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Version Age of Information Minimization Over Fading Broadcast Channels

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第2期24卷 1620-1634页

作者： Karevvanavar, Gangadhar Pable, Hrishikesh Patil, Om Bhat, Rajshekhar Vishweshwar Pappas, Nikolaos Indian Inst Technol Dharwad Dharwad 580011 Karnataka India Linkoping Univ Dept Comp & Informat Sci S-58183 Linkoping Sweden

We consider a base station (BS) that receives version update packets from multiple streams and broadcasts them using non-orthogonal multiple access (NOMA) over a fading broadcast channel. Sequentially indexed packets arrive randomly, rendering previous ones obsolete. The version age of information (VAoI) at a user is defined as the difference between the latest packet's version index at the BS and at the user. Our objective is to minimize the average VAoI across users, subject to an average power constraint at the BS, by optimally scheduling and transmitting packets with sufficient power for successful delivery. We consider channel-only stationary randomized policies (CO-SRP), making transmission decisions based on channel power gains, and obtain optimal CO-SRP, showing that VAoI achieved with CO-SRP is within twice the optimal VAoI. We also develop a Constrained Markov Decision Process (CMDP)-based solution, several heuristic benchmarks, and analyze CMDP policy properties. Simulations compare achievable VAoI and computational performance of various policies and reveal differences between optimizing AoI and VAoI. Notably, a scheme allowing transmission to at most one user at a time matches NOMA's performance under strict power constraints but is outperformed when constraints are relaxed. Additionally, AoI-optimized policies result in higher VAoI compared to VAoI-optimized policies and vice versa, when user arrival rates are mismatched.

关键词： NOMA Fading channels Streams Optimization Decoding Transmitters Minimization Information age Wireless communication Time division multiple access Version age of information non-orthogonal multiple access time division multiple access broadcast channel scheduling algorithms

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The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第1期24卷 150-164页

作者： Ganesan, Ashwin Atlas SkillTech Univ Mumbai 400070 Maharashtra India

An assumption that researchers have often used to model interference in a wireless network is the unit disk graph model. While many theoretical results and performance guarantees have been obtained under this model, an open research direction is to extend these results to hypergraph interference models. Motivated by recent results that the worst-case performance of the distributed maximal scheduling algorithm is characterized by the interference degree of the hypergraph, in the present work we investigate properties of the interference degree of the hypergraph and the structure of hypergraphs arising from physical constraints. We show that the problem of computing the interference degree of a hypergraph is NP-hard and we prove some properties and results concerning this hypergraph invariant. We investigate which hypergraphs are realizable, i.e. which hypergraphs arise in practice, based on physical constraints, as the interference model of a wireless network. In particular, a question that arises naturally is: what is the maximal value of r such that the hypergraph K-1,K-r is realizable? We determine this quantity for various integral and nonintegral values of the path loss exponent of signal propagation. We also investigate hypergraphs generated by line networks.

关键词： Interference scheduling algorithms Stars scheduling Signal to noise ratio Propagation losses Applications of hypergraph theory applied algorithms cellular systems distributed algorithms hypergraph models interference degree maximal scheduling unit disk graphs wireless networks wireless networks

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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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FlexTAS: Flexible Gating Control for Enhanced Time-Sensitive Networking Deployment

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年

作者： Lin, Jiashuo Li, Weichao Feng, Xingbo Zhan, Shuangping Ning, Lewei Wang, Yi Wang, Tao Wan, Hai Tang, Bo Tao, Xiaofeng Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen 518055 Peoples R China Pengcheng Lab Shenzhen 518055 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China Tsinghua Univ Sch Software Beijing 100084 Peoples R China

Time-sensitive networking (TSN), essential in industrial networks for its promise of reliable and deterministic data transmission, faces deployment challenges due to the limitations of existing time-aware shaper (TAS)-based scheduling algorithms. Specifically, the size of the generated gate control lists (GCLs) is usually too large to be deployed in actual devices. To bridge the gap between theory and practice, we propose FlexTAS, a flexible and practical solution for TSN. The key insight behind FlexTAS is that relaxing gating does not introduce uncertainty, as long as nonoverlap reserved time slots are guaranteed. FlexTAS is comprised of two main components: first, a novel gating model deviates from the conventional TAS model by incorporating selective relaxation of gating at certain nodes;and second, a deep reinforcement learning-based engine to rapidly generate valid schedules. We build a real testbed and validate the effectiveness of our proposed solution. Our evaluation demonstrates that FlexTAS effectively controls the number of gate entries within the GCL capacity of devices, while simultaneously meeting the Quality of Service(QoS) requirements of time-triggered streams. It significantly reduces the number of GCL entries by 60% to 80%, and facilitates deployment in heterogeneous networks, thus offering a practical solution for TSN.

