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Dynamic extended sigmoid-based scheduling with virtualized RB allocation for maximizing frequency numerology efficiency in 5G/B5G NR networks

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Computer Networks 2023年 237卷

作者： Chang, Wei-Teng Chang, Ben-Jye Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Taiwan

New trends of extremely ultra-low delay, ultra-high reliability, long-distance high-moving, etc., are strongly required for achieving Emergency resecure, Active Safe Driving (ASD), IoV communications, LEO communications, etc. Thus, 3GPP 5 G/B5G specifies flexible numerology technology providing different frequency SCS modes with different slot-times for diverse types of flows requiring different 5QIs in terms of delay, data rate, jitter, loss probability, and reliability. Although based on the frequency numerology, 3GPP Release 17 specifies three types of RB allocations, i.e., Types 0, 1, and dynamic switching allocations for UL access, such static and consecutive RB allocations result in inefficient numerology and frequency spectrum efficiency. As a result, typical critical issues exhibit in B5G NR, including high mutual exclusion (MX) of numerology, RB state independency flow scheduling, and static RB allocations suffering from dynamic flowing traffic. Thus, this paper proposes the Extended Sigmoid-based scheduling with a Virtualized RB Allocation (SSA) consisting of two phases. Phase 1 proposes an Extended Sigmoid-based Cost-based Flow scheduling (SCFS) algorithm to dynamically differentiate flow priorities. Phase 2 proposes a dynamic Virtualized RB pre-Allocation (VRBA) mechanism to maximize radio RB utilization and minimize mutual exclusion in 5 G frequency numerology. Numerical results indicate that the proposed SSA outperforms the compared approaches in network delay, jitter, resource utilization, network reward, and net-profit. Consequently, this paper achieves several objectives and contributions: 1) analyzing the QoS requirements of different applications with limited frequency spectrum, 2) proposing vRB state-related dynamic flow scheduling algorithm to maximize network efficiency, 3) minimizing numerology MX for vRB allocation, and 4) proposing adaptive cost-reward-based scheduling. © 2023

关键词： scheduling algorithms

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Low-latency Deterministic Forwarding for Multi-modal Connection Using Time-Sensitive Networking 23

Low-latency Deterministic Forwarding for Multi-modal Connect...

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2023 ACM Turing Award Celebration Conference, CHINA 2023

作者： Zhang, Weichen Dang, Fan Wang, Xu Global Innovation Exchange Tsinghua University Beijing China

ISBN: (纸本)9798400702334

This poster proposes a low-latency deterministic forwarding technology for multi-modal data based on time-sensitive networks. It presents the design and implementation of an FPGA-based switch that can handle data frames of different protocols, including Ethernet, PROFINET, and EtherCAT. The switch consists of an input port, an output port, a clock module, an exchange module, and a gate control module. Its core is the switch module, which comprises four sub-modules: protocol identification, caching, handling, and conversion. To prioritize critical traffic over normal traffic, the switch implements a priority-based scheduling algorithm. It also provides timestamping for performance analysis. Through the proposed technology and switch design, the poster aims to improve low-latency deterministic forwarding for time-sensitive multi-modal data. © 2023 Owner/Author.

关键词： scheduling algorithms

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An Efficient Design Framework for 2×2 CNN Accelerator Chiplet Cluster with SerDes Interconnects 5

An Efficient Design Framework for 2×2 CNN Accelerator Chipl...

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5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023

作者： Wu, Yajie Li, Tianze Shao, Zhuang Du, Li Du, Yuan Nanjing University Nanjing China

ISBN: (纸本)9798350332674

Multi-Chiplet integrated systems for high-performance computing with dedicated CNN accelerators are highly demanded due to ever-increasing AI-related training and inferencing tasks;however, many design challenges hinder their large-scale applications, such as complicated multi-task scheduling, high-speed die-to-die SerDes (Serializer/Deserializer) link modeling, and detailed communication and computation hardware co-simulation. In this paper, an optimized 2×2 CNN accelerator chiplet framework with a SerDes link model is presented, which addresses the above challenges. A methodology for designing a 2×2 CNN accelerator chiplet framework is also proposed, and several experiments are conducted. The system performances of different designs are compared and analyzed with different design parameters of computation hardware, SerDes links, and improved scheduling algorithms. The results show that with the same interconnection structure and bandwidth, every 1TFLOPS increase in one chiplet's computing power can bring an average 3.7% execution time reduction. © 2023 IEEE.

关键词： scheduling algorithms

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An Energy Saving Control Strategy Based on Multi-Agent Q-Learning Algorithm for Data Center 2

An Energy Saving Control Strategy Based on Multi-Agent Q-Lea...

