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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yi Yang Guangyong Shang Guangpeng Qi Zhen Ma Yaxiong Liu Jiazhou Tian Aocheng Duan Meng Zhang Jingying Li Xuan Ding School of Software Tsinghua University Beijing China Inspur Yunzhou Industrial Internet Co. Ltd Jinan Shandong China School of Cyber Engineering Xidian University Xi’an Shaanxi China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Blockchain technology inherently necessitates redundant computation to achieve consensus among untrusted parties because of its fundamental threat model. This requirement, however, compromises system performance and impedes the widespread adoption of blockchain. To leverage existing physical resources, current research on high-performance consortium blockchain algorithms and architectures frequently employs cluster-node architectures to expand the parallel processing capability of traditional single physical nodes. Our investigation reveals a significant trend as the parallel capability of individual nodes improves. The idle time caused by synchronization of all transactions within each block, previously considered negligible, has become increasingly significant. To address this, we present BachLedger, which implements Seamless scheduling to fully utilize inter-block thread idle time, thereby augmenting system resource utilization and achieving overall performance improvements. Our experimental results demonstrate that our algorithm surpasses current state-of-the-art (SOTA) performance levels in high-performance consortium blockchains and effectively resolves the aforementioned synchronization issue. Furthermore, this scheduling algorithm offers enhanced scalability for BachLedger, positioning it as a promising solution for future blockchain implementations.

关键词： Threat modeling scheduling algorithms System performance Scalability Computer architecture Parallel processing Dynamic scheduling Blockchains Synchronization Resource management

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Instance Configuration for Sustainable Job Shop scheduling

arXiv

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arXiv 2024年

作者： Pérez, Christian March, Carlos Salido, Miguel Universitat Politècnica de València Instituto de Automática e Informática Industrial Camì de Vera S/N Valencia Spain Universitat Politècnica de València valgrAI - Valencian Graduate School and Research Network of Artificial Intelligence Camì de Vera S/N Valencia Spain

The Job Shop scheduling Problem (JSP) is a pivotal challenge in operations research and is essential for evaluating the effectiveness and performance of scheduling algorithms. scheduling problems are a crucial domain in combinatorial optimization, where resources (machines) are allocated to job tasks to minimize the completion time (makespan) alongside other objectives like energy consumption. This research delves into the intricacies of JSP, focusing on optimizing performance metrics and minimizing energy consumption while considering various constraints such as deadlines and release dates. Recognizing the multi-dimensional nature of benchmarking in JSP, this study underscores the significance of reference libraries and datasets like JSPLIB in enriching algorithm evaluation. The research highlights the importance of problem instance characteristics, including job and machine numbers, processing times, and machine availability, emphasizing the complexities introduced by energy consumption considerations. An innovative instance configurator is proposed, equipped with parameters such as the number of jobs, machines, tasks, and speeds, alongside distributions for processing times and energy consumption. The generated instances encompass various configurations, reflecting real-world scenarios and operational constraints. These instances facilitate comprehensive benchmarking and evaluation of scheduling algorithms, particularly in contexts of energy efficiency. A comprehensive set of 500 test instances has been generated and made publicly available, promoting further research and benchmarking in JSP. These instances enable robust analyses and foster collaboration in developing advanced, energy-efficient scheduling solutions by providing diverse *** Codes 68W99 © 2024, CC BY-NC-ND.

关键词： scheduling algorithms

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TS-EoH: An Edge Server Task scheduling Algorithm Based on Evolution of Heuristic

arXiv

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arXiv 2024年

作者： Wang, Yatong Pei, Yuchen Zhao, Yuqi School of Computer Science Central China Normal University Wuhan China

With the widespread adoption of 5G and Internet of Things (IoT) technologies, the low latency provided by edge computing has great importance for real-time processing. However, managing numerous simultaneous service requests poses a significant challenge to maintaining low latency. Current edge server task scheduling methods often fail to balance multiple optimization goals effectively. This paper introduces a novel task-scheduling approach based on Evolutionary Computing (EC) theory and heuristic algorithms. We model service requests as task sequences and evaluate various scheduling schemes during each evolutionary process using Large Language Models (LLMs) services. Experimental results show that our task-scheduling algorithm outperforms existing heuristic and traditional reinforcement learning methods. Additionally, we investigate the effects of different heuristic strategies and compare the evolutionary outcomes across various LLM services. © 2024, CC BY.

