New Data Importance Metric for Communication Control in Spatial Knowledge Services
| Project/Area Number |
17H01732
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Information network
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
矢守 恭子 朝日大学, 経営学部, 教授 (20350449)
笠井 裕之 電気通信大学, 大学院情報理工学研究科, 教授 (40312079)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥18,720,000 (Direct Cost: ¥14,400,000、Indirect Cost: ¥4,320,000)
Fiscal Year 2019: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2018: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2017: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
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| Keywords | 実空間情報 / 機械学習 / 可推定性 / 可代替性 / 経済学モデル / モバイルセンサ基盤 / ユーザ誘導 / ネットワークアーキテクチャ / データ重要度 / 実空間ナレッジ / Quality of Service / Internet of Things / Software-Defined Network / Unmanned Aerial Vehicle |
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| Outline of Final Research Achievements |
It is expected that the information and communication technology delivers fine-grained data about spatial information. An example scenario is that smart cars interact with drivers using such information, which could realize the society with no traffic congestion and accident. However, the data volume of spatial information can be huge; the communication network can be a bottleneck because of its limited capacity. Therefore, this study has established the model that represents importance of data and has proposed a control scheme that assigns communication and computational resource in accordance of the importance of data in terms of how easily the data can be estimated and replaced from and with other data. Considering the scenario mentioned above, our result has verified that the proposed scheme can reduce the retrieval latency of spatial information.
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| Academic Significance and Societal Importance of the Research Achievements |
本成果の学術的意義は、機械学習や経済学を用いて、データ各々の重要度を評価可能なモデルを確立したことである。このモデルに基づく様々な応用研究が可能であり、学術界での波及効果が期待できる。一方、社会的には、本成果を用いることで少ないデータで高い精度を達成することができるため、電波資源の節約や消費エネルギーの削減を可能にする点で意義が大きい。
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Report
(4 results)
Research Products
(93 results)