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2022 2nd International Conference on Communication Technology and Information Technology, ICCTIT 2022

作者： Yu, Hui Xia, Ying Network Information Center Wuhan University of Technology Wuhan430000 China

In recent years, the application of green renewable energy to data centers has become an important trend. Traditional solutions lack the consideration of matching tasks to renewable energy supplies. Therefore, in the face of diverse real-time computing tasks, how to reduce the total energy cost while ensuring the quality of service is an important challenge for the data center in the future. In this paper, our focus is on using the information on renewable energy supply and task characteristics as input states to assign tasks that maximize user satisfaction while meeting the minimum total cost of energy consumption. We consider the diversity of real-time tasks and design three different task types: the most crucial task, the crucial task and the non-crucial task. According to the different characteristics of these tasks, we propose a scheduling algorithm based on multi-agent, which uses multiple sets of agents with different initial positions to parallel search in different dimensions of the parameter space to find the optimal solution. To further optimize the algorithm, we eliminate the centralized noise solution based on the Pareto sorting method and sort the multiple optimal solutions to highlight the most suitable solution. The experimental results show that the proposed algorithm compared with other algorithms can reduce the total energy consumption by 11% and increase the customer satisfaction by 13% on average, and has better performance and applicability. © Published under licence by IOP Publishing Ltd.

关键词： scheduling algorithms

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Enhancement of Cloud Performance using the Clustering Method of Scientific Workflow Task

Enhancement of Cloud Performance using the Clustering Method...

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Singh, Bhaludra R Nadh Raina, Kandikatla Janapareddy, Thanmayee Shivani, Namani Narendruni, Lakshmi Priya Sheri, Shiva Varshini Reddy Bhoj Reddy Engineering College for Women Department of Computer Science and Engineering Hyderabad India Nalla Malla Reddy Engineering College Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350317060

The scientific community may save money using cloud computing to roll out massive workflow apps. scheduling workflow jobs with changing resources is a complex problem when running large-scale scientific applications for workflow in a distributed heterogeneous environment. In addition, a scheduling algorithm has to effectively use the resource's time in a utility-based computing environment like the cloud, which allows for a pay-per-use model of the resources. The cloud is inherently dynamic, yet most scheduling methods ignore this and instead generate static schedules. A public cloud setting, such as Amazon EC2, has access to a plethora of resources and pays for them hourly. Any time used in fractions of an hour is rounded up to the nearest whole hour. The proposed work centres on integrating an accounting model cognizant task clustering technique into the workflow scheduling procedure to satisfy the customer's budget and deadline. A method for selecting the most appropriate resources at any given point in a process is also presented. Two scientific programs, Montage and Cyber Shake, were run with varying resources and task clustering methods, and the first findings are described. © 2023 IEEE.

关键词： scheduling algorithms

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A Digital Twin-Based Robotic Control Framework for Rocket Launch Missions

A Digital Twin-Based Robotic Control Framework for Rocket La...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Hongru Shen, Tingzheng Suo, Xiangbo Fan, Li College of Control Science and Engineering Zhejiang University Hangzhou China Jiuquan Satellite Launch Center Jiuquan China College of Control Science and Engineering Zhejiang University Huzhou Institute Zhejiang University Huzhou China

ISBN: (纸本)9798350303759

Using robots in rocket launch missions has difficulties in technical verification, task scheduling, monitoring, and optimization. In this paper, we take digital twin (DT) as a systematic toolkit to manage the task of robots, making full use of its inherent advantages in simulation and scheduling complex tasks. We propose a DT-based robotic control framework (DTRCF) for rocket launch missions, which consists of three subsystems: physical entity system, task scheduling system, and virtual entity system. During the launch mission, commands are generated autonomously in the task scheduling system deployed on the cloud and sent to physical entities of robots through the connection layer. Through performing bi-directional mapping of virtual space and physical space, the DT-based robotic control framework covers three stages of launch missions, including verification, execution, and optimization. We designed a prototype of this framework and conducted related experiments to prove the feasibility of our design. © 2023 IEEE.

关键词： scheduling algorithms

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FIPO: Software-Defined Packet scheduling Primitive for Time-Sensitive Networking 17th

FIPO: Software-Defined Packet Scheduling Primitive for Time-...

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CCF 17th International Conference on Service Science, CCF ICSS 2024

作者： Liu, Shang Gao, Shuai Chen, Jia Huang, Xu Qian, Dongsheng Liao, Chenxi National Engineering Research Center for Advanced Network Technologies School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Peng Cheng Laboratory Shenzhen518055 China

ISBN: (纸本)9789819757596

Software-Defined Networking (SDN) improves the flexibility of the network by separating the data plane and the control plane, bringing revolutionary changes to the network architecture. However, with the development of metaverse as well as holographic technology, applications require the network to provide different levels of deterministic transmission guarantees including data rate, delay, and jitter. In addition, these deterministic requirements may also change over time. This demands the network to have diverse deterministic transmission capabilities on the one hand, and to flexibly and quickly switch deterministic transmission mechanisms according to the application requirements on the other hand. In this paper, we propose a new software-defined packet scheduling primitive, First-In-Pick-Out (FIPO). FIPO integrates SDN with Time-Sensitive Networking (TSN) to achieve programmable deterministic transmission. FIPO can express existing TSN scheduling algorithms, and is flexible enough to support future algorithms. Furthermore, based on FIPO we design a software-defined packet scheduling prototype system, which can support flexible switching of diverse deterministic transmission mechanisms. The experimental results show that the prototype system is able to correctly express diverse deterministic scheduling algorithms and quickly respond to changes in network requirements, reducing configuration time by 60% compared to NETCONF. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： scheduling algorithms

