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Investigation of Performance and Configuration of a Selected IoT System—Middleware Deployment Benchmarking and Recommendations

Applied sciences, 2022-05, Vol.12 (10), p.5212 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app12105212

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  • Title:
    Investigation of Performance and Configuration of a Selected IoT System—Middleware Deployment Benchmarking and Recommendations
  • Author: Kałaska, Robert ; Czarnul, Paweł
  • Subjects: application development for scalable architectures ; Clients ; Computer centers ; Configuration management ; Containerization ; Cores ; Feasibility studies ; Flexibility ; Internet of Things ; Investigations ; IoT deployment ; IoT middleware performance ; large-scale HPC application containerization ; Middleware ; Nodes ; Sensors ; Servers ; Software ; Workloads
  • Is Part Of: Applied sciences, 2022-05, Vol.12 (10), p.5212
  • Description: Nowadays Internet of Things is gaining more and more focus all over the world. As a concept it gives many opportunities for applications for society and it is expected that the number of software services deployed in this area will still grow fast. Especially important in this context are properties connected with deployment such as portability, scalability and balance between software requirements and hardware capabilities. In this article, we present results of practical tests with multiple clients representing sensors sending notifications to an IoT middleware—DeviceHive. Firstly, we investigate performance using two deployment configurations—containerized and bare-metal showing small overhead of the former under different loads by various numbers of IoT clients. We present scaling of the middleware on the server side using various numbers of cores as well as HyperThreading for all aforementioned configurations. Furthermore, we also investigated how containarization affects performance when the system is scaled with various numbers of nodes each using a predefined number of cores, considering memory usage of various configurations. The latter could be found useful when assigning cores to Docker nodes in cloud environments.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 2076-3417
    EISSN: 2076-3417
    DOI: 10.3390/app12105212
  • Source: ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
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