关键词： scheduling algorithms

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A Window-Based Heuristic TSN scheduling Algorithm Using Array Theory Encoding

A Window-Based Heuristic TSN Scheduling Algorithm Using Arra...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Zhaochuan Sang Yinshan Wang Hongchao Zhang School of Automobile and Transportation Tianjin University of Technology and Education Tianjin China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

The Time Sensitive Network (TSN) based on Ethernet extends standard Ethernet into a deterministic network with real-time functionality through a series of sub standards. This paper designs a mathematical model using array theory, which transforms the gate control mechanism into an array of window opening and closing events while retaining the original model, making it applicable to the general situation of TSN networks (multiple frames per stream, multicast streams). In addition, based on the preprocessing algorithm proposed in this paper for synthesizing link sequences, a multi-objective heuristic optimization offline scheduling algorithm based on SMT was designed to schedule each link with the shortest GCL length and the smallest number of occupied queues. This algorithm has the ability to solve in polynomial time and reserves more time and space resources for the network. The performance evaluation using the Z3 solver shows that the optimized algorithm has significantly improved performance compared to the original algorithm.

关键词： Performance evaluation Schedules Multicast algorithms scheduling algorithms Ethernet Transforms Mathematical models scheduling Real-time systems Standards

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Synergy: Collaborating Centralized and Local scheduling for Serverless Functions

Synergy: Collaborating Centralized and Local Scheduling for ...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Hanmei Chen Laiping Zhao Yanan Yang Jianing You Keqiu Li Tianjin Key Lab. of Advanced Networking Tianjin University Tianjin China TANKLAB Tianjin University Tianjin China China Telecom Cloud Computing Research Institute Beijing China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Serverless computing enables a new way of building and scaling cloud applications by allowing developers to write fine-grained functions. The execution duration of a cloud function is typically short, usually ranging from a few milliseconds to a few seconds. FaaS providers charge users based on the execution duration of cloud functions with a granularity of 1 millisecond. Existing mixed scheduling methods collocate functions with varying execution times, which may prolong their execution duration and lead to unfair charges for FaaS users. To address this problem, we propose a partition scheduling approach, placing functions with varying execution times on different partitions. We introduce Synergy, a solution in serverless computing that leverages a collaboration of central and local scheduling to partition functions and employs suitable scheduling algorithms for these partitions respectively. Synergy also supports the dynamic switching of scheduling algorithms for partitioned nodes to adapt to highly fluctuating loads. We evaluate Synergy using real-world, representative benchmarks. Experimental results demonstrate that, compared to state-of-the-art and conventional approaches, Synergy can reduce the average function execution duration by $63 \%$.

关键词： scheduling algorithms Heuristic algorithms Buildings Serverless computing Collaboration Optimal scheduling Switches Dynamic scheduling Distance measurement Partitioning algorithms

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Work-in-Progress: Multi-Deadline DAG scheduling Model for Autonomous Driving Systems

Work-in-Progress: Multi-Deadline DAG Scheduling Model for Au...

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Real-Time Systems Symposium (RTSS)

作者： Atsushi Yano Takuya Azumi Graduate School of Science and Engineering Saitama University Japan TIER IV Incorporated Japan

ISBN: (数字)9798331540265

ISBN: (纸本)9798331540272

Autoware is an autonomous driving system implemented on Robot Operation System (ROS) 2, where an end-to-end timing guarantee is crucial to ensure safety. However, existing ROS 2 cause-effect chain models for analyzing end-toend latency struggle to accurately represent the complexities of Autoware, particularly regarding sync callbacks, queue consumption patterns, and feedback loops. To address these problems, we propose a new scheduling model that decomposes the end-to-end timing constraints of Autoware into local relative deadlines for each sub-DAG. This multi-deadline DAG scheduling model avoids the need for complex analysis of data flows through queues and loops, while ensuring that all callbacks receive data within correct intervals. Furthermore, we extend the Global Earliest Deadline First (GEDF) algorithm for the proposed model and evaluate its effectiveness using a synthetic workload derived from Autoware.

关键词： Analytical models scheduling algorithms Real-time systems Data models Complexity theory Safety Synchronization Queueing analysis Autonomous vehicles Robots

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Sparse Actuator scheduling for Discrete-Time Linear Dynamical Systems

Sparse Actuator Scheduling for Discrete-Time Linear Dynamica...