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Dependency, Deadline and Priority Aware Multi-Queue Dynamic Task scheduling Using Heterogeneous Resources in Fog Environment

Dependency, Deadline and Priority Aware Multi-Queue Dynamic ...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Maneesha Rani Saha Muhammad Ehsanul Kader Rezwana Reaz Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9798350367201

ISBN: (纸本)9798350367218

Internet of Things (IoT) has emerged as a transformative paradigm and revolutionized our way of engaging with technology in everyday life. The limited computing resources and storage capacity of IoT devices have necessitated the integration of heterogeneous fog resources in IoT task execution. Moreover, some IoT applications such as healthcare services are highly delay-sensitive; hence need immediate processing and response. On the other hand, the best utilization of heterogeneous storage and processing capacity of fog resources plays a pivotal role in improving the response time of IoT applications. Thus, an adaptive task scheduling algorithm for executing IoT tasks in a fog environment is required which will consider the heterogeneity of available resources and various response time requirements of different IoT applications. In this paper, we propose a non-preemptive batch task scheduling algorithm with dynamic resource allocation. The proposed method addresses the challenges of scheduling tasks with varying priority levels, deadline constraints, and dependencies utilizing the concepts of Directed Acyclic Graphs (DAGs), priority queues, and dynamic queue switching. We introduce a novel numerical scoring mechanism that prioritizes the execution of tasks with higher urgency and critical dependencies. The major goals of the proposed technique are to reduce the overall average response time, makespan, and increase the throughput. We have implemented our algorithm in a Java based proprietary simulator. Our simulation results demonstrate that the proposed algorithm significantly improves the average response time, makespan and throughput compared to the existing priority based batch scheduling algorithms. Precisely, our algorithm reduces average response time by at least 50.2%, makespan by at least 8.18%, and increases throughput by at least 13%, task completion rate by at least 4.3% compared to Shortest Job First (SJF) and Multi Level Feedback Queue (MLFQ).

关键词： scheduling algorithms Heuristic algorithms Switches Medical services Dynamic scheduling Throughput Internet of Things Time factors Resource management Edge computing

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Fault-Tolerant scheduling of Scientific Workflow in Cloud Computing

Fault-Tolerant Scheduling of Scientific Workflow in Cloud Co...

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Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), International Conference on

作者： Archana Pandita P.K Upadhyay Ved Prakash Mishra Department of Computer Science and Engineering Amity University Dubai Department of EEE Birla Institute of Technology

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

Cloud computing, a pivotal technology offering computational services through diverse deployment models, faces challenges in experimentation and testing due to high infrastructure access costs and limited scalability of testbeds. This research introduces Workflowsim, a simulation tool building on CloudSim, facilitating high-level workflow management. The system in-corporates dynamic clustering, enabling fine-grained task consolidation into coarser clusters. However, existing algorithms, such as MinMin and FCFS, exhibit runtime overhead in layered architectures. The paper proposes fault-tolerant scheduling using Dynamic ReClustering, addressing task and job failures in scientific workflows. Employing a Failure Generator and Failure Monitor, the system simulates failures, adjusting clustering dynamically through Reclustering. The proposed algorithm optimizes task scheduling based on dependencies, significantly reducing waiting times. The experi-mental results, implemented on Workflowsim, demonstrate the effectiveness of the proposed fault-tolerant scheduling algorithm, outperforming existing methods in makespan and mean execution time for scientific workflows.

关键词： Cloud computing Fault tolerance Runtime scheduling algorithms Heuristic algorithms Scalability Fault tolerant systems Clustering algorithms Dynamic scheduling Testing

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Research on Multi-Task scheduling in Smart Warehouse Systems Based on Dual-Task Chains

Research on Multi-Task Scheduling in Smart Warehouse Systems...

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IEEE International Conference on Networking, Sensing and Control

作者： Chenwei Zhang Weimin Wu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

With the advancement of warehousing technology, the allocation of multiple tasks in multi-AGV systems has become an important factor in order to decrease task completion time in the warehouse. This paper develops a multi-task scheduling algorithm that employs a dual-task chain approach to maximize task execution benefits. For the multi-task allocation problem, this paper proposes a dual-task chain-based task allocation algorithm (DTTA), which uses the dual-task chain strategy as a mechanism for selecting multiple tasks, taking into consideration derived tasks to enhance solution quality. Simulation experiments show that the proposed algorithm and model perform better than other methods.

关键词： scheduling algorithms Simulation Warehousing System recovery Multitasking Sensors Batteries Resource management Collision avoidance

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