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IEEE Conference on Vehicular Technology (VTC)

作者： Wenhao Zou Zongshuai Zhang Nina Wang Xiaochen Tan Lin Tian Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Nanjing Institute of InforSuperBahn Nanjing China University of Chinese Academy of Sciences Nanjing China Department of Computer Science and Technology University of Cambridge United Kingdom

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

In common scenarios of cloud computing and edge computing, jobs are divided into tasks with dependencies, and task scheduling and computation are performed through containers. However, the cold start of containers significantly impedes the efficiency of short tasks. The existing research on cold starts faces challenges in addressing task scheduling with dependencies and may not fully exploit the distinct advantages offered by cloud and edge servers. On the other hand, there is limited research on using Deep Reinforcement Learning (DRL) to optimize container cold starts. Existing task scheduling algorithms based on DRL often struggle to handle scenarios with multiple jobs simultaneously. To reduce the job completion time of the system, this paper introduces a task scheduling algorithm based on DRL. By intelligently reusing containers and minimizing cold starts, the algorithm aims to simultaneously consider computing and communication resources, effectively leveraging the unique strengths of both cloud and edge servers to enhance job completion speed. The proposed architecture, comprising both Agent and Scheduler components, reduces the action space and enhances the ability to handle multiple jobs. Simulation results demonstrate that, compared to existing common algorithms, the proposed algorithm reduces the average job completion time by approximately 30%.

关键词： Cloud computing Vehicular and wireless technologies scheduling algorithms Simulation Collaboration Containers Deep reinforcement learning

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Streamlining Load scheduling in Cloud Computing: A Thorough Performance Assessment and Development of Effective Methods for Design

Streamlining Load Scheduling in Cloud Computing: A Thorough ...

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Advances in Modern Age Technologies for Health and Engineering Science (AMATHE), International Conference on

作者： Kavitha M S Ramachandra Rao G S. Karthik Department of CSE SNS college of Technology Coimbatore

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

In order to satisfy the various cloud applications' quality of service needs, load scheduling in the cloud is a challenging operation that significantly depends on the effective distribution of resources. The intrinsic variability, unpredictable nature, and dispersed nature of cloud systems are the root causes of the issues. Advanced load scheduling methods are required to maximize performance and resource usage because traditional resource allocation mechanisms frequently fail to solve these problems. A variety of approaches, each tailored to address a particular facet of the cloud's resource allocation dilemma, are presented in the literature on load scheduling algorithms. Researchers and practitioners still have a great deal of difficulty when deciding which load scheduling approach is best suited for a given workload. The intrinsic variability of cloud environments' resources is one of the key variables impacting how effective load scheduling algorithms are. A range of resources with unique features and capabilities are included in cloud infrastructures. Network setups, storage choices, and various virtual machine kinds are a few examples. Because of this, load scheduling algorithms have to negotiate this complex environment to distribute resources as efficiently as possible, taking into account variables like processing speed, memory capacity, and network bandwidth. Another issue in cloud settings is the unpredictable nature of workloads. Depending on user activity, application requirements, and outside variables, resource consumption may vary suddenly. For resources to be distributed effectively to meet shifting needs, load scheduling algorithms must be flexible and sensitive to these variations. Its flexibility is essential to sustaining peak performance and avoiding wasteful or excessive use of resources. Another level of complexity to cloud load scheduling is the distribution of resources among geographically dispersed data centers. To improve redundancy, l

关键词： Cloud computing Data centers scheduling algorithms Heuristic algorithms Throughput Virtual machining Complexity theory

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scheduling with Probabilistic Per-Packet Real-Time Guarantee for Industrial URLLC

Scheduling with Probabilistic Per-Packet Real-Time Guarantee...

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Industrial Cyber-Physical Systems (ICPS)

作者： Zhibo Meng Hongwei Zhang James Gross Iowa State University U.S.A. KTH Royal Institute of Technology Sweden

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

For ultra-reliable, low-latency communications (URLLC) applications in industrial wireless networks such as mission-critical industrial control, it is important to ensure the communication quality of individual packets. Prior studies have considered Probabilistic Per-packet Real-time Communications (PPRC) guarantees for single-cell, single-channel networks but they have not considered real-world complexities such as inter-cell interference in large-scale networks with multiple communication channels and heterogeneous real-time requirements. To fill the gap, we propose a real-time scheduling algorithm based on local-deadline-partition (LDP), and the LDP algorithm ensures PPRC guarantee for large-scale, multi-channel networks with heterogeneous real-time constraints. We numerically study the properties of the LDP algorithm and observe that it significantly improves the network capacity of URLLC, for instance, by a factor of 5-20 as compared with a typical method. Furthermore, the PPRC traffic supportable by the LDP algorithm is significantly higher than that of state-of-the-art comparison schemes. This demonstrates the potential of fine-grained scheduling algorithms for URLLC wireless systems regarding interference scenarios.

