Yuangyai, Chumpol
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Preferred name
Yuangyai, Chumpol
Alternative Name
Yuangyai, Čhumpol
Yuangyai, C.
Main Affiliation
Email
chumpol.yu@kmitl.ac.th
2 results
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Item type:Publication, Epidemic Algorithms on Distributed Systems Towards Industry 4.0(2018-08-21); ; In today changing world, with the advent of technology and a challenging competition, reliable information methodologies and tools are required to collaborate big data and various components in both vertical and horizontal integrations over the value chain. Cyber-Physical System or CPS is one of available technologies serving industries' needs and desires. However, its important properties are required to be investigated to fully understand its characteristics and performance. This study present an epidemic-based communication and the results show that the base station could obtain the higher accuracy of the information while the method was adopted. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Epidemic System Conversion on Industry 4.0's Perspective under Dynamic Network Condition(2019-09-25); ; In large-scale manufacturing operations with increasing global competition, success depends on a reliable network system to complete a value chain transformation. The use of the Industry 4.0 paradigm is increasingly evolving in many areas of different industries to ensure significant increases in factory productivity, flexibility, and efficiency. Consequently, the system transformation requires a shift from single automated node to a fully integrated system. However, selected methodology and results require study to fully understand the digital transformation as well as its characteristics. This investigation presents a system conversion study, between centralized and decentralized systems, using the concept of epidemic membership protocols in the context of Industry 4.0. This paper proposes the method based on membership protocols focusing on the system conversion methodology under dynamic network condition. The experimental results show that the proposed method provides an ability to rewrite the structure of the network topology with optimal accuracy of epidemic application.