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Indian Control Conference (ICC)

作者： Krishna Praveen V. S. Kondapi Chandrasekhar Sriram Geethu Joseph Chandra R. Murthy Dept. of ECE Indian Institute of Science (IISc) Bangalore India Dept. of ECE IISc Texas Instruments India Pvt. Ltd. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft CD Netherlands

ISBN: (数字)9798331517212

ISBN: (纸本)9798331517229

We consider the control of discrete-time linear dynamical systems using sparse inputs where we limit the number of active actuators at every time step. We develop an algorithm for determining a sparse actuator schedule that ensures the existence of a sparse control input sequence, following the schedule, that takes the system from any given initial state to any desired final state. Since such an actuator schedule is not unique, we look for a schedule that minimizes the energy of sparse inputs. For this, we optimize the trace of the inverse of the resulting controllability Gramian, which is an approximate measure of the average energy of the inputs. We present a greedy algorithm along with its theoretical guarantees. Finally, we empirically show that our greedy algorithm ensures the controllability of the linear system with a small number of active actuators per time step without a significant average energy expenditure compared to the fully actuated system.

关键词： Greedy algorithms Linear systems Actuators Schedules scheduling algorithms Heuristic algorithms Energy measurement Controllability Minimization Dynamical systems

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SLA based Workflow scheduling algorithm in Cloud Computing using Haris Hawks optimization

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EAI Endorsed Transactions on Scalable Information Systems 2023年第6期10卷

作者： Mangalampalli, Sudheer Karri, Ganesh Reddy Pokkuluri, Kiran Sree RajKumar, K Varada Satish, Ganti Naga School of Computer Science and Engineering VIT-AP University Amaravati India Department of Computer Science and Engineering Shri Vishnu Engineering College for Women A.P. Bhimavaram India MLRIT Hyderabad Telangana India Department of Computer Science and Engineering BVRIT HYDERABAD Telangana India

Task scheduling is crucial facet in cloud paradigm as virtual resources need to be provisioned to the variable requests coming onto cloud console from various users and more over that tasks are depends on each other which creates a workflow which is a difficult task for cloud service provider to provision these tasks over appropriate VMs. Inefficient mapping of tasks to VMs increases makespan and lead to violation of SLA between users, cloud provider. In this paper, we modeled a SLA based workflow scheduling algorithm focuses on minimization of makespan and SLA violations. This algorithm developed using Harris hawks optimization. Experimentation carried out using workflowsim. Random workload fed as input to algorithm and it is evaluated against existing baseline approaches and simulation results revealed that our proposed approach minimizes makespan and SLA violations over existing approaches by 40% and 43% respectively. © 2023 S. Mangalampalli et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

关键词： scheduling algorithms

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A Heuristic Task scheduling Algorithm for Vehicular Fog Computing

A Heuristic Task Scheduling Algorithm for Vehicular Fog Comp...

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International Conference on Internet of Things and Applications (IoT)

作者： Maryam Taghizadeh Mahmood Ahmadi Computer Engineering and Information Technology Razi University Kermanshah Iran

ISBN: (数字)9798350374674

ISBN: (纸本)9798350374681

Vehicular fog computing (VFC) is a promising solution in addressing various applications in intelligent transportation systems. Computational resources of both parking and moving vehicles can be used for computation-intensive tasks. This paper proposes a straightforward heuristic method in two forms for resource allocation and task scheduling problem in a cloud-fog environment, based on the idea of VFC. First, tasks requesting maximum resources are scheduled to static fog nodes which have more computational resources. Dynamic fog nodes are assigned to tasks while there are no available static fog nodes. Static fog nodes refers to stationary servers, while and dynamic fog nodes refer to parked or moving vehicles, respectively. Moreover, static fog nodes show greater priority in comparison to dynamic fog nodes. This method is evaluated by stochastic data and measures makespan, cost, and wait time. Experimental results show the achievement of the proposed method in reducing both makespan and wait time.

关键词： Smart cities scheduling algorithms Metaheuristics Time measurement scheduling Resource management Servers

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Low Energy scheduling of Hybrid Mine Trucks with Application of Wireless Power Transfer

Low Energy Scheduling of Hybrid Mine Trucks with Application...

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Signal Processing and Intelligent Computing (SPIC), International Conference on

作者： Lincong Zhang Hui Wang Yongjun Li Shenyang Ligong University Shenyang China Anyang No.63 Junior Middle School Anyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

Aiming at the problem of energy consumption in open pit mine truck transport, this paper takes hybrid mine trucks as the research object and realizes the wireless charging of hybrid mine trucks by setting up wireless power transfer charging piles. To minimize transport cost and energy consumption, the transport road conditions and production tasks between each loading point and unloading point are considered comprehensively, and the characteristics of energy recovery of hybrid mine trucks are taken into account in the design of the scheduling algorithm so that the low-energy scheduling model of hybrid mine trucks is established and solved. The final results show that the study can effectively reduce the transport cost and energy consumption and the operating cost of mining enterprises.

关键词： Energy consumption Costs scheduling algorithms Roads Wireless power transfer Production Signal processing Hybrid power systems scheduling Matlab

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