| 研究課題/領域番号 |
16K16053
|
|---|
| 研究機関 | 国立研究開発法人情報通信研究機構 |
|---|
研究代表者 |
SHAO XUN 国立研究開発法人情報通信研究機構, ネットワークシステム研究所ネットワーク基盤研究室, 研究員 (80774588)
|
|---|
| 研究期間 (年度) |
2016-04-01 – 2018-03-31
|
| キーワード | IoT (Internet of Things) / big data / in-network processing / overlay / CCN/NFN |
|---|
| 研究実績の概要 |
In FY 2016, I almost achieved the research objectives. Specifically, the following achievements have been made: I proposed novel in-network big data processing architecture for IoT applications and services. The proposed architecture makes fundamental difference from the existing centralized big data processing architectures in that it takes the advantages of distributed computing resources located in the edge of the Internet. To realize the architecture, I clarified the major issues and challenges, and developed the key technologies including the self-organizing technologies for distributed computing resources, flash crowds alleviation methods, and load balancing mechanisms. In FY 2017, the focus will be put on the performance improvement and practical application development.
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
This research aims to develop novel fundamental in-network data processing technologies to support and develop IoT applications and services. For this purpose, in FY 2016, I made the following progress:
1. I conducted extensive survey of IoT, cloud computing, and some emerging distributed computing technologies.
2. Based on the survey, I proposed novel in-network big data processing architecture, which explores the opportunities to carry out data processing with the computing resources located in the edge of the Internet.
3. I proposed novel self-organizing methods to address the key issues such as flash crowds alleviation and load balancing.
4. The proposed technologies were verified rigorously with mathematical models, and validated with simulation and testbed experiments.
|
| 今後の研究の推進方策 |
The emphasis is put on the two aspects: performance enhancement and practical applications in stream data processing.
1. I will take the advantages of the stat-of-the-art networking technologies: content centric network (CCN) and named function network (NFN). Compared with the conventional overlay-based deployment, the CCN/NFN-based implementation will improve the performance significantly.
2. I will apply the proposed technologies to stream data processing applications. For this purpose, in addition to satisfying the basic requirements of big data processing, more specific issues have to be considered and addressed.
In addition, in FY 2017, I will implement a demonstration system to validate the proposed technologies, and promote the application to both academy and industry.
|
| 次年度使用額が生じた理由 |
1. Travel expenses saving. (1) I participated the ACM ICN conference, and it was held in Japan the last year. (2) In FY 2016, I emphasized on accomplishing the foundations of the technologies, and did not hold meetings with collaborators abroad.
2. Device cost saving. In FY 2016, because only preliminary simulations were conducted, I took the advantage of the computers available in my affiliation.
|
| 次年度使用額の使用計画 |
1. International conference participation. To discuss with the other researchers and promote application of the research results, I will participate a prestigious International conference, giving a presentation or demonstration if possible.
2. Purchase of computer. In FY 2017, because large-scale simulations are planed, I will buy an additional computer.
|
