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A Smart Collaborative Routing Protocol for Delay Sensitive Applications in Industrial IoT
- Source :
- IEEE Access, Vol 8, Pp 20413-20427 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- In the industrial Internet of things (IIoT), there is always a strong demand for real-time information transfer. Especially when deploying wireless/wired hybrid networks in smart factories, the requirement for low delay interaction is more prominent. Although tree routing protocols have been successfully executed in simple networks, more challenges in transmission speed can be observed in the manufacturing broadband communication system. Motivated by the progresses in deep learning, a smart collaborative routing protocol with low delay and high reliability is proposed to accommodate mixed link scenarios. First, we establish a one-hop delay model to investigate the potential affects of Media Access Control (MAC) layer parameters, which supports the subsequent design. Second, forwarding, maintenance, and efficiency strategies are created to construct the basic functionalities for our routing protocol. Relevant procedures and key approaches are highlighted as well. Third, two sub-protocols are generated and the corresponding implementation steps are described. The experimental results demonstrate that the end-to-end delay can be effectively cut down through comprehensive improvements. Even more sensor nodes and larger network scale are involved, our proposed protocol can still illustrate the advantages comparing with existing solutions within IIoT.
- Subjects :
- Routing protocol
General Computer Science
Computer science
delay
Reliability (computer networking)
02 engineering and technology
routing protocol
Network topology
tree topology
01 natural sciences
Industrial IoT
0202 electrical engineering, electronic engineering, information engineering
Wireless
General Materials Science
Protocol (object-oriented programming)
SIMPLE (military communications protocol)
business.industry
010401 analytical chemistry
General Engineering
deep learning
020206 networking & telecommunications
0104 chemical sciences
Media access control
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
lcsh:TK1-9971
Computer network
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....a579ad6c6f9be5c4839d4bfdae1f0c89