A Fair Comparison of Message Queuing Systems

Fu, Guo; Zhang, Yanfeng; Yu, Ge

doi:10.1109/access.2020.3046503

Cited by 45 publications

(28 citation statements)

References 19 publications

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“…The messaging integration style is asynchronous messaging and can decouple all the applications so the sender does not need to wait for the receiver, and we can develop the application efficiently in the real-time monitoring system, as shown in Figure 11. In an earlier study [24], the authors compared five typical message queuing systems, including Kafka [25], RabbitMQ [26], RocketMQ [27], ActiveMQ [28], and Pulsar [29]. They also tested the latency and the throughput in the three scenarios, including the message size, number of producers/consumers, and number of partitions.…”

Section: Message Queuing Systemmentioning

confidence: 99%

Real-Time UAV Trash Monitoring System

Liao

Juang

2022

Applied Sciences

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This study proposes a marine trash detection system based on unmanned aerial vehicles (UAVs) and aims to replace manpower with UAVs to detect marine trash efficiently and provide information to government agencies regarding real-time trash pollution. Internet technology and computer–machine interaction were applied in this study, which involves the deployment of a marine trash detection system on a drone’s onboard computer for real-time calculations. Images of marine trash were provided to train a modified YOLO model (You Look Only Once networks). The UAV was shown to be able to fly along a predefined path and detect trash in coastal areas. The detection results were sent to a data streaming platform for data processing and analysis. The Kafka message queuing system and the Mongo database were used for data transmission and analysis. It was shown that a real-time drone map monitoring station can be built up at any place where mobile communication is accessible. While a UAV is automatically controlled by an onboard computer, it can also be controlled through a remote station. It was shown that the proposed system can perform data analysis and transmit heatmaps of coastal trash information to a remote site. From the heatmaps, government agencies can use trash categories and locations to take further action.

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Section: Message Queuing Systemmentioning

confidence: 99%

Real-Time UAV Trash Monitoring System

Liao

Juang

2022

Applied Sciences

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“…In such cases, AC methods were utilized to tune controller parameters, [ 57,58 ] or identify the process dynamics [ 59 ] and help generate control actions. [ 60–63 ]…”

Section: Process Control Applicationsmentioning

confidence: 99%

“…As to the use of application software, approximately 60% of the studies, utilized MATLAB software for controller development, integration, or real‐time implementation. [ 60,63,69 ] Other researchers mostly used Tensorflow [ 64 ] and Python. [ 83 ] Some studies have integrated different functionalities of more than one software applications, for example, (i) MATLAB's process simulation module with Python's ANN generator APIs–PyTorch and Keras [ 70 ] and (ii) hybrid training module of Tensorflow and Python's Lambda deep learning workstation.…”

Section: Process Control Applicationsmentioning

confidence: 99%

A survey and comparative evaluation of actor‐critic methods in process control

Dutta

Upreti

2022

Can J Chem Eng

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Actor-critic (AC) methods have emerged as an important class of reinforcement learning (RL) paradigm that enables model-free control by acting on a process and learning from the consequence. To that end, these methods utilize artificial neural networks, which are synergized for action evaluation and optimal action prediction. This feature is highly desirable for process control, especially when the knowledge about a process is limited or when it is susceptible to uncertainties. In this work, we summarize important concepts of AC methods and survey their process control applications. This treatment is followed by a comparative evaluation of the set-point tracking and robustness of controllers based on five prominent AC methods, namely, DDPG, TD3, SAC, PPO, and TRPO, in five case studies of varying process nonlinearity. The training demands and control performances indicate the superiority of DDPG and TD3 methods, which rely on off-policy, deterministic search for optimal action policies. Overall, the knowledge base and results of this work are expected to serve practitioners in their efforts toward further development of autonomous process control strategies.

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“…Apache Camel [65] is an open source integration framework designed as message-oriented middleware that provides interfaces for the Enterprise Integration Patterns. A good comparison of some of the most recent message queuing systems (Kafka, RabbitMQ, RocketMQ, ActiveMQ, and Pulsar) can be found in [66]. A curating list of existing streaming frameworks and applications can also be found in [67].…”

Section: Other Available Toolsmentioning

confidence: 99%

“…For example, in data ingestion and transformation, Apache Storm [54] can be used for high volume real-time data, Apache Nifi can be used for medium volume real-time data, and Sqoop can be used for batch data with low latency requirements. In addition, extensive comparisons of some of the latest message queueing systems (e.g., Kafka, RabbitMQ, RocketMQ, ActiveMQ, and Pulsar) have shown that Kafka can be used for higher throughput, RabbitMQ is more suitable for lower latency, while RocketMQ can provide both low latency and high quality of service for applications and services [66]. Some tools, such as Apache Druid, only allow querying a single data set, so joining with multiple other data sources is not possible.…”

Section: B Challengesmentioning

confidence: 99%