| Project/Area Number |
23K10985
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 60010:Theory of informatics-related
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| Research Institution | The University of Aizu |
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Principal Investigator |
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| Project Period (FY) |
2023-04-01 – 2026-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2025: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2024: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2023: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | Dynamic networks / Anonymous computations / Dynamic Networks / Anonymous Networks / History Trees / Average Consensus / Counting |
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| Outline of Research at the Start |
A network is "dynamic" when its communication links may change unpredictably; for privacy reasons, the nodes of such networks may be considered anonymous. The goal of this project is to advance our understanding of Anonymous Dynamic Networks and develop efficient and reliable algorithms for them.
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| Outline of Annual Research Achievements |
In this fiscal year, I advanced our theoretical knowledge about Anonymous Dynamic Networks.
An example of a possible application is the following. In a network of smartphones running a COVID-19 app, it is desirable to obtain statistics about the percentage of infected people without disclosing any data about people's identities or anything that could link to a person's location or habits. This research makes it possible to solve this and other problems very efficiently.
In particular, this year I focused on the scenario in which the network is "congested": in other words, there is so much traffic in the network that only a very small amount of data can be transmitted at each inteaction. Essentially, I designed a technique that allows our algorithms to deal with this challenging scenario with a small performance loss.
As part of this project, I also traveled to conferences and joined research partners from overseas who are experts in this field of research. Our collaboration has been fruitful and has revealed new and interesting ways to approach computation in Anonymous Dynamic Networks, especially in cases where previous techniques were ineffective or very inefficient. We are also writing a book on the subject, which can be used to train graduate students and help other researchers familiarize with this fast-developing research area.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Designing efficient algorithm for congested networks was one of the main goals of this project. Although the algorithms we developed for this scenario are not extremely efficient, there is a theoretical limit to how efficient they may be. In fact, our solution is very close to this limit, and therefore it is almost optimal. My collaboratos and I consider it a successful achievement, and we managed to publish a preliminary report of it at PODC 2023, the most prestigious conference in this research area. We also have partial results in other directions, including fault tolearnce, self-stabilization, and asymmetric communications.
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| Strategy for Future Research Activity |
In the future, I plan to further develop the theory of Anonymous Dynamic Networks in new directions. We have preliminary results on more and more challenging and restrictive network scenarios, and we also have ambitious goals related to fault tolerance. Indeed, we would like to design robust algorithms that give reliable results even if some of the devices in the network are broken or malicious and send incorrect messages. We have developed the basic theoretical tools needed for this task and we are applying them with some success. We expect to make more breakthroughs in the upcoming years and publish our findings at top international scientific venues.
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