Related papers: A Survey of Scheduling Algorithms for the Time-Awa…

Connected cars are susceptible to cyberattacks. Security and safety of future vehicles highly depend on a holistic protection of automotive components, of which the time-sensitive backbone network takes a significant role. These onboard…

Spiking Neural Networks (SNNs) have attracted significant attention from researchers across various domains due to their brain-like information processing mechanism. However, SNNs typically grapple with challenges such as extended time…

Time-Sensitive Networking (TSN) and Deterministic Networking (DetNet) are emerging standards to enable deterministic, delay-critical communication in such networks. This naturally (re-)calls attention to the network calculus theory (NC),…

The emerging paradigm of resource disaggregation enables the deployment of cloud-like services across a pool of physical and virtualized resources, interconnected using a network fabric. This design embodies several benefits in terms of…

Traffic flow forecasting is a fundamental research issue for transportation planning and management, which serves as a canonical and typical example of spatial-temporal predictions. In recent years, Graph Neural Networks (GNNs) and…

The IEEE 802.1 time-sensitive networking (TSN) standards aim at improving the real-time capabilities of standard Ethernet. TSN is widely recognized as the long-term replacement of proprietary technologies for industrial control systems.…

Minimizing transmission delay in wireless multi-hop networks is a fundamental yet challenging task due to the complex coupling among interference, queue dynamics, and distributed control. Traditional scheduling algorithms, such as…

Flow reshaping is used in time-sensitive networks (as in the context of IEEE TSN and IETF Detnet) in order to reduce burstiness inside the network and to support the computation of guaranteed latency bounds. This is performed using per-flow…

This paper has been withdrawn by arXiv. arXiv admin note: author list truncated due to disputed authorship and content. This submission repeats large portions of text from this http URL by other authors. Duty cycle mode in WSN improves…

The traditional industrial communication networks may not meet the requirements of the main smart factory applications together, such as Remote control and safety applications (which considered as strict real time applications) and…

Deploying deep neural network (DNN) accelerators with Layer Temporal Scheduling (LTS) often incurs significant overheads (e.g., energy and latency), as intermediate activations must be cached in DRAM. To alleviate this, Tile Spatial…

Network calculus (NC), particularly its min-plus branch, has been extensively utilized to construct service models and compute delay bounds for time-sensitive networks (TSNs). This paper provides a revisit to the fundamental results. In…

As required by Industry 4.0, companies will move towards flexible and individual manufacturing. To succeed in this transition, convergence of 5G and time-sensitive networks (TSN) is the most promising technology and has thus attracted…

While technologies such as Time-Sensitive Networking (TSN) improve deterministic behaviour, real-time functionality, and robustness of Ethernet, future industrial networks aim to be increasingly wireless. While wireless networks facilitate…

Spiking neural networks (SNNs), inspired by the spiking behavior of biological neurons, provide a unique pathway for capturing the intricacies of temporal data. However, applying SNNs to time-series forecasting is challenging due to…

Mission-critical systems (MCSs) have embraced new design paradigms such as service-oriented architecture (SOA) and IEEE 802.1 Time-sensitive Networking (TSN). These approaches tackle the static and closed-loop design and configuration of…

Networked control systems (NCS) have attracted considerable attention in recent years. While the stabilizability and optimal control of NCS for a given communication system has already been studied extensively, the design of the…

The biological neurons use precise spike times, in addition to the spike firing rate, to communicate with each other. The time-to-first-spike (TTFS) coding is inspired by such biological observation. However, there is a lack of effective…

IEEE 802.1 Time-sensitive Networking~(TSN) standards are envisioned to replace legacy network protocols in critical domains to ensure reliable and deterministic communication over off-the-shelf Ethernet equipment. However, they lack…

Multivariate time-series (MTS) forecasting is a paramount and fundamental problem in many real-world applications. The core issue in MTS forecasting is how to effectively model complex spatial-temporal patterns. In this paper, we develop a…