Yunfeng Duan , Jingchun Li , Hao Sun , Fanqin Zhou , Jiaxing Chen , Tiandong Wu , Wenjing Li , Yuxing Fan
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引用次数: 0
Abstract
As demand for computing power and low latency in intelligence applications grows, the efficient management and coordination of resources in computing power networks become crucial. This paper presents a telemetry-aided multi-agent cooperation framework for DAG task scheduling in computing power networks. Utilizing distributed agents with network telemetry, the framework accurately assesses local network state information, formulates scheduling policies, and assigns tasks to edge servers. An online learning algorithm for DAG task scheduling is also introduced to enhance the cooperation strategy in decision-making, enabling rapid task scheduling and resource allocation decisions. Simulation results demonstrate a minimum 13.5% reduction in total task execution time compared to sub-optimal methods, along with improved node and link load balancing.
随着智能应用对计算能力和低延迟的需求日益增长,计算能力网络中资源的高效管理和协调变得至关重要。本文提出了一种遥测辅助的多代理合作框架,用于计算能力网络中的 DAG 任务调度。该框架利用具有网络遥测功能的分布式代理,准确评估本地网络状态信息,制定调度策略,并将任务分配给边缘服务器。该框架还引入了 DAG 任务调度的在线学习算法,以加强决策中的合作策略,从而实现快速的任务调度和资源分配决策。仿真结果表明,与次优方法相比,总任务执行时间至少缩短了 13.5%,节点和链路负载平衡也得到了改善。
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
• methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.;
• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.