Chang Liu

ORCID: 0000-0002-6166-421X
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About
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Research Areas
  • Network Time Synchronization Technologies
  • Smart Grid Security and Resilience
  • Real-Time Systems Scheduling
  • Traffic Prediction and Management Techniques
  • Network Traffic and Congestion Control
  • Advanced Optical Network Technologies
  • Caching and Content Delivery
  • Energy Load and Power Forecasting
  • Context-Aware Activity Recognition Systems
  • Stock Market Forecasting Methods
  • Advanced Photonic Communication Systems
  • Technology and Security Systems
  • IoT and Edge/Fog Computing
  • Software-Defined Networks and 5G

Ningbo Product Quality Supervision and Inspection Institute
2023

ABSTRACT Although many studies have conducted the traffic scheduling of time‐sensitive networks, most focus on small‐scale static for specific scenarios, which cannot cope with dynamic and rapid time‐triggered (TT) flows generated in scalable scenarios Industrial Internet Things. In this paper, we propose a Scalable TT flow method based Dynamic Online Grouping industrial networks (SDOG). To achieve that, establish an undirected weighted graph conflict index between divide available time into...

10.1002/nem.70001 article EN International Journal of Network Management 2025-01-30

To solve the problem of jitter and low network throughput caused by impact background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for flows, named hierarchical crossover mechanism based time-aware shaper (HC-TAS) improving traditional counterpart. Then, model, we designed an inbound algorithm frame length matching outbound queue status, making sure that smaller data frames will not be blocked large frames. This greatly improves utilization...

10.1155/2024/8882006 article EN Wireless Communications and Mobile Computing 2024-04-15

With the development of power internet things (IOT), load forecasting will play an important role system. It can optimize generation planning and improve economical operation IOT. In this paper, a new loading algorithm for IOT is proposed using training data dimension expansion ensemble learning. offline phase, obtained meteorological time information normalized to remove unit effect at first. Then, Hampel filter used cope with outliers from sensors. Through preprocessing, fingerprint...

10.1155/2022/6730677 article EN cc-by Journal of Sensors 2022-06-20

Power Internet of things (IoT) is deemed as a promising network platform with widely deployed infrastructure to boost efficient information delivery in the power grid. Due long history mature grid and increased requirements from various industries, architecture IoT should be carefully investigated. Specifically, large number end devices are required simultaneously report their sensed management side. However, there few works related uniform communication mechanism support made by different...

10.1155/2022/1260923 article EN Mobile Information Systems 2022-08-08

As a key data in electric power communication network, link importance is very important for network optimization, security and maintenance of network. In this paper, model with master standby routing services based on SDN architecture constructed, evaluation algorithm under proposed. A method dividing links into three layers proposed to evaluate the quantitatively. Compared traditional analysis method, simulation results show that has significant effect importance.

10.1109/jcice59059.2023.00032 article EN 2023-05-01
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