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Efficient Flow scheduling for Industrial Time-Sensitive Networking: A Divisibility Theory-Based Method

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2022年第12期18卷 9312-9323页

作者： Zhang, Yanzhou Xu, Qimin Xu, Lei Chen, Cailian Guan, Xinping Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manag Shanghai 200240 Peoples R China

As an emerging communication technology, time-sensitive networking (TSN) promises the real time and deterministic interaction of massive data in Industrial Internet of Things. However, it is challenging to schedule the time-sensitive flows timely and superiorly through the mechanism analysis for current TSN scheduling models, especially in complex industrial scenarios. In this article, we propose an analysis approach of flow sequences based on divisibility theory to characterize the flow conflicts and dependencies, which derives the scheduling flexibility based on flow position diversity (PD) and the equivalent flow judgment conditions for slot occupancy. Integrating the abovementioned derivation, a parallel computing framework with the generalized slot length is established to lower the scheduling complexity. Within each computing unit, an incremental scheduling algorithm with the flow judgment conditions and PD-based search boundary is proposed. It reduces the scheduling complexity further while maintaining load balance for the mixed transmission of periodic and aperiodic flows. To achieve the optimality of runtime and load balance, two PD-based flow sorting strategies are designed, respectively. The evaluation results show that compared with the existing works, the runtime efficiency of scheduling at scale is increased by at least 1500 times in complex traffic scenarios while the load balance on the network links is also improved.

关键词： Job shop scheduling Optimal scheduling Switches Load modeling Sorting Industrial Internet of Things scheduling algorithms Divisibility theory flow judgment conditions for slot occupancy flow sequence analysis scheduling flexibility time-sensitive networking (TSN)

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Bio-Inspired scheduling for Factory Automation in the TD-LTE System

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IETE TECHNICAL REVIEW 2022年第5期39卷 1189-1207页

作者： Ryu, Won Jae Satrya, Gandeva Bayu Shin, Soo Young Kumoh Natl Inst Technol ICT Convergence Res Ctr Gumi Si South Korea Telkom Univ Sch Appl Sci Bandung Indonesia Kumoh Natl Inst Technol Dept IT Convergence Engn Gumi Si South Korea

Wireless technology has advantages such as low cost, flexibility, relatively easy installation, and the ability to address routing issues. Consequently, wireless factory automation has received considerable attention recently. However, most wireless technologies in factory automation have adopted unlicensed bandwidth, which can be affected by interference from other users. Long-term evolution adopts a licensed bandwidth;therefore, it can be a solution for factory automation. This paper presents scheduling algorithms in wireless industrial networks for factory automation in wireless sensor networks using the TD-LTE system. To satisfy real-time requirements, scheduling algorithms based on bio-inspired optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), and firefly algorithm (FA), and dynamic frame configuration (DFC) are proposed to cover more nodes. Furthermore, the performances of these algorithms with and without DFC are evaluated.

关键词： Evolutionary computation Factory automation Firefly algorithms Genetic algorithms Particle swarm optimization scheduling algorithms TD-LTE Wireless communication

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Path-flow matching: Two-sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud date center network

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2022年第8期33卷

作者： Tan, Lizhuang Su, Wei Gao, Shuai Miao, Jingying Cheng, Yuan Cheng, Peng Beijing Jiaotong Univ Sch Elect & Informat Engn Natl Engn Lab Next Generat Internet Interconnect Beijing Peoples R China China Univ Petr Coll Comp & Commun Engn Qingdao Shandong Peoples R China

Improving the operational efficiency of data center has always been an important direction for the development of ICT. In this paper, we apply two-sided matching decision-making process in game theory to traffic scheduling problem in data center network. From the perspective of matching between flow and path, the traffic scheduling is properly arranged. We first propose and model the path-flow matching problem, considering the preference ordering, then formulate the problem as a multiobjective optimization problem with the target to ensure the stability and satisfaction from the matching scheme, and design a preference-based path-flow ordering method Extended PIAS, and finally propose a lightweight scheduling algorithm LinkGame based on multiobjective evolutionary algorithm. Compared with the previous scheduling methods (ECMP, Hedera, and Fincher), experiment results demonstrate that LinkGame can simultaneously consider the stability and satisfaction of the matching results, with improved bandwidth utilization and flow completion time.

关键词： scheduling algorithms

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Laser: Buffer-Aware Learned Query scheduling in Master-Standby Databases 51st

Laser: Buffer-Aware Learned Query Scheduling in Master-Stand...

