Participated in IEEE GLOBECOM 2023
Prof. Akihito Hiromori, Prof. Hamada Rizk, and M2 student Ren Ozeki participated in IEEE GLOBECOM 2023 and presented two papers.
Publications & Talks
International Conference · 2023
Adaptive Pub/sub Message Delivery for World Weather IoT
Abstract
This study proposes an adaptive message delivery mechanism for a broker in the WMO Information System 2.0 (WIS2.0), a next-generation world weather loT data exchange system, to satisfy the time constraints (deadlines) of the messages requested by subscribers in the system. Since WIS2.0 is a worldwide, heterogeneous system, each broker has to handle a variety of requests by each subscriber to receive messages (data) with different time constraints and sizes. Therefore, it needs to control the timing of message delivery to subscribers, considering publishers' delivery timing, subscribers' processing performance, network bandwidth, message types, data volume, and so on. To this end, the proposed method takes a reinforcement learning-based approach where the feasible timing to transmit messages is learned by monitoring the message arrival patterns from the publishers, message ACK delay from the subscriber, and the sensing window size, all of which are easily observable at the broker. Experiments using a network simulator showed that under the best-case scenario, the proposed method could achieve 10% higher message goodput compared to DWEDF-RL, the state-of-the-art RL-based packet scheduling method tailored to the pub/sub model.
Research Note
This study proposes an adaptive message delivery mechanism for a broker in the WMO Information System 2.0 (WIS2.0), a next-generation world weather IoT data exchange system, to satisfy the time constraints (deadlines) of the messages subscribers request in the system.
Since WIS2.0 is a worldwide, heterogeneous system, each broker has to handle various requests by each subscriber to receive messages (data) with different time constraints and sizes. Therefore, it needs to control the timing of message delivery to subscribers, considering publishers’ delivery timing, subscribers’ processing performance, network bandwidth, message types, data volume, and so on. To this end, the proposed method takes a reinforcement learning-based approach where the feasible timing to transmit messages is learned by monitoring the message arrival patterns from the publishers, application layer ACK (A-ACK) delay from the subscriber, and the sending window size, all of which are easily observable at the broker. Furthermore, since A-ACK depends on message contents, our method employs content-aware prediction for the response time of A-ACK utilizing a message Topic that describes message contents in natural language.
Published Papers
- 小関廉, 廣森聡仁, and 山口弘純. "Pub/sub モデルにおけるリアルタイム配信に向けた強化学習ベースの制御手法の検討." 研究報告高度交通システムとスマートコミュニティ (ITS) 2022.10 (2022): 1-8.
- 小関廉, 廣森聡仁, and 山口弘純. "言語モデルによる付加情報を用いた pub/sub システムのメッセージ制御." 研究報告マルチメディア通信と分散処理 (DPS) 2023.10 (2023): 1-8.
- 小関廉, 廣森聡仁, and 山口弘純. "即時性の高い広域情報を扱う pub/sub システムにおける適応的メッセージ制御." 研究報告モバイルコンピューティングと新社会システム (MBL) 2023.34 (2023): 1-8.
- Ozeki, Ren, Akihito Hiromori, and Hirozumi Yamaguchi. "Adaptive Pub/Sub Message Delivery for World Weather IoT." GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023.
Related Lab Activities
Related Projects
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