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author:

Lei, N. (Lei, N..) [1] | Huang, L. (Huang, L..) [2] | Fang, H. (Fang, H..) [3] | Chen, C.-H. (Chen, C.-H..) [4]

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EI Scopus

Abstract:

Internet of Things (IoT) has significantly changed our lives and the development of technology. Different types of smart terminal devices are connected to the Internet to achieve communications with each other. To establish the connections, communication protocols among different devices should be unified. Message Queue Teleme-try Transport (MQTT) as a protocol based on publisher/subscriber and broker requires a small amount of bandwidth and guarantees the message passing process by providing different Quality of Services (QoS) levels. The message loss for the subscriber still ex-ists during the downtime of the broker, which greatly affects service qualities. Currently, the message loss of MQTT is mainly collected by practical experiments which costs ex-tra resources. Therefore, this paper proposed a statistical-based message loss estimation approach to analyze the message loss for the subscriber when MQTT supports different QoS levels. The proposed method can estimate the message loss directly from the derived formula. Numerical analysis is adopted to prove the availability of the message loss estimation formulas. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

Keyword:

IoT Message Loss Estimation MQTT Probability Model QoS

Community:

  • [ 1 ] [Lei N.]College of Science and Technology, Fujian Open University, Fujian, Fuzhou, China
  • [ 2 ] [Huang L.]College of Science and Technology, Fujian Open University, Fujian, Fuzhou, China
  • [ 3 ] [Fang H.]College of Computer and Data Science, Fuzhou University, Fujian, Fuzhou, China
  • [ 4 ] [Chen C.-H.]College of Computer and Data Science, Fuzhou University, Fujian, Fuzhou, China

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Source :

Journal of Network Intelligence

ISSN: 2414-8105

Year: 2023

Issue: 2

Volume: 8

Page: 586-594

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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