Comparative Evaluation of Dataflow Component Selection Methods in Distributed MQTT Broker Environment
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- Ishihara Shintaro
- Graduate School of Frontier Informatics, Kyoto Sangyo University
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- Yasuda Kazuma
- Graduate School of Frontier Informatics, Kyoto Sangyo University
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- Abe Kota
- Graduate School of Engineering, Osaka City University
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- Teranishi Yuuichi
- National Institute of Information and Communications Technology
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- Akiyama Toyokazu
- Graduate School of Frontier Informatics, Kyoto Sangyo University
説明
<p>Internet of Things applications often require reducing the communication delay and the traffic between sensors and actuators. In addition, research and development of dataflow platforms is ongoing. In these platforms, to meet the aforementioned requirements, geographically distributed dataflow components should be connected appropriately using edge computing environments. Existing approaches provide efficient communication considering the geographical distance using a distributed publish/subscribe broker that uses the peer-to-peer overlay; however, they do not consider resource information. In this paper, we propose two component selection methods - Multicast and Anycast - for inter-component communication considering resource information. Multicast selects a component by collecting resource information before selection, while Anycast selects a component using the aggregated resource information together with the overlay maintenance. We evaluated the hop count and amount of traffic using each method. As a result, we clarified that Anycast provides a smaller number of hops than Multicast when the aggregated values are sufficiently updated or there are sufficient available components. Furthermore, we examined how to use Anycast and Multicast considering the traffic volume against the sending interval of the component reservation request and the interval between sending the update query for maintaining the overlay. The sender node can choose the component selection method based on the number of hops and the traffic volume.</p>
収録刊行物
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- Journal of Information Processing
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Journal of Information Processing 29 (0), 787-800, 2021
一般社団法人 情報処理学会
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詳細情報 詳細情報について
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- CRID
- 1390290393638232576
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- NII論文ID
- 130008129556
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- ISSN
- 18826652
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可