关键词： Job shop scheduling scheduling algorithms Wireless networks Industrial control Mission critical systems Interference Ultra reliable low latency communication

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Hybrid Time-Triggered and Event-Triggered Flow scheduling for Time-Sensitive Networking (TSN) 10

Hybrid Time-Triggered and Event-Triggered Flow Scheduling fo...

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10th International Conference on Computer and Communications, ICCC 2024

作者： Xu, Yiming Kang, Kaixuan Tan, Qianyi Cao, Suzhi Liu, Peng University of Chinese Academy of Sciences Beijing 100094 China Key Laboratory of Space Utilization Chinese Academy of Sciences Beijing 100094 China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing 100094 China

Time-sensitive Networking (TSN) is an emerging technology that aims to solve the problem of precise network latency control in next generation industrial networks. In addition to conventional best-effort flows, TSN needs to deliver time critical flows, which are of high-priority. To ensure deterministic latency for time-critical flows, various scheduling models have been developed. However, those models are primarily designed for time-triggered (TT) critical flows, which are predictable and periodic. In realistic industrial scenarios, often there exist event-triggered (ET) critical flows, which are bursty and may have higher priority than time-triggered flows. In this paper, we design an enhanced TACQ model to meet the requirements of managing event-triggered flows, without affecting the deterministic transmission of time-triggered flows. On top of this model, we propose a corresponding event-triggered flows scheduling algorithm. Furthermore, to reduce the computation time of time-triggered flows scheduling, we propose a weighted sorting algorithm based on path optimization (WSPO). Simulations are conducted to evaluate the performance of our model and algorithms. Compared to traditional models and algorithms, the proposed methods can better handle hybrid critical flows. © 2024 IEEE.

关键词： scheduling algorithms

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Task Offloading and scheduling in Osmotic Computing-Based Health Monitoring Systems

Task Offloading and Scheduling in Osmotic Computing-Based He...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Benazir Neha Sanjaya Kumar Panda Pradip Kumar Sahu Department of IT VSSUT Burla Burla Odisha India Department of CSE NIT Warangal Warangal Telangana India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The advent of osmotic computing has brought significant advancements in health monitoring systems (HMSs). Osmotic computing explores and leverages the synergy between the Internet of Things (IoT) and edge tiers, edge and cloud tiers, for dynamic and adaptive management of tasks and resources. In this paper, we introduce task offloading and scheduling algorithms (i.e., emergency level-based task offloading (ELTO) and osmotic task scheduling (OTS) algorithms) within an osmotic computing framework aimed at reducing latency, optimizing resource utilization, and enhancing the scalability of HMSs. Our proposed task offloading algorithm, ELTO, ascertains the dynamic movement of tasks to either the edge tier or cloud tier from the IoT tier, assuring prompt processing of critical healthcare tasks, such as real-time monitoring of vital signs, data analysis and emergency response. On the other hand, our OTS algorithm is used to utilize the edge tier resources efficiently. Through rigorous simulations, we illustrate the effectiveness of our algorithms in enhancing system responsiveness and reliability compared to baseline algorithms.

关键词： Cloud computing scheduling algorithms Heuristic algorithms Scalability Medical services Real-time systems Computational efficiency Resource management Internet of Things Monitoring

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From Entanglement Purification scheduling to Fidelity-Constrained Entanglement Routing

From Entanglement Purification Scheduling to Fidelity-Constr...

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International Conference on Network Protocols

作者： Ziyue Jia Lin Chen School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Provincial Key Laboratory of Information Security Technology Guangzhou China

ISBN: (数字)9798350351712

ISBN: (纸本)9798350351729

Recently emerged as a disruptive networking paradigm, quantum networks rely on the mysterious quantum entanglement to teleport qubits without physically transferring quantum particles. However, the state of quantum systems is extremely fragile due to environment noise. A promising technique to combat against quantum decoherence is entanglement purification. To fully exploit its benefit, two fundamental research questions need to be answered: (1) given an entanglement path, what is the optimal entanglement purification schedule? (2) how to compute min-cost end-to-end entanglement paths subject to fidelity constraint? In this paper, we give algorithmic solutions to both questions. For the first question, we develop an optimal entanglement purification scheduling algorithm for the singlehop case and analyze the PURIFY-AND-SWAP strategy in the multi-hop case by establishing the closed-form condition for its optimality. For the second question, we design a polynomialtime algorithm constructing an $\epsilon$ -optimal fidelity-constrained path. The effectiveness of our algorithms are also numerically demonstrated by extensive simulations.

关键词： Schedules Quantum system Protocols Purification Quantum entanglement scheduling algorithms Qubit Routing Quantum decoherence Quantum networks

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Research on Single Bottleneck Optimization Based on Intelligent Manufacturing Mode

Research on Single Bottleneck Optimization Based on Intellig...

