期刊论文详细信息
Applied Sciences
Network Calculus-Based Latency for Time-Triggered Traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN)
Aduwati Sali1  Fazirulhisyam Hashim1  Khaled M. Shalghum1  Nor Kamariah Noordin1 
[1] Department of Computer and Communication Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia;
关键词: mixed-criticality real-time systems;    time-sensitive network (TSN);    scheduling algorithm;    worst-case latency performance;    network calculus;   
DOI  :  10.3390/app11093896
来源: DOAJ
【 摘 要 】

Deterministic latency is an urgent demand to pursue the continuous increase in intelligence in several real-time applications, such as connected vehicles and automation industries. A time-sensitive network (TSN) is a new framework introduced to serve these applications. Several functions are defined in the TSN standard to support time-triggered (TT) requirements, such as IEEE 802.1Qbv and IEEE 802.1Qbu for traffic scheduling and preemption mechanisms, respectively. However, implementing strict timing constraints to support scheduled traffic can miss the needs of unscheduled real-time flows. Accordingly, more relaxed scheduling algorithms are required. In this paper, we introduce the flexible window-overlapping scheduling (FWOS) algorithm that optimizes the overlapping among TT windows by three different metrics: the priority of overlapping, the position of overlapping, and the overlapping ratio (OR). An analytical model for the worst-case end-to-end delay (WCD) is derived using the network calculus (NC) approach considering the relative relationships between window offsets for consecutive nodes and evaluated under a realistic vehicle use case. While guaranteeing latency deadline for TT traffic, the FWOS algorithm defines the maximum allowable OR that maximizes the bandwidth available for unscheduled transmission. Even under a non-overlapping scenario, less pessimistic latency bounds have been obtained using FWOS than the latest related works.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:0次