| Paper Abstract and Keywords |
| Presentation |
2021-11-16 11:30
Selective Data Transmission Method Based on Data Completeness for Large Spatio-temporal Data Retention
Hotaka Kaneyasu, Daiki Nobayashi, Kazuya Tsukamoto, Takeshi Ikenaga (KIT) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
With the development and spread of IoT technology, various devices have been connected to networks. Some data generated from IoT devices depends on geographical location and time (Spatio-temporal Data, STD). For location-dependent applications, it is effective to spread and acquire STD at the location in real-time. Therefore, to aim for local production and consumption of STD, we have proposed the STD retention system using vehicles and evaluated its performance with STD consisting of a single packet. However, there are various types and sizes of STD such as sensing data, photos, video, and so on. To retain these STD efficiently, a transmission control method considering large-capacity data is necessary. Hence, in this paper, we propose a selective data transmission control method to realize large STD retention based on data completeness. Finally, we evaluated our proposed method using simulations. The simulation result clarifies that our proposed method can suppress packet collisions by reducing incomplete data transmission and retain large STD efficiently. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Vehicle Network / Local Production and Consumption of Data / Spatio-Temporal Data Retension / / / / / |
| Reference Info. |
IEICE Tech. Rep. |
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| Conference Information |
| Committee |
RISING |
| Conference Date |
2021-11-15 - 2021-11-17 |
| Place (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
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| Paper Information |
| Registration To |
RISING |
| Conference Code |
2021-11-RISING |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Selective Data Transmission Method Based on Data Completeness for Large Spatio-temporal Data Retention |
| Sub Title (in English) |
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Vehicle Network |
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Local Production and Consumption of Data |
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Spatio-Temporal Data Retension |
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| 1st Author's Name |
Hotaka Kaneyasu |
| 1st Author's Affiliation |
Kyushu Institute of Technology (KIT) |
| 2nd Author's Name |
Daiki Nobayashi |
| 2nd Author's Affiliation |
Kyushu Institute of Technology (KIT) |
| 3rd Author's Name |
Kazuya Tsukamoto |
| 3rd Author's Affiliation |
Kyushu Institute of Technology (KIT) |
| 4th Author's Name |
Takeshi Ikenaga |
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Kyushu Institute of Technology (KIT) |
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Author-1 |
| Date Time |
2021-11-16 11:30:00 |
| Presentation Time |
50 minutes |
| Registration for |
RISING |
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