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51st International Conference on Very Large Data Bases, VLDB 2025

作者： Huang, Yuwei Li, Guoliang Department of Computer Science Tsinghua University China

Master-standby database deployment is a commonly adopted database architecture in modern production environments, thanks to its fault tolerance and high availability. However, despite the architecture’s widespread application in various online services, relatively few research efforts have been made to improve its overall query performance. When a sequence of queries arrive, existing methods of scheduling them across master and standby servers still rely on rules or heuristics, which may overlook some potential optimization directions such as buffer utilization. If we can efficiently reuse the database buffers resident in memory through intelligent query scheduling, the average response time of user queries can be significantly reduced as opposed to reading data from disk. To address this issue, in this paper, we introduce a new buffera ware query scheduling system named Laser. The system integrates a lightweight learned model that can directly map a query to the data blocks it accesses. Then, based on the predictions of the queries, we develop adaptive query scheduling algorithms to perform queryal location as well as query rearrangements, aiming to maximize the overall buffer hit rate while also maintaining load balance. The proposed system requires no pre-training, and can adjust to unseen workloads on the fly through constant model updates and query re-allocation. In our experiments, we observe a reduction of ∼80%in query completion time compared to other traditional heuristic based methods, with relatively low extra overhead added to the critical path of query execution. © 2025, VLDB Endowment, All rights reserved.

关键词： scheduling algorithms

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University Timetable scheduling: A Heuristic and Machine Learning Approach 5th

University Timetable Scheduling: A Heuristic and Machine Lea...

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5th International Conference on Computing and Network Communications, CoCoNet 2023

作者： Priya, L. Kamatchi Bhat, Tushar Tsephel, Tenzin Rethwik, Voolla Sai Bansal, Tanya PES University Bangaluru India

ISBN: (纸本)9789819747108

The University Class scheduling Problem stands as a pivotal and intricate challenge within academia. A proficient university timetable holds the key to seamless academic operations, necessitating the delicate balance of multiple constraints like teacher availability and subject-hour allocations. This NP-Hard problem's complexity arises from its diverse limitations. Manual timetable creation presents a formidable task for educators and evaluators alike, underscoring the need for a system that fosters a balanced and equitable learning environment. This study introduces a novel university timetable scheduling algorithm adept at accommodating dynamic constraints, thus addressing the demand for adaptable and responsive scheduling solutions. By harnessing the potential of heuristic and machine learning algorithms, our Timetable scheduling System aims to efficiently generate schedules while adhering to specified constraints that should not be compromised, ensuring the production of high-quality timetables. Ultimately, this endeavor strives to streamline the timetable creation process, liberating educators to focus on delivering superior education and optimizing student outcomes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： scheduling algorithms

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On the Performance of Frequency-Mixing Reconfigurable Intelligent Surfaces-Aided System: Achievable Rates and Reflective Patterns

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第4期24卷 3117-3131页

作者： Yuan, Jide Huang, Huan Jin, Shi Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210000 Peoples R China

Frequency mixing reconfigurable intelligent surface (FMx-RIS) is an innovative concept within the realm of RIS technology. It distinguishes itself from conventional RIS by continuously modifying the phase of incident electromagnetic waves, thereby inducing frequency shifts. By uniquely associating FMx-RIS elements with a specific frequency, this approach allows receivers to distinguish channels from each propagation path by detecting the frequency shifts. This decoupling feature enables channel estimation and augments diversity gain in the frequency domain. In this paper, we explore the architectural aspects of FMx-RIS in both single-carrier and multi-carrier systems to validate its practicality. For single-carrier systems, we derive closed-form lower bounds for achievable data rates under scenarios with perfect and imperfect channel state information, alongside the corresponding power scaling laws. For multi-carrier systems, our focus lies in the scheduling of reflective patterns for FMx-RISs, recognizing that frequency mixing operations introduce additional inter-carrier interference among users. We introduce two scheduling algorithms designed to maximize the minimum user signal-to-interference-plus-noise ratio. The numerical results confirm the analytical achievable rates and demonstrate that the FMx-RIS-aided system surpasses conventional RIS-aided systems. Furthermore, we assess the effectiveness of the proposed scheduling algorithms, where the ADMM-based scheme exhibits similar performance to the SoTA scheme.

关键词： Reconfigurable intelligent surfaces Receivers Channel estimation Interference Frequency modulation Frequency estimation Time-frequency analysis Signal to noise ratio scheduling algorithms Oscillators Achievable rate intelligent reflecting surface (RIS) reflective pattern scheduling

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HRL-TSCH: A Hierarchical Reinforcement Learning-Based TSCH Scheduler for IIoT

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2024年第6期10卷 2102-2118页

作者： Jurado-Lasso, F. Fernando Orfanidis, Charalampos Jurado, J. F. Fafoutis, Xenofon Tech Univ Denmark Embedded Syst Engn Sect DTU Compute DK-2800 Lyngby Denmark Univ Nacl Colombia Sede Palmira Fac Engn & Adm Dept Basic Sci Palmira 763531 Colombia

The Industrial Internet of Things (IIoT) demands adaptable Networked Embedded Systems (NES) for optimal performance. Combined with recent advances in Artificial Intelligence (AI), tailored solutions can be developed to meet specific application requirements. This study introduces HRL-TSCH, an approach rooted in Hierarchical Reinforcement Learning (HRL), to devise Time Slotted Channel Hopping (TSCH) schedules provisioning IIoT demand. HRL-TSCH employs dual policies: one at a higher level for TSCH schedule link management, and another at a lower level for timeslot and channel assignments. The proposed RL agents address a multi-objective problem, optimizing throughput, power efficiency, and network delay based on predefined application requirements. Simulation experiments demonstrate HRL-TSCH's superiority over existing state-of-art approaches, effectively achieving an optimal balance between throughput, power consumption, and delay, thereby enhancing IIoT network performance.

