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DR-IS:Dynamic Response Incremental Scheduling in time-sensitive network

China Communications 2024年第10期21卷 28-42页

作者： Pei Jinchuan Hu Yuxiang Tian Le Li Ziyong PLA Strategic Support Force Information Engineering University Zhengzhou 450002China

time-sensitive network(TSN)with deterministic transmission capability is increasingly used in many emerging *** mainly guarantees the Quality of Service(QoS)of applications with strict requirements on time and *** of the core features of TSN is traffic scheduling with bounded low delay in the ***,traffic scheduling schemes in TSN are usually synthesized offline and lack *** implement incremental scheduling of newly arrived traffic in TSN,we propose a Dynamic Response Incremental Scheduling(DR-IS)method for time-sensitive traffic and deploy it on a software-defined time-sensitive network *** the premise of meeting the traffic scheduling requirements,we adopt two modes,traffic shift and traffic exchange,to dynamically adjust the time slot injection position of the traffic in the original scheme,and determine the sending offset time of the new timesensitive traffic to minimize the global traffic transmission *** evaluation results show that DRIS method can effectively control the large increase of traffic transmission jitter in incremental scheduling without affecting the transmission delay,thus realizing the dynamic incremental scheduling of time-sensitive traffic in TSN.

关键词： incremental scheduling time-sensitive network traffic scheduling transmission jitter

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Graph Attention Residual network Based Routing and Fault-Tolerant SchedulingMechanism for Data Flow in Power Communication network

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Computers, Materials and Continua 2024年第1期81卷 1641-1665页

作者： Lin Z. Zeng Z. Yu Y. Ren Y. Qiu X. Chen J. State Key Laboratory ofnetworking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China State Grid Jiangsu Electric Power Co. Ltd Nanjing 210008 China

For permanent faults (PF) in the power communication network (PCN), such as link interruptions, the timesensitive networking (TSN) relied on by PCN, typically employs spatial redundancy fault-tolerance methods to keep service stability and reliability, which often limits TSN scheduling performance in fault-free ideal states. So this paper proposes a graph attention residual network-based routing and fault-tolerant scheduling mechanism (GRFS) for data flow in PCN, which specifically includes a communication system architecture for integrated terminals based on a cyclic queuing and forwarding (CQF) model and fault recovery method, which reduces the impact of faults by simplified scheduling configurations of CQF and fault-tolerance of prioritizing the rerouting of faulty time-sensitive (TS) flows; considering that PF leading to changes in network topology is more appropriately solved by doing routing and time slot injection decisions hop-by-hop, and that reasonable network load can reduce the damage caused by PF and reserve resources for the rerouting of faulty TS flows, an optimization model for joint routing and scheduling is constructed with scheduling success rate as the objective, and with traffic latency and network load as constraints; to catch changes in TSN topology and traffic load, a D3QN algorithm based on a multi-head graph attention residual network (MGAR) is designed to solve the problem model, where the MGAR based encoder reconstructs theTSNstatus into feature embedding vectors, and a dueling network decoder performs decoding tasks on the reconstructed feature embedding vectors. Simulation results show that GRFS outperforms heuristic fault-tolerance algorithms and other benchmark schemes by approximately 10%in routing and scheduling success rate in ideal states and 5% in rerouting and rescheduling success rate in fault states. © 2024 The Authors. Published by Tech Science Press.

关键词： deep reinforcement learning fault tolerance graph attention network time-sensitive network

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