Adaptive Internet Integration of Field Bus Systems

Eberle, Stephan

doi:10.1109/tii.2006.890525

Cited by 26 publications

(7 citation statements)

References 12 publications

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“…We expect to see that industry applications are increasingly integrated with services running on large numbers of networked, resource-limited mobile and smart embedded devices using SOA approaches. On the other hand, techniques such as embedded Web servers [51], gateway implementation and XML [52][53] and TCP/IP -based protocol application programming [51][52] will continue to be used to exchange data with large number of heterogeneous Networked Control Systems (NCS) and commercial Programmable Logic Controllers (PLC) deployed in the industry over the years. A main reason is that SOA has not been adopted yet in these NCS and PLCs and thus cannot be considered as a feasible solution for integration with already deployed control systems [51].…”

Section: A Trendsmentioning

confidence: 99%

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Integration of Distributed Enterprise Applications: A Survey

2014

IEEE Trans. Ind. Inf.

255

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Section: A Trendsmentioning

confidence: 99%

“…2) Many industrial enterprises have distributed real-time control systems (DRCS) which communicate with sensors and actuators over a communication network [53]. Generally, DRCS needs more reliability, robustness and efficiency than data-centric applications.…”

Section: A Trendsmentioning

confidence: 99%

Integration of Distributed Enterprise Applications: A Survey

2014

IEEE Trans. Ind. Inf.

255

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“…• Application layer: this layer is responsible for carrying commands from applications to the end-device actuators • Perception layer: this layer is responsible for collecting information and identifying objects and includes some key technologies such as RFID, sensors, nanotechnology, and barcodes. Recently, there is a five-layer architecture that has been introduced in [7,8] by adding two layers as in Figure 3:…”

Section: Basics and Backgroundmentioning

confidence: 99%

Internet Intelligent Services of Vehicles Based on the Internet of Things and Multiagent Systems

Darwish

Turcu

2018

Journal of the Egyptian Mathematical Society

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The facilities offered by the distributed computing systems such as Internet of Things (IoT), multi-agent systems (MASs) and vehicular networks can be used to integrate such paradigms to provide several services of Internet of Vehicles (IoV). The core objective of this paper is to present the integration of Multi-agent Systems (MASs) with IoT and IoV as a new model in Cypher Physical System (CPS) of smart vehicles application. MASs are more effective when we employ them with distributed computing infrastructures as with IoV to achieve more high performance. On the other hand, there is a lack of research works and a few papers in the literature till today with the integration of such paradigms, MAS, IoT, and IoV. The features of the proposed integration are based on the main characteristics of intelligent agents like intelligence, flexibility, proactivity and reactivity, and autonomy which can be employed in IoV paradigm to provide new solutions and intelligent services that will explore new advances and different facilities in transportation problems. Also, IoT provides an adequate environment for communication with MASs paradigms and applications as it provides reliable, flexible, effective, and smart services to vehicular networks. Moreover, integrating MASs with IoT and IoV could provide flexible, autonomous, and intelligent services of IoV. Some limitations and challenges of the proposed integration method in this paper are presented with some future research trends.

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“…In the Internet of Things (IoT) age, many fieldbuses such as building facility control networks are often integrated with IP networks using gateways . These fieldbuses often employ of a random‐access‐type protocol with the bit rate of a few tens of kbps .…”

Section: Introductionmentioning

confidence: 99%

Analysis on burst packet buffering of communication gateway between fast IP network and slow facility fieldbus

Yamada

Ninagawa

2016

IEEJ Transactions Elec Engng

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In the Internet of Things (IoT) age, fieldbuses for distributed embedded systems are often integrated with IP networks with gateways. Because of the vast difference in bit rates between both networks, buffering characteristics of these gateways are becoming important. In this paper, we modeled a fieldbus gateway using an M/M/1 queuing system for the transient packet buffering. Assuming burst packet arrivals at the gateway, time trends of the expected value and the standard deviation of the number of buffered packets were calculated analytically. Validity of our analysis was confirmed using computer simulation for CSMA/CD communications. Time trend curves for the expected value and the standard deviation matched within 5% and 20 %, respectively. Our transient analysis method provides a practical estimation method for the transient performance of the fieldbus gateways.

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Adaptive Internet Integration of Field Bus Systems

Cited by 26 publications

References 12 publications

Integration of Distributed Enterprise Applications: A Survey

Integration of Distributed Enterprise Applications: A Survey

Internet Intelligent Services of Vehicles Based on the Internet of Things and Multiagent Systems

Analysis on burst packet buffering of communication gateway between fast IP network and slow facility fieldbus

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