O-MI/O-DF vs. MQTT: A performance analysis

Benedick, Paul-Lou; Robert, Jérémy; Traon, Yves Le; Kubler, Sylvain

doi:10.1109/icphys.2018.8387652

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…For MQTT in [7], a comparison with CoAP on Ponte Eclipse Project implementation was provided. Also, an analysis of MQTT performance was done in [8]. ere is a formal approach to model, analyze, and verify the usage of MQTT in the case of communicating vehicles in [9].…”

Section: Related Workmentioning

confidence: 99%

Using IoT Protocols in Real-Time Systems: Protocol Analysis and Evaluation of Data Transmission Characteristics

Gavrilov

Bergaliyev

Sergey

et al. 2022

Journal of Computer Networks and Communications

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In the Internet of things, many data transfer protocols are used for various tasks. In this article, we consider the application layer protocols that are the main ones for transmitting messages in the IoT. The main problems are unpredictability, lack of stability of data transmission delays, and non-determinism, which are also important for real-time systems. The purpose of this study is to determine the most appropriate middleware and data transfer protocol for systems with high data transfer requirements, including real-time systems. Therefore, MQTT, RTPS, JMS, and AMQP protocols were analyzed in order to find out what tasks these protocols should be used for and whether they can be used in robotic and autonomous systems where high data transmission requirements are imposed. To evaluate the protocols, the standards were analyzed to determine the pros and cons, and the software implementations of each of them were selected. To assess the characteristics of data transmission, we have developed our own test scenarios that simulate complex situations. The behavior of software solutions is analyzed and a comparative analysis is made based on the obtained data. Together, the theoretical analysis of protocols and the study of software solutions allow us to conclude on the applicability of a particular protocol in real-time systems. As a result of the study, we can conclude that RTPS is the best solution for real-time systems with different traffic and MQTT performs well when transmitting short messages. But none of the protocols under consideration guarantees the determinism of data transmission, so it is better to use specialized link-layer protocols to obtain guarantees.

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Section: Related Workmentioning

confidence: 99%

Using IoT Protocols in Real-Time Systems: Protocol Analysis and Evaluation of Data Transmission Characteristics

Gavrilov

Bergaliyev

Sergey

et al. 2022

Journal of Computer Networks and Communications

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“…Within this context, two main communication patterns govern these models 2 : (a) Publish/Subscribe (Pub/Sub): asynchronous, point-tomultipoint and loosely coupled messaging model allowing messages to be broadcast to systems having subscribed to a given "topic". The most common Pub/-Sub protocols are MQTT (Message Queuing Telemetry Transport) [23], AMQP (Advanced Message Queuing Protocol) [24] and WAMP (Web Application Messaging Protocol) [25]. (b) Client/Server: synchronous, point-to-point and tightly coupled messaging model allowing clients to request a data or service item from an identified server [26].…”

Section: C3mentioning

confidence: 99%

bIoTope: Building an IoT Open Innovation Ecosystem for Smart Cities

et al. 2020

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The Internet of Things (IoT) has led towards a digital world in which everything becomes connected. Unfortunately, most of the currently marketed connected devices feed vertically-oriented closed systems (commonly referred to as vertical silos) which prevent the development of a unified global IoT. This issue is all the more valid in complex environments, such as smart cities, in which exceedingly large amounts of heterogeneous sensor data are collected, and in which platforms and stakeholders should also be able to interact and cooperate. Therefore, it is of utmost importance to move towards the creation of open IoT ecosystems to support efficient smart city service integration, discovery and composition. This paper contributes to the specifications of such an ecosystem, which has been developed as part of the EU's H2020 bIoTope project. The novelty of this ecosystem compared with the current literature is threefold: (i) it is based on the extensive use of open communication and data standards, notably O-MI and O-DF standards, that foster technical, syntactic and semantic interoperability over domains; (ii) it proposes an innovative service marketplace for data/service publication, discovery and incentivization; (iii) it integrates security functionalities at the IoT gateway level. The practicability of our ecosystem has been validated through several smart city proofs-of-concept set up in three distinct cities: Helsinki, Lyon and Brussels. Given the five major themes defined in the CITYKeys (a smart city performance indicator framework), namely People, Planet, Prosperity, Governance and Propagation, bIoTope mainly contributes to Prosperity-related metrics, as discussed in this paper.

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“…are heterogeneous, requiring middleware to access and standardise data, while providing an interface between the business and industrial worlds [ 15 ]. Such data collection infrastructure may have sparse performance, in particular in terms of network metrics such as losses, delays or traffic-load [ 16 , 17 ], resulting in data quality degradation.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Approach for Evaluating Artificial Intelligence Models in Industrial Settings

Benedick

Robert²,

Traon

2021

Sensors

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Artificial Intelligence (AI) is one of the hottest topics in our society, especially when it comes to solving data-analysis problems. Industry are conducting their digital shifts, and AI is becoming a cornerstone technology for making decisions out of the huge amount of (sensors-based) data available in the production floor. However, such technology may be disappointing when deployed in real conditions. Despite good theoretical performances and high accuracy when trained and tested in isolation, a Machine-Learning (M-L) model may provide degraded performances in real conditions. One reason may be fragility in treating properly unexpected or perturbed data. The objective of the paper is therefore to study the robustness of seven M-L and Deep-Learning (D-L) algorithms, when classifying univariate time-series under perturbations. A systematic approach is proposed for artificially injecting perturbations in the data and for evaluating the robustness of the models. This approach focuses on two perturbations that are likely to happen during data collection. Our experimental study, conducted on twenty sensors’ datasets from the public University of California Riverside (UCR) repository, shows a great disparity of the models’ robustness under data quality degradation. Those results are used to analyse whether the impact of such robustness can be predictable—thanks to decision trees—which would prevent us from testing all perturbations scenarios. Our study shows that building such a predictor is not straightforward and suggests that such a systematic approach needs to be used for evaluating AI models’ robustness.

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O-MI/O-DF vs. MQTT: A performance analysis

Cited by 4 publications

References 9 publications

Using IoT Protocols in Real-Time Systems: Protocol Analysis and Evaluation of Data Transmission Characteristics

Using IoT Protocols in Real-Time Systems: Protocol Analysis and Evaluation of Data Transmission Characteristics

bIoTope: Building an IoT Open Innovation Ecosystem for Smart Cities

A Systematic Approach for Evaluating Artificial Intelligence Models in Industrial Settings

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