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2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023

作者： Hu, Han Cao, Jun Hui, Guan Wuhan Vocational College of Software and Engineering Wuhan China Huazhong University of Science and Technology State Key Lab of Digital Manufacturing Equipment and Technology Hust-Sany Joint Lab of Advanced Manufacturing School of Mechanical Science and Engineering Wuhan China Wuhan Railway Vocation College of Technology Wuhan China Northwest A&F University College of Languages and Culture Xianyang China

ISBN: (纸本)9798350399028

More and more manufacturing companies are adopting a multi-variety, low-volume production model, and there are bottlenecks in the workshop due to the different demands on machine capacity for different products. The presence of the bottleneck in the workshop will severely limit the daily output of the workshop, reducing productivity and profits. In this paper, an improved Jaya algorithm based on problem characteristics is proposed to solve the single bottleneck optimization problem within intelligent manufacturing mode. Firstly, under the single bottleneck of intelligent manufacturing mode, the flexible factor of the manufacturing machine is considered, which effectively solves the problem of machine load distribution in the workshop. Secondly, based on the basic JAYA algorithm, a two-layer encoding mechanism and decoding mechanism based on problem characteristics are proposed, as well as the improvement of the similarity method. Finally, the effectiveness of the improved algorithm in this problem is demonstrated by comparing it with other algorithms. © 2023 IEEE.

关键词： scheduling algorithms

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Research on Engineering Project Schedule Optimization Method Based on HRRN

Research on Engineering Project Schedule Optimization Method...

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2023 International Conference on Electronics and Devices, Computational Science, ICEDCS 2023

作者： Zhou, Rongkun University of Minnesota Twin Cities College of Science & Engineering MinneapolisMN55455 United States

ISBN: (纸本)9798350343038

Engineering project schedule optimization is an important means to improve engineering efficiency and quality, but it is also faced with a variety of constraints and uncertainties. This paper proposes a project schedule optimization method based on an HRRN to solve this problem. First, according to the characteristics and requirements of engineering projects, a multi-objective mixed integer programming model is established, and the optimal scheduling sequence and resource allocation scheme of projects are obtained. Secondly, a risk assessment and adjustment strategy based on Monte Carlo simulation is proposed to eliminate the uncertainties in the engineering project schedule. Thirdly, according to the dynamic priority property of the HRRN, a response ratio calculation model that comprehensively considers the influence of urgency and importance of engineering projects is constructed, which describes the priority of projects more precisely. Finally, an engineering project schedule optimization system is built using an HRRN. Simulation and experimental verification prove the method proposed in this paper's effectiveness and superiority. © 2023 IEEE.

关键词： scheduling algorithms

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AoI Minimization for Multi-user Networks with Delayed Feedback

AoI Minimization for Multi-user Networks with Delayed Feedba...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Lu, Yuxiao Xu, Xiaoli Huang, Xinmei Southeast University School of Information Science and Engineering Nanjing China Jinling Institute of Technology Department of Mathematics Nanjing China

ISBN: (纸本)9798350345384

This paper considers the packet scheduling for minimizing the age of information (AoI) in multi-user networks under delayed feedback, and investigates the impact of feedback delay on the AoI performance. With delayed feedback, the transmitter is not aware of the real-time receiving status at the moment of making the scheduling decisions. Hence, this problem is modelled as a partially-observable Markov decision process (POMDP), which includes a belief vector describing the probability distribution of the receiving status for all the users. The belief vector is updated based on the delayed feedback and the historical actions. Solving the POMDP optimally is rather challenging due to the large state space. We further propose a low-complexity policy, which selects the action that maximizes the expected immediate reward at each time slot. Numerical results show that the proposed policy significantly outperforms the stationary random policy. By comparing with the scheduling algorithm under instantaneous feedback, we show that the performance degradation caused by feedback delay increases with the packet arrival rate, channel erasure probability and the number of users. © 2023 IEEE.

关键词： scheduling algorithms

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Deterministic Asynchronous scheduling with Probabilistic Reliability Guarantee in Industrial Wireless Networks

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IEEE NETWORK 2021年第6期35卷 263-269页

作者： Qiu, Ying Ke, Jie Liang, Chao Jia, Yubo Xu, Weiqiang Chen, Hsiao-Hwa Zhejiang Sci Tech Univ Hangzhou Peoples R China Natl Cheng Kung Univ Taipei Taiwan

Industrial Wireless Networks (IWNs) play a critical role in industry 4.0 applications. However, industrial control processes require deterministic data delivery with an extremely high reliability, which is challenging in harsh IWN environments. Existing scheduling schemes rely mainly on accurate global synchronization to ensure deterministic transmission, which incurs additional hardware cost and a large communication overhead. To eliminate the synchronization requirements, we propose an asynchronous scheduling model that supports arbitrary time offset between any node pairs. As finding a solution with a given reliability guarantee in this model is a NP-hard problem, we design a probabilistic algorithm based on the Monte Carlo tree search (MCTS) method to generate and verify feasible schedules. The simulation results show that E-MCTS is significantly better in transmission reliability if compared to the classic Monte Carlo tree search algorithm.

关键词： Reliability scheduling Job shop scheduling Schedules Probabilistic logic Synchronization scheduling algorithms

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