关键词： Schedules Industrial Internet of Things Heuristic algorithms Delays scheduling algorithms Throughput Optimal scheduling Industrial Internet of Things (IIoT) Networked Embedded Systems (NES) sleep scheduling Time Slotted Channel Hopping (TSCH) Reinforcement Learning (RL) Software-Defined Wireless Sensor Networks (SDWSNs)

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The Freshness Game: Timely Communications in the Presence of an Adversary

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IEEE-ACM TRANSACTIONS ON NETWORKING 2024年第5期32卷 4067-4084页

作者： Banerjee, Subhankar Ulukus, Sennur Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA

We consider a communication system where a base station (BS) transmits update packets to $N$ users, one user at a time, over a wireless channel. We investigate the age of this status updating system with an adversary that jams the update packets in the downlink. We consider two system models: with diversity and without diversity. In the model without diversity, in each time slot, the BS schedules a user from $N$ users according to a user scheduling algorithm. The constrained adversary blocks at most a given fraction, alpha, of the time slots over a horizon of T slots, i.e., it can block at most alpha T slots of its choosing out of the total T time slots. We show that if the BS schedules the users with a stationary randomized policy, then the optimal choice for the adversary is to block the user which has the lowest probability of getting scheduled by the BS, at the middle of the time horizon, consecutively for alpha T time slots. The interesting consecutive property of the blocked time slots is due to the cumulative nature of the age metric. In the model with diversity, in each time slot, the BS schedules a user from N users and chooses a sub-carrier from N-sub sub-carriers to transmit update packets to the scheduled user according to a user scheduling algorithm and a sub-carrier choosing algorithm, respectively. The adversary blocks alpha T time slots of its choosing out of T time slots at the sub-carriers of its choosing. We show that for large T, the uniform user scheduling algorithm together with the uniform sub-carrier choosing algorithm is 2N(sub)/N-sub-1 optimal. Next, we investigate the game theoretic equilibrium points of this status updating system. For the model without diversity, we show that a Nash equilibrium does not exist, however, a Stackelberg equilibrium exists when the scheduling algorithm of the BS acts as the leader and the adversary acts as the follower. For the model with diversity, we show that a Nash equilibrium exists and identify the Nash

关键词： Schedules Games Nash equilibrium Jamming scheduling algorithms Information age Throughput Age of information information freshness jamming adversary game theory

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Research on substation camera inspection task scheduling method based on enhanced DDE-DTS algorithm 5

Research on substation camera inspection task scheduling met...

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5th International Conference on Computer Vision and Data Mining, ICCVDM 2024

作者： Wu, Xichun Lin, Feng Min, Peng Li, Haifeng State Grid Hubei Electric Power Co. Ltd. Yichang Power Supply Company Yichang443000 China College of Electricity and New Energy China Three Gorges University Yichang443000 China

ISBN: (纸本)9781510682863

An enhanced DDE-DTS algorithm is proposed to solve the substation camera inspection work task scheduling problem. Firstly, considering the camera scheduling problem in actual inspection tasks, the maximization of the minimum completion time of inspection work is set as the objective, and constraints are established to develop an optimization scheduling model. Then, a search space is established using transformer sequences as arrangement codes, and an improved WPF-NEH joint rule is proposed to generate the initial population. Furthermore, in order to improve the efficiency of the solution, an enhanced discrete differential evolution algorithm is employed in the global parallel search phase, and a dynamic taboo search algorithm that takes into account both concentration and diversity is proposed for the local search phase, forming an enhanced hybrid DDE-DTS algorithm. Finally, the algorithm is successfully applied to optimize the scheduling of substation camera inspections in actual inspection work. © 2024 SPIE.

关键词： scheduling algorithms

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A PPO-guided multi-population co-evolution algorithm for Distributed Flexible Assembly Flowshop scheduling Problem 24

A PPO-guided multi-population co-evolution algorithm for Dis...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Zhao, Fuqing Du, Yuqing Yin, Fumin School of Computer and Communication Lanzhou University of Technology Gansu China

ISBN: (纸本)9798400710681

A distributed flexible assembly flowshop scheduling problem(DFAFSP), which holds significant applications in modern large-scale manufacturing systems, is investigated in this paper. A PPO-guided multi-population co-evolution algorithm (PPO-MPCE) is introduced in response to the DFAFSP problem. Automatic algorithm design and a co-evolution among two populations are utilized to minimize the total flowtime objective in DFAFSP. A three-segment encoding method is devised for DFAFSP, and each segment implements a unique search strategy tailored to address the problem from a distinct physical perspective. Eight search states and a reward function are designed to evaluate the current population state for the PPO mechanism. Finally, the performance of random-MPCE, PPO-MPCE, and five existing algorithms are evaluated on 68 small-scale and 30 large-scale test instances. Simulation experiments in this paper indicate that the proposed algorithms outperform the latest algorithms in performance. © 2024 Copyright held by the owner/author(s).

关键词： scheduling algorithms

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