关键词： Streams Logic gates Jitter Job shop scheduling Delays Quality of service Engines Analytical models Synchronization scheduling algorithms Deterministic network flexible gating control network scheduling time-sensitive networking (TSN)

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Multigranularity Interleaved Reconfigurable Edge Data Center Network Architecture for Accelerated GAI Jobs

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IEEE INTERNET OF THINGS JOURNAL 2025年第10期12卷 13222-13232页

作者： Teng, Yun Yang, Hui Yao, Qiuyan Cheng, Wenlong Hao, Miao Zhang, Jie Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

The network has become a bottleneck for generative artificial intelligence (GAI) jobs. Accelerating GAI jobs in edge data centers using hybrid electrical/optical switch is considered a promising solution. This architecture optimizes bandwidth utilization by enabling demand-aware topology reconfiguration through flexible configuration of optical circuit switche optical circuit switches (OCS). However, frequent topology reconfiguration may increase latency. Therefore, there is a balanced relationship between latency and bandwidth utilization. In this article, we propose a multigranularity adaptive interleaved algorithm for service scheduling in edge data centers. First, different degrees of time slot shifts are introduced based on the latency sensitivity of jobs, where large bandwidth GAI jobs are transmitted in a single hop by configuring a demand-aware topology. Additionally, when the reconfiguration threshold is met, low-priority ports are prioritized for reconfiguration to ensure latency requirements are met. This approach effectively resolves the tradeoff between bandwidth utilization and latency by decoupling them from each other. Simulation results show that this approach can effectively reduce the latency and improve the network throughput.

关键词： Optical switches Data centers Bandwidth Computer architecture scheduling algorithms Topology Cloud computing Switching circuits Low latency communication Optical fiber networks Demand-aware topology reconfiguration edge data centers hybrid electrical/optical switch multigranularity adaptive interleaving algorithm

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Reproducibility Report for ACM SIGMOD 2023 Paper: "MorphStream: Adaptive scheduling for Scalable Transactional Stream Processing on Multicores"

Reproducibility Report for ACM SIGMOD 2023 Paper: "MorphStre...

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2024 International Conference on Management of Data, SIGMOD ARI Reports 2024

作者： Singh, Ayushi Helmer, Sven Mao, Yancan Zhao, Jianjun Zhang, Shuhao Netflix Los GatosCA United States University of Zurich Zurich Switzerland National University of Singapore Singapore Singapore Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798400711794

We were able to reproduce the findings of the original paper. This includes performance comparisons with other systems, measurements of throughput and latency for different workloads and scheduling strategies, handling of abort decisions, and scalability comparisons. In total, this involves sixteen different figures in the original paper that were reproduced. © 2024 Copyright held by the owner/author(s).

关键词： scheduling algorithms

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Optimized Multitask scheduling in Cloud Computing Using Advanced Machine Learning Techniques

Optimized Multitask Scheduling in Cloud Computing Using Adva...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Vullam, Nagagopi Raju Geetha, Gorikapudi Rao, Nagamalleswara Vellela, Sai Srinivas Rao, Thalakola Syamsundara Thommandru, Raju Rao, Kolla Naga Sreenivasa Chalapathi Institute of Engineering and Technology Dept. of Cse AP Guntur India Chalapathi Institute of Technology Dept. of CSE-AI AP Guntur India Chalapathi Institute of Technology Dept. of Cse AP Guntur522016 India Chalapathi Institute of Technology Dept. of CSE-DS AP Guntur522016 India Kkr & Ksr Institute of Technology and Sciences Dept. of CSE-DS AP Guntur522017 India Chalapathi Institute of Technology Dept. of Ece AP Guntur522016 India Chalapathi Institute of Technology A.P Guntur522016 India

ISBN: (纸本)9798331527495

The delivery of computing services over the internet is known as cloud computing. One of most important problem in the cloud computing environment task scheduling, which has a direct affect on the platform's overall performance. Tasks are scheduled for specific resources at specific times based on user requests. It mainly focuses maximize resource utilization, minimize make span. Task scheduling in cloud is still a problem even if there are several ways to improve it. One important step in effectively harnessing cloud computing potential is scheduling tasks efficiently. In this work, machine learning technique is presented for improved multitask scheduling in cloud computing. For efficient task scheduling, we propose ML feature-based heuristic task scheduling (MLF-H). Instead of randomly assigning a scheduling algorithm, ML techniques are used to incoming task requests to classify best suitable algorithm for task. Simulations results show that MLF-H task scheduling approach has shortest make span and rapid generalization capabilities when compared to traditional methods. This proves the availability of the approach and the efficiency of the MLF-H scheduling algorithm. © 2025 IEEE.

