9798350368314

An optimal scheduling model that integrates economic development and environmental protection is proposed for a virtual power plant (VPP) system composed of photovoltaic (PV) cells, wind turbines, micro-turbines, and energy storage. The model addresses a multi-objective optimization problem, encompassing both operational costs and pollution treatment expenses under system constraints. Additionally, the model focuses on the optimal dispatch problem in the operation of the VPP. Simulation results demonstrate that the proposed optimal dispatch model for the VPP holds significant guiding value for both economic and environmental objectives. ©2024 IEEE.

关键词： scheduling algorithms

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Dynamic Slot Injection and Queue Allocation scheduling Algorithm Implementing Hybrid Flow scheduling In TSN 7

Dynamic Slot Injection and Queue Allocation Scheduling Algor...

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7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Guo, Yang Chang, Yingxian Yu, Zhanpeng Liu, Xin Liu, Donglan Zhang, Hao Yao, Honglei Beijing China-Power Information Technology Co. LTD Beijing China State Grid Shandong Electric Power Company Shandong China State Grid Shandong Electric Power Research Institute Shandong China

ISBN: (纸本)9798350339161

Time-sensitive networks provide deterministic, low-latency, and reliably delivered data transmission to existing networks, while being able to retransmit traffic of different priorities on the same network. To achieve this reliable transmission, the Time Sensitive Networking Standard defines a number of flow scheduling methods. In this paper, we innovate the TAS and CQF hybrid scheduling mechanism and propose an algorithm for dynamic slot injection. Compared with the existing hybrid scheduling, the scheduling algorithm in this paper can schedule more mixed time-sensitive traffic. The dynamic time slot injection algorithm dynamically adjusts the injection time slots of different periods of the same stream, and plans the optimal injection time slots for each stream. At the same time, the CQF mechanism has been improved, and a dynamic queue has been added to increase the number of cached streams in the same time slot. We compare the algorithm of this paper with the HSTC algorithm, and the success rate and number of flow scheduling in this paper are much larger than those of the HSTC algorithm. © 2024 IEEE.

关键词： scheduling algorithms

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