关键词： scheduling algorithms

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NAGA: A Deterministic Programmable Network With Update Timing Guarantees

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2025年第2期22卷 1874-1888页

作者： Deric, Nemanja Varasteh, Amir Blenk, Andreas Kellerer, Wolfgang Tech Univ Munich Chair Commun Networks D-80333 Munich Germany Siemens AG Fdn Technol Dept D-80333 Munich Germany

There is no system yet that provides predictable data plane and control plane operations in programmable networks. However, both predictable data plane and control plane operations are needed, e.g., in industrial networks. Particularly there, the operation of the network needs to be planned and, hence, relies on network operations that are deterministic and executed in a timely manner. To fill this gap, this paper proposes our system named NAGA, which provides data plane deterministic guarantees along with consistent and timely network updates in programmable networks. In order to not rely on specialized hardware, NAGA uses widely-available hardware capabilities such as priority queuing and label-based forwarding. Whereas the real implementation of NAGA in a P4-based testbed demonstrates that applications receive guaranteed performance in terms of latency and data rate, simulation studies show the ability of NAGA to be even deployed in large scale scenarios beyond industrial networks, such as wide area and data center networks.

关键词： Control systems Hardware scheduling algorithms Process control Delays Tagging Scalability Runtime Production facilities Packet loss Network control deterministic networking programmable devices

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Economic Optimal scheduling of Integrated Energy System Based on Improved DQN Algorithm 1st

Economic Optimal Scheduling of Integrated Energy System Base...

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1st Electrical Artificial Intelligence Conference, EAIC 2024

作者： Ye, Ning Li, Ke Wang, Xuerui Wang, Haiyang Zhang, Chenghui School of Control Science and Engineering Shandong University Shandong Province Jinan250061 China

ISBN: (纸本)9789819648559

Integrated energy systems have a significant role and non-negligible importance in modern energy systems. In order to improve the operating economy of the integrated energy system and at the same time to cope with the challenges brought by multiple uncertainties within the system, an economic scheduling model of the integrated energy system is proposed and solved by deep reinforcement learning method. Firstly, the optimal scheduling problem of the integrated energy system is mathematically modeled;secondly, it is converted into the expression form of Markov decision process, and the state, action space and reward function are established;after that, the DQN algorithm is improved to increase the training speed and stability of the algorithm, and the optimal scheduling problem is solved with the goal of economy. Finally, the effectiveness and superiority of the proposed method in optimized scheduling of integrated energy systems are verified through arithmetic simulation and comparison with traditional algorithms. © The Author(s) 2025.

关键词： scheduling algorithms

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Intelligent course scheduling method and its optimization based on multi-stage heuristic algorithm 5

Intelligent course scheduling method and its optimization ba...

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5th International Conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Xia, Yeqin Policarpio, Princess Angeles University Foundation Angeles Philippines

ISBN: (纸本)9781510691667

The advancement of artificial intelligence technology has brought breakthrough progress to the field of education. A multi-stage heuristic algorithm based intelligent class scheduling method is designed to solve the shortcomings of low efficiency and poor resource utilization in existing class scheduling problems. Research on generating initial shift plans through greedy strategies and optimizing the shift method using simulated annealing algorithm. In order to ensure efficient and reasonable course scheduling for each class, a scheduling method based on competitive search algorithm is raised. The findings denoted that when the number of iterations was 100, the proposed algorithm reduced the objective function by 68.13% compared to the control allocation algorithm. When the number of iterations reached 900, the average value of the course uniformity objective function of the course scheduling algorithm proposed by the research institute decreased by 76.92% compared to the initial value. The outcomes denoted that the raised method has excellent performance in both class allocation optimization and scheduling optimization problems, and has critical theoretical and practical significance for promoting the informatization and intelligence process in the field of education management. © 2025 SPIE.

关键词： scheduling algorithms

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